From 9435b3ede6bfd6bdf31293f98b33a11f39a9aa0c Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Tue, 9 Mar 2021 10:38:11 +0100 Subject: [PATCH 01/18] initial conversion --- rfcs/images/15_clustering/cluster-mode.png | Bin 0 -> 132797 bytes rfcs/images/15_clustering/no-cluster-mode.png | Bin 0 -> 49301 bytes rfcs/images/15_clustering/perf-4-workers.png | Bin 0 -> 446234 bytes .../perf-clustering-2-worker.png | Bin 0 -> 450498 bytes .../15_clustering/perf-no-clustering.png | Bin 0 -> 452150 bytes rfcs/text/0015_nodejs_clustering.md | 426 ++++++++++++++++++ 6 files changed, 426 insertions(+) create mode 100644 rfcs/images/15_clustering/cluster-mode.png create mode 100644 rfcs/images/15_clustering/no-cluster-mode.png create mode 100644 rfcs/images/15_clustering/perf-4-workers.png create mode 100644 rfcs/images/15_clustering/perf-clustering-2-worker.png create mode 100644 rfcs/images/15_clustering/perf-no-clustering.png create mode 100644 rfcs/text/0015_nodejs_clustering.md diff --git 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NodeJS underlying socket implementation allows multiple processes to listen to the same ports, +performing http traffic balancing between the workers for us. + +![image](../images/15_clustering/cluster-mode.png) + +The coordinator sole responsibility is to orchestrate the workers. It would not be a 'super' worker handling both +the job of a worker while being in charge of managing the other workers. + +# Performance testing + +## Local testing + +These tests were performed against a local development machine, with a 8-core cpu (2.4 GHz 8-Core Intel Core i9 - 32 GB 2400 MHz DDR4), +using the default configuration of the `kibana-load-testing` tool. + +### Raw results + +#### Non-clustered mode + +![image](../images/15_clustering/perf-no-clustering.png) + +#### Clustered mode, 2 workers + +![image](../images/15_clustering/perf-clustering-2-worker.png) + +#### Clustered mode, 4 workers + +![image](../images/15_clustering/perf-4-workers.png) + +### Analysis + +- Between non-clustered and 2-worker cluster mode, we observe a 20/25% gain in the 50th percentile response time. + Gain for the 75th and 95th are between 10% and 40% +- Between 2-worker and 4-workers cluster mode, the gain on 50th is negligible, but the 75th and the 95th are + significantly better on the 4-workers results, sometimes up to 100% gain (factor 2 ratio) + +Overall, switching to 2 workers comes with the most significant improvement in the 50th pct, +and increasing further to 4 workers decreases even more significantly the highest percentiles. +Even if increasing the number of workers doesn’t just linearly increase the performances +(which totally make sense, most of our requests response time is caused by awaiting ES response), +the improvements of the clustering mode on performance under heavy load are far from negligible. + +## Testing against cloud + +There is currently no easy way to test the performance improvements this could provide on Cloud, as we can't +deploy custom builds or branches on Cloud at the moment. + +On Cloud, Kibana is running in a containerised environment using CPU CFS quota and CPU shares. + +If we want to investigate the potential perf improvement on Cloud further, our only option would be to setup a +similar-ish environment locally (which wasn't done during the initial investigation) + +# Implementation proposal + +## Cross-worker communication + +We will be adding a new clustering service to core, that will add the necessary cluster APIs + +For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. Such communication will need to pass through the coordinator, which will also serve as an 'event bus'. + +The base API for such communication will be exposed from the clustering service. + +```ts +export interface ClusteringServiceSetup { + // [...] + broadcast: (type: string, payload?: ClusterMessagePayload, options?: BroadcastOptions) => void; + addMessageHandler: (type: string, handler: MessageHandler) => MessageHandlerUnsubscribeFn; +} +``` + +Notes: +- to reduce cluster/non-cluster mode divergence, in non-clustering mode, these APIs would just be no-ops. + It will avoid to force (most) code to check in which mode Kibana is running before calling them. +- We could eventually use an Observable pattern instead of a handler pattern to subscribe to messages. + +## Executing code on a single worker + +In some scenario, we would like to have some part of the code executed from a single process. The SO migration would be a good example: we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying the migration, and the other wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, as it doesn't actually run a Kibana's Server. + +There are various ways to address such use-case. What seems to be the best compromise right now would be the concept of 'main worker'. The coordinator would arbitrary elect a worker as the 'main' one. The clustering service would then expose an API to let workers identify themselves as main or not. + +```ts +export interface ClusteringServiceSetup { + // [...] + isMainWorker: () => boolean; +} +``` + +Notes: +- in non-clustered mode, `isMainWorker` would always return true, to reduce the divergence between clustered and + non-clustered modes. + +### Example: SO Migration + +To take the example of SO migration, the `KibanaMigrator.runMigrations` implementation could change to +(naive implementation, the function is supposed to return a promise here, did not include that for simplicity): + +```ts +runMigration() { + if(clustering.isMainWorker()) { + this.runMigrationsInternal().then((result) => { + applyMigrationState(result); + clustering.broadcast('migration-complete', { payload: result }, { persist: true }); // persist: true will send message even if subscriber subscribe after the message was actually sent + }) + } + else { + const unsubscribe = clustering.addMessageHandler('migration-complete', ({ payload: result }) => { + applyMigrationState(result); + unsubscribe(); + }); + } +} +``` + +## Sharing state between workers + +This is not identified as necessary at the moment, and IPC broadcast should be sufficient. + +If we do need shared state, we will probably have to use syscall libraries to share buffers such as [mmap-io](https://www.npmjs.com/package/mmap-io), +and expose a higher level API for that from the `clustering` service. + +# Technical impact on the codebase + +This section is meant to be an exhaustive (even if realistically not at the moment) inventory of the changes that would +be required to support clustering mode. + +## Technical impact on Core + +### Handling multi-process logs + +This is an example of log output in a 2 workers cluster, coming from the POC + +``` +[2021-03-02T10:23:41.834+01:00][INFO ][plugins-service] Plugin initialization disabled. +[2021-03-02T10:23:41.840+01:00][INFO ][plugins-service] Plugin initialization disabled. +[2021-03-02T10:23:41.900+01:00][WARN ][savedobjects-service] Skipping Saved Object migrations on startup. Note: Individual documents will still be migrated when read or written. +[2021-03-02T10:23:41.903+01:00][WARN ][savedobjects-service] Skipping Saved Object migrations on startup. Note: Individual documents will still be migrated when read or written. +``` + +The workers logs are interleaved, and, most importantly, there is no way to see which process the log is coming from. +We will need to address that. + +Our options are + +- Have a distinct logging configuration for each worker + +We could do that by automatically adding a suffix depending on the process to the appropriate appenders configuration. +Note that this doesn’t solve the problem for the console appender, which is probably a no-go. + +- Add the process info to the log pattern and output it with the log message + +We could add the process name information to the log messages, and add a new conversion to be able to display it with the pattern layout, such as %process for example. + +the default pattern could evolve to (ideally, only when clustering is enabled) + +``` +[%date][%level][%process][%logger] %message +``` + +The logging output would then look like + +``` +[2021-03-02T10:23:41.834+01:00][INFO ][worker-1][plugins-service] Plugin initialization disabled. +[2021-03-02T10:23:41.840+01:00][INFO ][worker-2][plugins-service] Plugin initialization disabled. +``` + +This will require some changes in the logging system implementation, as currently the BaseLogger has no logic to +enhance the log record with context information before forwarding it to its appenders, but this still +seems to be the best solution. + +### The rolling-file appender + +The rolling process of the `rolling-file` appender is going to be problematic in clustered mode, as it will cause +concurrency issues during the rolling. We need to find a way to have this rolling process clustered-proof. + +Identified options are: + +- have the rolling file appenders coordinate themselves when rolling + +By using a broadcast message based mutex mechanism, the appenders could acquire a ‘lock’ to roll a specific file, and release the lock once the rotation is done. + +- have the coordinator process perform the rolling + +Another option would be to have the coordinator perform the rotation instead. When a rolling is required, the appender would send a message to the coordinator, which would perform the rolling and notify the workers once the process is complete. Note that this option is even more complicated than the previous one, as it forces to move the rolling implementation outside of the appender, without any significant upsides. + +- centralize the logging system in the coordinator (and have the workers send messages to the coordinator when using the logging system) + +We could go further, and change the way the logging system works in clustering mode by having the coordinator centralize the logging system. The worker’s logger implementation would just send messages to the coordinator. If this may be a correct design, the main downside is that the logging implementation would be totally different in cluster and non cluster mode, and is overall way more work that the other options. + +Overall, if no option is trivial, I feel like option 1) is still the most pragmatic one. Option 3) is probably a better +design, but represents more work. It would probably be fine if all our appenders were impacted, but as only the +rolling-file one is, I feel like going with 1) would be ok. + +### The status API + +In clustering mode, the workers will all have an individual status. One could have a connectivity issue with ES +while the other ones are green. Hitting the `/status` endpoint will reach a random (and different each time) worker, +meaning that it would not be possible to know the status of the cluster as a whole. + +We will need to add a centralized status service in the coordinator. Also, as the `/status` endpoint cannot be served +from the coordinator, we will also need to have the workers retrieve the global status from the coordinator to serve +the status endpoint. + +We may also want to have the `/status` endpoint display each individual worker status in addition to the +global status, which may be breaking change in the `/status` API response format. + +### PID file + +Without changes, each worker is going to try to write and read the same PID file. Also, this breaks the whole pid file +usage, as the PID stored in the file will be a arbitrary worker’s PID, instead of the coordinator (main process) PID. + +In clustering mode, we will need to have to coordinator handle the PID file logic, and to disable pid file handling +in the worker's environment service. + +### SavedObjects migration + +In the current state, all workers are going to try to perform the migration. Ideally, we would have only one process +perform the migration, and the other ones just wait for a ready signal. We can’t easily have the coordinator do it, +so we would probably have to leverage the ‘main worker’ concept to do so. + +The SO migration v2 is supposed to be resilient to concurrent attempts though, as we already support multi-instances +Kibana, so this can probably be considered an improvement. + +## Open questions and things to solve + +### Memory consumption +In cluster mode, node options such as `max-old-space-size` will be used by all processes. E.g using +`--max-old-space-size=1024` in a 2 workers cluster would have a maximum memory usage of 3gb (1 coordinator + 2 workers). + +If this something we will need to document somewhere? + +### Workers error handling + +When using `cluster`, the common best practice is to have the coordinator recreate workers when they terminate unexpectedly. +However, given Kibana's architecture, some failures are not recoverable (workers failing because of config validation, failed migration...). + +For instance, if a worker (well, all workers) terminates because of an invalid configuration property, it doesn't make +any sense to have the coordinator recreate them indefinitely, as the error requires manual intervention. + +Should we try to distinguish recoverable and non-recoverable errors, or are we good terminating the main Kibana process +when any worker terminates unexpectedly for any reason (After all, this is already the behavior in non-cluster mode)? + +### Data folder + +The data folder (`path.data`) is currently the same for all workers. + +We still have to identify with the teams if this is going to be a problem. It could be, for example, if some plugins +are accessing files in write mode, which could result in concurrency issues between the workers. + +If that was confirmed, we would have to create and use a distinct data folder for each worker. + +One pragmatic solution would be, when clustering is enabled, to create a sub folder under path.data for each worker. + +If we need to do so, should this be considered a breaking change, or do we assume the usage of the data folder is an +implementation detail and not part of our public 'API'? + +### instanceUUID + +The same instance UUID (`server.uuid` / `{dataFolder}/uuid`) is currently used by all the workers. + +We still need to identify with the teams if this is going to be a problem, in which case we would need to have distinct +instance uuid per workers. + +Note that this could be a breaking change, as the single `server.uuid` configuration property would not be enough. +We may want to introduce a new `workerId` variable and create the associated API to expose this value to plugins? + +### The Dev CLI + +In development mode, we are already spawning processes from the main process: The Kibana server running in the main process +actually just kickstarts core to get the configuration and services required to instantiate the `CliDevMode` +(from the legacy service), which itself spawns a child process to run the actual Kibana server. + +Even if not technically blocking, it would greatly simplify parts of the workers and coordinator logic if we were able +to finally extract the dev cli from Core and to avoid having it create a temporary server just to access the Legacy service +and configuration. + +Note that extracting and refactoring the dev cli is going to be required anyway to remove the last bits of legacy, +as it currently relies on the legacy configuration to run (and is running from the legacy service). + +## Technical impact on our plugins codebase + +### Identifying things that may break + +- Concurrent access to the same resources + +Is there, for example, some part of the code that is accessing and writing files from the data folder (or anywhere else) +and makes the assumption that it is the sole process actually writing to that file? + +- Using instanceUUID as a unique Kibana process identifier + +Is there, for example, schedulers that are using the instanceUUID a single process id, in opposition to a single +Kibana instance id? Are there situations where having the same instance UUID for all the workers is going to be a problem? + +- Things needing to run only once per Kibana instance + +Is there any part of the code that needs to be executed only once in a multi-worker mode, such as initialization code, +or starting schedulers? + +An example would be reporting's queueFactory pooling. As we want to only be running a single headless at a time per +Kibana instance, only one worker should have pooling enabled. + +### Identified required changes + +(Probably not exhaustive at the moment) + +#### Reporting + +We will probably want to restrict to a single headless per Kibana instance. For that, we will have to change the logic +in [createQueueFactory](https://github.com/elastic/kibana/blob/4584a8b570402aa07832cf3e5b520e5d2cfa7166/x-pack/plugins/reporting/server/lib/create_queue.ts#L60-L64) +to only have the 'main' worker be pooling for reporting tasks. + +#### Telemetry + +- Server side fetcher + +The telemetry/server/fetcher.ts will attempt sending the telemetry usage multiple times once per day from each process. +We do store a state in the SavedObjects store of the last time the usage was sent to prevent sending multiple times +(although race conditions might occur). + +- Tasks storing telemetry data + +We have tasks across several plugins storing data in savedobjects specifically for telemetry. Under clustering these +tasks will be registered multiple times. + +Note that sending the data multiple times doesn’t have any real consequences, so this should be considered +non-blocking and only an improvement. + +#### TaskManager + +Currently, task manager does "claims" for jobs to run based on the server uuid. I think this would still work with +workers - each task manager in the worker would be doing "claims" for the same server uuid, which I think is basically +the same as setting your max_workers to "current max_workers * number of workers" + +We probably only want one worker doing the task claims, and then when it gets tasks to run, sends them to a worker to run. +Short term, having only the 'main' worker perform the task claims and executions should be good enough. + +#### Alerting + +Do we need the alerting task runner (`TaskRunner`, `TaskRunnerFactory`) to be running on a single worker? + +# Summary of the potential user-facing breaking changes + +## status API + +If we want to have the status API returns each individual worker's status, we will need to change the output of the +status API in clustering mode. + +Note that the new format for /api/status is still behind a v8format flag, meaning that if we do these changes before 8.0, +we won't be introducing any breaking change later. + +## instanceUUID + +Depending on our decision regarding the instanceUUID problematic, we may have to change the server.uuid configuration +property when clustering mode is enabled, which would be a breaking change. + +## distinct logging configuration + +If we decide to have each worker output log in distinct files, we would have to change the logging configuration to +add a prefix/suffix to each log file, which would be a breaking change. Note that this option is probably not the one +we'll choose. + +## data folder + +We may need to have each worker uses a distinct data folder. Should this be considered a breaking change? + +# Drawbacks + +Why should we *not* do this? Please consider: + +- implementation cost, both in term of code size and complexity +- the impact on teaching people Kibana development +- integration of this feature with other existing and planned features +- cost of migrating existing Kibana plugins (is it a breaking change?) + +There are tradeoffs to choosing any path. Attempt to identify them here. + +# Alternatives + +What other designs have been considered? What is the impact of not doing this? + +# Adoption strategy + +If we implement this proposal, how will existing Kibana developers adopt it? Is +this a breaking change? Can we write a codemod? Should we coordinate with +other projects or libraries? + +# How we teach this + +What names and terminology work best for these concepts and why? How is this +idea best presented? As a continuation of existing Kibana patterns? + +Would the acceptance of this proposal mean the Kibana documentation must be +re-organized or altered? Does it change how Kibana is taught to new developers +at any level? + +How should this feature be taught to existing Kibana developers? + +# Unresolved questions + +None (well, except every single section of the document). \ No newline at end of file From e977dba34e802c7d3895d44d3d8ea95aef42ce16 Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Tue, 9 Mar 2021 10:42:19 +0100 Subject: [PATCH 02/18] add RFC PR link --- rfcs/text/0015_nodejs_clustering.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index b880b0178e215..d6f24670c8a92 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -1,5 +1,5 @@ - Start Date: 2021-03-09 -- RFC PR: (leave this empty) +- RFC PR: https://github.com/elastic/kibana/pull/94057 - Kibana Issue: https://github.com/elastic/kibana/issues/68626 - POC issue: https://github.com/elastic/kibana/pull/93380 From 22c8fbfde1c21fcc3a12465dfe3eabf3631b5ff6 Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Tue, 9 Mar 2021 11:11:23 +0100 Subject: [PATCH 03/18] The missing chapters --- rfcs/text/0015_nodejs_clustering.md | 42 +++++++++++++++-------------- 1 file changed, 22 insertions(+), 20 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index d6f24670c8a92..7f9d5ba88550b 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -391,35 +391,37 @@ We may need to have each worker uses a distinct data folder. Should this be cons # Drawbacks -Why should we *not* do this? Please consider: - -- implementation cost, both in term of code size and complexity -- the impact on teaching people Kibana development -- integration of this feature with other existing and planned features -- cost of migrating existing Kibana plugins (is it a breaking change?) - -There are tradeoffs to choosing any path. Attempt to identify them here. +- Implementation cost is going to be significant, both in core and in plugins. Also, this will have to be a collaborative + effort, as we can't enable the clustered mode in production until all the identified breaking changes has been addressed. + +- Even if easier to deploy, it doesn't really provide anything more than a multi-instances Kibana setup. + +- This will complexify the code, especially in Core were some part of the logic will drastically change between clustered and +non-clustered modes (e.g the status API). + +- It could introduce subtle bugs in clustered mode, as we may overlook some breaking changes, or new features may omit to +ensure clustered mode compatibility. + +- Proper testing of all the edge case is going to be tedious, if not just realistically impossible. # Alternatives -What other designs have been considered? What is the impact of not doing this? +Regarding the whole proposal, an alternative would be to provide tooling to ease the deployment of multi-instance Kibana setups. + +Regarding the implementation proposal, the discussion is still ongoing. # Adoption strategy -If we implement this proposal, how will existing Kibana developers adopt it? Is -this a breaking change? Can we write a codemod? Should we coordinate with -other projects or libraries? +Phase 1: we perform the required changes in `Core`, and add the `clustering.enabled` configuration property for development mode only. +That way, we allow developers to test their features against clustering mode and to adapt their code to use the new `clustering` API +and service. -# How we teach this +Phase 2: when all the required changes have been performed, we enable the `clustering` configuration on production mode as a `beta` feature. +We would ideally also add telemetry collection for the clustering usages (actual metrics TBD) to have a precise vision of the adoption of the feature. -What names and terminology work best for these concepts and why? How is this -idea best presented? As a continuation of existing Kibana patterns? - -Would the acceptance of this proposal mean the Kibana documentation must be -re-organized or altered? Does it change how Kibana is taught to new developers -at any level? +# How we teach this -How should this feature be taught to existing Kibana developers? +During phase 1, we should create documentation on the clustering mode: best practices, how to identify code that may breaks in clustered mode, and so on. # Unresolved questions From e1cfb5889f7c448ccb140036df4d90d03df24095 Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Tue, 9 Mar 2021 11:31:03 +0100 Subject: [PATCH 04/18] more details on the clustering service --- rfcs/text/0015_nodejs_clustering.md | 95 ++++++++++++++++++++++++++--- 1 file changed, 88 insertions(+), 7 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 7f9d5ba88550b..51f0bc50ab314 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -78,11 +78,80 @@ similar-ish environment locally (which wasn't done during the initial investigat # Implementation proposal -## Cross-worker communication +## enabling clustering mode + +Enabling clustering mode will be done using the `clustering.enabled` configuration property. + +The whole `clustering` configuration would look like: + +```ts +export const config = { + path: 'clustering', + schema: schema.object({ + enabled: schema.boolean({ defaultValue: false }), + workers: schema.number({ defaultValue: 2 }), + }), +}; +``` + +Notes: +- What should be the default value for `clustering.workers`? We could go with `Max(1, os.cpus().length - 1)`, but do we really want to use all cpus by default, + knowing that every worker is going to have its own memory usage. + +## The clustering service + +We will be adding a new clustering service to core, that will add the necessary cluster APIs, and would be accessible via core's setup and start contracts (`coreSetup.clustering` and `coreStart.clustering`). + +At the moment, no need to extend Core's request handler context with clustering related APIs has been identified. + +The contract interface would look like (more APIs could be added depending on the discussions on this RFC) + +```ts +type ClusterMessagePayload = Serializable; + +interface BroadcastOptions { + /** + * If true, will also send the message to the worker that sent it. + * Defaults to false. + */ + sendToSelf?: boolean; + /** + * If true, the message will also be sent to subscribers subscribing after the message was effectively sent. + * Defaults to false. + */ + persist?: boolean; +} -We will be adding a new clustering service to core, that will add the necessary cluster APIs +export interface ClusteringServiceSetup { + /** + * Return true if clustering mode is enabled, false otherwise + */ + isEnabled: () => boolean; + /** + * Return the current worker's id. In non-clustered mode, will return `1` + */ + getWorkerId: () => number; + /** + * Broadcast a message to other workers. + * In non-clustered mode, this is a no-op + */ + broadcast: (type: string, payload?: ClusterMessagePayload, options?: BroadcastOptions) => void; + /** + * Registered a handler for given `type` of IPC messages + * In non-clustered mode, this is a no-op that returns a no-op unsubscription callback. + */ + addMessageHandler: (type: string, handler: MessageHandler) => MessageHandlerUnsubscribeFn; + /** + * Returns true if the current worker has been elected as the main one. In non-clustered mode, will return true + */ + isMainWorker: () => boolean; +} +``` + +## Cross-worker communication -For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. Such communication will need to pass through the coordinator, which will also serve as an 'event bus'. +For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. Such communication +will need to pass through the coordinator, which will also serve as an 'event bus', or IPC forwarder. The base API for such communication will be exposed from the clustering service. @@ -95,15 +164,20 @@ export interface ClusteringServiceSetup { ``` Notes: -- to reduce cluster/non-cluster mode divergence, in non-clustering mode, these APIs would just be no-ops. +- to reduce clustered and non-clustered mode divergence, in non-clustered mode, these APIs would just be no-ops. It will avoid to force (most) code to check in which mode Kibana is running before calling them. - We could eventually use an Observable pattern instead of a handler pattern to subscribe to messages. ## Executing code on a single worker -In some scenario, we would like to have some part of the code executed from a single process. The SO migration would be a good example: we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying the migration, and the other wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, as it doesn't actually run a Kibana's Server. +In some scenario, we would like to have some part of the code executed from a single process. The SO migration would be a good example: +we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying the migration, +and the other wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, +as it doesn't actually run a Kibana's Server. -There are various ways to address such use-case. What seems to be the best compromise right now would be the concept of 'main worker'. The coordinator would arbitrary elect a worker as the 'main' one. The clustering service would then expose an API to let workers identify themselves as main or not. +There are various ways to address such use-case. What seems to be the best compromise right now would be the concept of +'main worker'. The coordinator would arbitrary elect a worker as the 'main' one. The clustering service would then expose +an API to let workers identify themselves as main or not. ```ts export interface ClusteringServiceSetup { @@ -138,9 +212,16 @@ runMigration() { } ``` +Notes: + - to be sure that we do not encounter a race condition with the event subscribing / sending (workers subscribing after + the main worker actually send the `migration-complete` event and then waiting indefinitely), we are using the `persist` option of the `broadcast` API. + I'm honestly not sure this is the best pattern, but I couldn't come with anything better (maybe shared state instead?). + This is probably something else we should discuss. + + ## Sharing state between workers -This is not identified as necessary at the moment, and IPC broadcast should be sufficient. +This is not identified as necessary at the moment, and IPC broadcast should be sufficient, hopefully. If we do need shared state, we will probably have to use syscall libraries to share buffers such as [mmap-io](https://www.npmjs.com/package/mmap-io), and expose a higher level API for that from the `clustering` service. From 4603408f92f0ca7a348544eaa6782168062f95ba Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Tue, 9 Mar 2021 12:45:51 +0100 Subject: [PATCH 05/18] self review --- rfcs/text/0015_nodejs_clustering.md | 87 +++++++++++++++++------------ 1 file changed, 52 insertions(+), 35 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 51f0bc50ab314..958acb898f962 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -1,7 +1,7 @@ - Start Date: 2021-03-09 - RFC PR: https://github.com/elastic/kibana/pull/94057 - Kibana Issue: https://github.com/elastic/kibana/issues/68626 -- POC issue: https://github.com/elastic/kibana/pull/93380 +- POC PR: https://github.com/elastic/kibana/pull/93380 # Summary @@ -24,7 +24,7 @@ In 'classic' mode, the Kibana server is started in the main NodeJS process. ![image](../images/15_clustering/no-cluster-mode.png) In clustering mode, the main NodeJS process would only start the coordinator, which would then fork workers using -the cluster API. NodeJS underlying socket implementation allows multiple processes to listen to the same ports, +Node's `cluster` API. NodeJS underlying socket implementation allows multiple processes to listen to the same ports, performing http traffic balancing between the workers for us. ![image](../images/15_clustering/cluster-mode.png) @@ -150,10 +150,10 @@ export interface ClusteringServiceSetup { ## Cross-worker communication -For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. Such communication +For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. This will need to pass through the coordinator, which will also serve as an 'event bus', or IPC forwarder. -The base API for such communication will be exposed from the clustering service. +This IPC API will be exposed from the clustering service. ```ts export interface ClusteringServiceSetup { @@ -170,13 +170,15 @@ Notes: ## Executing code on a single worker -In some scenario, we would like to have some part of the code executed from a single process. The SO migration would be a good example: +In some scenarios, we would like to have parts of the code executed only from a single process. + +The SO migration would be a good example: we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying the migration, -and the other wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, -as it doesn't actually run a Kibana's Server. +and the others wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, +as it doesn't actually run a Kibana server. -There are various ways to address such use-case. What seems to be the best compromise right now would be the concept of -'main worker'. The coordinator would arbitrary elect a worker as the 'main' one. The clustering service would then expose +There are various ways to address such use-cases. What seems to be the best compromise right now would be the concept of +'main worker'. The coordinator would arbitrary elect a worker as the 'main' one at startup. The clustering service would then expose an API to let workers identify themselves as main or not. ```ts @@ -235,7 +237,7 @@ be required to support clustering mode. ### Handling multi-process logs -This is an example of log output in a 2 workers cluster, coming from the POC +This is an example of log output in a 2 workers cluster, coming from the POC: ``` [2021-03-02T10:23:41.834+01:00][INFO ][plugins-service] Plugin initialization disabled. @@ -244,19 +246,20 @@ This is an example of log output in a 2 workers cluster, coming from the POC [2021-03-02T10:23:41.903+01:00][WARN ][savedobjects-service] Skipping Saved Object migrations on startup. Note: Individual documents will still be migrated when read or written. ``` -The workers logs are interleaved, and, most importantly, there is no way to see which process the log is coming from. +The workers logs are interleaved, and, most importantly, there is no way to see which process each log entry is coming from. We will need to address that. -Our options are +Our options are: - Have a distinct logging configuration for each worker -We could do that by automatically adding a suffix depending on the process to the appropriate appenders configuration. +We could do that by automatically adding a suffix depending on the process to the appropriate file appenders configuration. Note that this doesn’t solve the problem for the console appender, which is probably a no-go. - Add the process info to the log pattern and output it with the log message -We could add the process name information to the log messages, and add a new conversion to be able to display it with the pattern layout, such as %process for example. +We could add the process name information to the log messages, and add a new conversion to be able to display it with +the pattern layout, such as `%process` for example. the default pattern could evolve to (ideally, only when clustering is enabled) @@ -271,30 +274,41 @@ The logging output would then look like [2021-03-02T10:23:41.840+01:00][INFO ][worker-2][plugins-service] Plugin initialization disabled. ``` -This will require some changes in the logging system implementation, as currently the BaseLogger has no logic to +This will require some non-trivial changes in the logging system implementation, as currently the BaseLogger has no logic to enhance the log record with context information before forwarding it to its appenders, but this still -seems to be the best solution. +seems to be the best solution. (This may even be the first step to implement our MDC) + +Notes: +- Even if we add the `%process` pattern, do we want to also allow users to specify per-worker log files? ### The rolling-file appender The rolling process of the `rolling-file` appender is going to be problematic in clustered mode, as it will cause -concurrency issues during the rolling. We need to find a way to have this rolling process clustered-proof. +concurrency issues during the rolling. We need to find a way to have this rolling stage clustered-proof. Identified options are: - have the rolling file appenders coordinate themselves when rolling -By using a broadcast message based mutex mechanism, the appenders could acquire a ‘lock’ to roll a specific file, and release the lock once the rotation is done. +By using a broadcast message based mutex mechanism, the appenders could acquire a ‘lock’ to roll a specific file, and +notify other workers when the rolling is complete (quite similar to what we want to do with SO migration for example). - have the coordinator process perform the rolling -Another option would be to have the coordinator perform the rotation instead. When a rolling is required, the appender would send a message to the coordinator, which would perform the rolling and notify the workers once the process is complete. Note that this option is even more complicated than the previous one, as it forces to move the rolling implementation outside of the appender, without any significant upsides. +Another option would be to have the coordinator perform the rotation instead. When a rolling is required, the appender +would send a message to the coordinator, which would perform the rolling and notify the workers once the operation is complete. + +Note that this option is even more complicated than the previous one, as it forces to move the rolling implementation +outside of the appender, without any significant upsides identified. - centralize the logging system in the coordinator (and have the workers send messages to the coordinator when using the logging system) -We could go further, and change the way the logging system works in clustering mode by having the coordinator centralize the logging system. The worker’s logger implementation would just send messages to the coordinator. If this may be a correct design, the main downside is that the logging implementation would be totally different in cluster and non cluster mode, and is overall way more work that the other options. +We could go further, and change the way the logging system works in clustering mode by having the coordinator centralize +the logging system. The worker’s logger implementation would just send messages to the coordinator. If this may be a +correct design, the main downside is that the logging implementation would be totally different in cluster and +non cluster mode, and seems to be way more work that the other options. -Overall, if no option is trivial, I feel like option 1) is still the most pragmatic one. Option 3) is probably a better +Overall, if no option is trivial, I feel like option 1) is still the most pragmatic one. Option 3) may be a better design, but represents more work. It would probably be fine if all our appenders were impacted, but as only the rolling-file one is, I feel like going with 1) would be ok. @@ -323,7 +337,7 @@ in the worker's environment service. In the current state, all workers are going to try to perform the migration. Ideally, we would have only one process perform the migration, and the other ones just wait for a ready signal. We can’t easily have the coordinator do it, -so we would probably have to leverage the ‘main worker’ concept to do so. +so we would probably have to leverage the ‘main worker’ concept here. The SO migration v2 is supposed to be resilient to concurrent attempts though, as we already support multi-instances Kibana, so this can probably be considered an improvement. @@ -331,14 +345,16 @@ Kibana, so this can probably be considered an improvement. ## Open questions and things to solve ### Memory consumption -In cluster mode, node options such as `max-old-space-size` will be used by all processes. E.g using -`--max-old-space-size=1024` in a 2 workers cluster would have a maximum memory usage of 3gb (1 coordinator + 2 workers). + +In clustered mode, node options such as `max-old-space-size` will be used by all processes. + +E.g using `--max-old-space-size=1024` in a 2 workers cluster would have a maximum memory usage of 3gb (1 coordinator + 2 workers). If this something we will need to document somewhere? ### Workers error handling -When using `cluster`, the common best practice is to have the coordinator recreate workers when they terminate unexpectedly. +When using `cluster`, the common best practice is to have the coordinator recreate ('restart') workers when they terminate unexpectedly. However, given Kibana's architecture, some failures are not recoverable (workers failing because of config validation, failed migration...). For instance, if a worker (well, all workers) terminates because of an invalid configuration property, it doesn't make @@ -356,7 +372,7 @@ are accessing files in write mode, which could result in concurrency issues betw If that was confirmed, we would have to create and use a distinct data folder for each worker. -One pragmatic solution would be, when clustering is enabled, to create a sub folder under path.data for each worker. +One pragmatic solution could be, when clustering is enabled, to create a sub folder under path.data for each worker. If we need to do so, should this be considered a breaking change, or do we assume the usage of the data folder is an implementation detail and not part of our public 'API'? @@ -369,7 +385,7 @@ We still need to identify with the teams if this is going to be a problem, in wh instance uuid per workers. Note that this could be a breaking change, as the single `server.uuid` configuration property would not be enough. -We may want to introduce a new `workerId` variable and create the associated API to expose this value to plugins? +Could the new `clustering.getWorkerId()` API be used here somehow? We could have a unique worker id with `serverUUid-workerId`. ### The Dev CLI @@ -473,23 +489,24 @@ We may need to have each worker uses a distinct data folder. Should this be cons # Drawbacks - Implementation cost is going to be significant, both in core and in plugins. Also, this will have to be a collaborative - effort, as we can't enable the clustered mode in production until all the identified breaking changes has been addressed. + effort, as we can't enable the clustered mode in production until all the identified breaking changes have been addressed. - Even if easier to deploy, it doesn't really provide anything more than a multi-instances Kibana setup. - This will complexify the code, especially in Core were some part of the logic will drastically change between clustered and -non-clustered modes (e.g the status API). +non-clustered modes (e.g the status API, rolling-file appender). -- It could introduce subtle bugs in clustered mode, as we may overlook some breaking changes, or new features may omit to -ensure clustered mode compatibility. +- It could introduce subtle bugs in clustered mode, as we may overlook some breaking changes, or developers may omit to +ensure clustered mode compatibility when adding new features. -- Proper testing of all the edge case is going to be tedious, if not just realistically impossible. +- Proper testing of all the edge cases is going to be tedious, if not just realistically impossible. We can't really + automate the testing of the clustered mode. # Alternatives Regarding the whole proposal, an alternative would be to provide tooling to ease the deployment of multi-instance Kibana setups. -Regarding the implementation proposal, the discussion is still ongoing. +Regarding the implementation proposal, the discussions are still ongoing. # Adoption strategy @@ -497,8 +514,8 @@ Phase 1: we perform the required changes in `Core`, and add the `clustering.enab That way, we allow developers to test their features against clustering mode and to adapt their code to use the new `clustering` API and service. -Phase 2: when all the required changes have been performed, we enable the `clustering` configuration on production mode as a `beta` feature. -We would ideally also add telemetry collection for the clustering usages (actual metrics TBD) to have a precise vision of the adoption of the feature. +Phase 2: when all the required changes have been performed in plugins code, we enable the `clustering` configuration on production mode as a `beta` feature. +We would ideally also add telemetry collection for the clustering usages (relevant metrics TBD) to have a precise vision of the adoption of the feature. # How we teach this From 37328e99c32c5ae0138fd37bfe537ee8ae1a2057 Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Mon, 22 Mar 2021 11:39:43 +0100 Subject: [PATCH 06/18] address some review comments --- rfcs/text/0015_nodejs_clustering.md | 140 +++++++++++++++------------- 1 file changed, 76 insertions(+), 64 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 958acb898f962..82b865acc1fbd 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -12,7 +12,8 @@ Leveraging NodeJS clustering API to have multi-processes Kibana instances. Kibana currently uses a single Node process/thread to serve HTTP traffic. This means Kibana cannot take advantage of multi-core hardware making it expensive to scale out Kibana. -Clustering mode would allow spawning multiple Kibana processes ('workers') from a single Kibana instance. +Clustering mode would allow spawning multiple Kibana processes ('workers') from a single Kibana instance. See the `alternatives` +section for the difference between clustering and worker pool. This should be an optional way to run Kibana since users running Kibana inside docker containers might choose to rather use their container orchestration to run a container (with a single kibana process)per host CPU. @@ -89,16 +90,65 @@ export const config = { path: 'clustering', schema: schema.object({ enabled: schema.boolean({ defaultValue: false }), - workers: schema.number({ defaultValue: 2 }), + workers: schema.conditional( + schema.siblingRef('enabled'), + false, + schema.number({ defaultValue: 1 }), + schema.number() + ) }), }; ``` Notes: -- What should be the default value for `clustering.workers`? We could go with `Max(1, os.cpus().length - 1)`, but do we really want to use all cpus by default, - knowing that every worker is going to have its own memory usage. +- As there isn't really a good way to automatically choose the correct number of workers automatically, It will be required + for the user to manually specify `clustering.workers` when clustering is enabled. + +## Cross-worker communication + +For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. This +will need to pass through the coordinator, which will also serve as an 'event bus', or IPC forwarder. + +This IPC API will be exposed from the clustering service. -## The clustering service +```ts +export interface ClusteringServiceSetup { + // [...] + broadcast: (type: string, payload?: ClusterMessagePayload, options?: BroadcastOptions) => void; + addMessageHandler: (type: string, handler: MessageHandler) => MessageHandlerUnsubscribeFn; +} +``` + +Notes: +- to reduce clustered and non-clustered mode divergence, in non-clustered mode, these APIs would just be no-ops. + It will avoid to force (most) code to check in which mode Kibana is running before calling them. +- We could eventually use an Observable pattern instead of a handler pattern to subscribe to messages. + +## Executing code on a single worker + +In some scenarios, we would like to have parts of the code executed only from a single process. + +The SO migration would be a good example: +we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying the migration, +and the others wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, +as it doesn't actually run a Kibana server. + +There are various ways to address such use-cases. What seems to be the best compromise right now would be the concept of +'main worker'. The coordinator would arbitrary elect a worker as the 'main' one at startup. The clustering service would then expose +an API to let workers identify themselves as main or not. + +```ts +export interface ClusteringServiceSetup { + // [...] + isMainWorker: () => boolean; +} +``` + +Notes: +- in non-clustered mode, `isMainWorker` would always return true, to reduce the divergence between clustered and + non-clustered modes. + +## The clustering service API We will be adding a new clustering service to core, that will add the necessary cluster APIs, and would be accessible via core's setup and start contracts (`coreSetup.clustering` and `coreStart.clustering`). @@ -142,56 +192,12 @@ export interface ClusteringServiceSetup { */ addMessageHandler: (type: string, handler: MessageHandler) => MessageHandlerUnsubscribeFn; /** - * Returns true if the current worker has been elected as the main one. In non-clustered mode, will return true + * Returns true if the current worker has been elected as the main one. In non-clustered mode, will always return true */ isMainWorker: () => boolean; } ``` -## Cross-worker communication - -For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. This -will need to pass through the coordinator, which will also serve as an 'event bus', or IPC forwarder. - -This IPC API will be exposed from the clustering service. - -```ts -export interface ClusteringServiceSetup { - // [...] - broadcast: (type: string, payload?: ClusterMessagePayload, options?: BroadcastOptions) => void; - addMessageHandler: (type: string, handler: MessageHandler) => MessageHandlerUnsubscribeFn; -} -``` - -Notes: -- to reduce clustered and non-clustered mode divergence, in non-clustered mode, these APIs would just be no-ops. - It will avoid to force (most) code to check in which mode Kibana is running before calling them. -- We could eventually use an Observable pattern instead of a handler pattern to subscribe to messages. - -## Executing code on a single worker - -In some scenarios, we would like to have parts of the code executed only from a single process. - -The SO migration would be a good example: -we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying the migration, -and the others wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, -as it doesn't actually run a Kibana server. - -There are various ways to address such use-cases. What seems to be the best compromise right now would be the concept of -'main worker'. The coordinator would arbitrary elect a worker as the 'main' one at startup. The clustering service would then expose -an API to let workers identify themselves as main or not. - -```ts -export interface ClusteringServiceSetup { - // [...] - isMainWorker: () => boolean; -} -``` - -Notes: -- in non-clustered mode, `isMainWorker` would always return true, to reduce the divergence between clustered and - non-clustered modes. - ### Example: SO Migration To take the example of SO migration, the `KibanaMigrator.runMigrations` implementation could change to @@ -259,12 +265,12 @@ Note that this doesn’t solve the problem for the console appender, which is pr - Add the process info to the log pattern and output it with the log message We could add the process name information to the log messages, and add a new conversion to be able to display it with -the pattern layout, such as `%process` for example. +the pattern layout, such as `%worker` for example. the default pattern could evolve to (ideally, only when clustering is enabled) ``` -[%date][%level][%process][%logger] %message +[%date][%level][%worker][%logger] %message ``` The logging output would then look like @@ -279,7 +285,9 @@ enhance the log record with context information before forwarding it to its appe seems to be the best solution. (This may even be the first step to implement our MDC) Notes: -- Even if we add the `%process` pattern, do we want to also allow users to specify per-worker log files? +- The coordinator will probably need to output logs too. `%worker` would be interpolated to `coordinator` + for the coordinator process +- Even if we add the `%worker` pattern, do we want to also allow users to specify per-worker log files? ### The rolling-file appender @@ -374,8 +382,8 @@ If that was confirmed, we would have to create and use a distinct data folder fo One pragmatic solution could be, when clustering is enabled, to create a sub folder under path.data for each worker. -If we need to do so, should this be considered a breaking change, or do we assume the usage of the data folder is an -implementation detail and not part of our public 'API'? +The data folder is not considered part of our public API, and the implementation and path already changed in previous +minor releases, so this should not be considered a breaking change. ### instanceUUID @@ -385,7 +393,7 @@ We still need to identify with the teams if this is going to be a problem, in wh instance uuid per workers. Note that this could be a breaking change, as the single `server.uuid` configuration property would not be enough. -Could the new `clustering.getWorkerId()` API be used here somehow? We could have a unique worker id with `serverUUid-workerId`. +Could the new `clustering.getWorkerId()` API be used here somehow? We could have a unique worker id with `{serverUUid}-{workerId}`. ### The Dev CLI @@ -398,7 +406,8 @@ to finally extract the dev cli from Core and to avoid having it create a tempora and configuration. Note that extracting and refactoring the dev cli is going to be required anyway to remove the last bits of legacy, -as it currently relies on the legacy configuration to run (and is running from the legacy service). +as it currently relies on the legacy configuration to run (and is running from the legacy service). This task is currently +planned for 7.13 or early 7.14, see [the associated GH issue](https://github.com/elastic/kibana/issues/76935) ## Technical impact on our plugins codebase @@ -445,7 +454,8 @@ We do store a state in the SavedObjects store of the last time the usage was sen We have tasks across several plugins storing data in savedobjects specifically for telemetry. Under clustering these tasks will be registered multiple times. -Note that sending the data multiple times doesn’t have any real consequences, so this should be considered +Note that sending the data multiple times doesn’t have any real consequences, apart from the additional number of ES requests, +so this should be considered non-blocking and only an improvement. #### TaskManager @@ -482,10 +492,6 @@ If we decide to have each worker output log in distinct files, we would have to add a prefix/suffix to each log file, which would be a breaking change. Note that this option is probably not the one we'll choose. -## data folder - -We may need to have each worker uses a distinct data folder. Should this be considered a breaking change? - # Drawbacks - Implementation cost is going to be significant, both in core and in plugins. Also, this will have to be a collaborative @@ -504,9 +510,15 @@ ensure clustered mode compatibility when adding new features. # Alternatives -Regarding the whole proposal, an alternative would be to provide tooling to ease the deployment of multi-instance Kibana setups. +One alternative of the `cluster` module is using a worker pool via `worker_threads`. Both have distinct use cases +though. Clustering is meant to have multiple workers with the same codebase, often sharing a network socket to balance +network traffic. The worker pattern is a way to create specialized workers in charge of executing isolated, CPU intensive +tasks on demand (e.g encrypting or descrypting a file). If we were to identify that under heavy load, the actual bottleneck +is ES, maybe exposing a worker thread service and API from core (task_manager would be a perfect example of potential consumer) +would make more sense. -Regarding the implementation proposal, the discussions are still ongoing. +Another alternative would be to provide tooling to ease the deployment of multi-instance Kibana setups, and only support +multi-instance mode. # Adoption strategy From c73c12dc5327601ed1f1663c3d9480d17a5ba9fe Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Mon, 22 Mar 2021 14:31:50 +0100 Subject: [PATCH 07/18] more nits --- rfcs/text/0015_nodejs_clustering.md | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 82b865acc1fbd..56f4b3eab021f 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -119,6 +119,9 @@ export interface ClusteringServiceSetup { } ``` +To preserve isolation and to avoid creating an implicit cross-plugin API, handlers registered from a given plugin will only be +invoked for messages sent by the same plugin. + Notes: - to reduce clustered and non-clustered mode divergence, in non-clustered mode, these APIs would just be no-ops. It will avoid to force (most) code to check in which mode Kibana is running before calling them. @@ -255,14 +258,14 @@ This is an example of log output in a 2 workers cluster, coming from the POC: The workers logs are interleaved, and, most importantly, there is no way to see which process each log entry is coming from. We will need to address that. -Our options are: +Our (non-exclusive) options are: -- Have a distinct logging configuration for each worker +1. Have a distinct logging configuration for each worker We could do that by automatically adding a suffix depending on the process to the appropriate file appenders configuration. Note that this doesn’t solve the problem for the console appender, which is probably a no-go. -- Add the process info to the log pattern and output it with the log message +2. Add the process info to the log pattern and output it with the log message We could add the process name information to the log messages, and add a new conversion to be able to display it with the pattern layout, such as `%worker` for example. @@ -296,12 +299,12 @@ concurrency issues during the rolling. We need to find a way to have this rollin Identified options are: -- have the rolling file appenders coordinate themselves when rolling +1. have the rolling file appenders coordinate themselves when rolling By using a broadcast message based mutex mechanism, the appenders could acquire a ‘lock’ to roll a specific file, and notify other workers when the rolling is complete (quite similar to what we want to do with SO migration for example). -- have the coordinator process perform the rolling +2. have the coordinator process perform the rolling Another option would be to have the coordinator perform the rotation instead. When a rolling is required, the appender would send a message to the coordinator, which would perform the rolling and notify the workers once the operation is complete. @@ -309,16 +312,16 @@ would send a message to the coordinator, which would perform the rolling and not Note that this option is even more complicated than the previous one, as it forces to move the rolling implementation outside of the appender, without any significant upsides identified. -- centralize the logging system in the coordinator (and have the workers send messages to the coordinator when using the logging system) +3. centralize the logging system in the coordinator We could go further, and change the way the logging system works in clustering mode by having the coordinator centralize the logging system. The worker’s logger implementation would just send messages to the coordinator. If this may be a correct design, the main downside is that the logging implementation would be totally different in cluster and non cluster mode, and seems to be way more work that the other options. -Overall, if no option is trivial, I feel like option 1) is still the most pragmatic one. Option 3) may be a better +Overall, if no option is trivial, I feel like option `1.` is still the most pragmatic one. Option `3.` may be a better design, but represents more work. It would probably be fine if all our appenders were impacted, but as only the -rolling-file one is, I feel like going with 1) would be ok. +rolling-file one is, I feel like going with `3.` would be ok. ### The status API From 0b22f4885de0fc7ceba6f256076ceffb91e4e8ba Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Mon, 22 Mar 2021 14:56:14 +0100 Subject: [PATCH 08/18] add alternative for rolling file --- rfcs/text/0015_nodejs_clustering.md | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 56f4b3eab021f..df2ff181b8072 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -304,6 +304,12 @@ Identified options are: By using a broadcast message based mutex mechanism, the appenders could acquire a ‘lock’ to roll a specific file, and notify other workers when the rolling is complete (quite similar to what we want to do with SO migration for example). +An alternative to this option would be to only have the main worker handle the rolling logic. We will lose control +on the exact size the file is when rolling, as we would need to wait until the main worker receives a log message +for the rolling appender before the rolling is effectively performed. The upside would be that it reduces the inter-workers +communication to a notification from the main worker to the others once the rolling is done for them to reopen their +file handler. + 2. have the coordinator process perform the rolling Another option would be to have the coordinator perform the rotation instead. When a rolling is required, the appender From 8b24baef043848118c4dafbf298e4a6f6b562f11 Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Mon, 22 Mar 2021 15:06:16 +0100 Subject: [PATCH 09/18] add part of telemetry --- rfcs/text/0015_nodejs_clustering.md | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index df2ff181b8072..04b0c5d8abd43 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -464,8 +464,15 @@ We have tasks across several plugins storing data in savedobjects specifically f tasks will be registered multiple times. Note that sending the data multiple times doesn’t have any real consequences, apart from the additional number of ES requests, -so this should be considered -non-blocking and only an improvement. +so this should be considered non-blocking and only an improvement. + +- Event-based telemetry + +Event-based telemetry may be affected as well. Both the existing one in the Security Solutions team and the general +one that is in the works. More specifically, the size of the queues will be multiplied per worker, also growing in the +amount of network bandwidth used, and potentially affecting our customers. + +We could address that by making sure that the queues are held only in the main worker. #### TaskManager From f8d7540ec7287d735a0ca1f8bba907423ab7f136 Mon Sep 17 00:00:00 2001 From: pgayvallet Date: Mon, 22 Mar 2021 15:17:48 +0100 Subject: [PATCH 10/18] rephrasing --- rfcs/text/0015_nodejs_clustering.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 04b0c5d8abd43..339d9143d67c4 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -528,7 +528,7 @@ ensure clustered mode compatibility when adding new features. One alternative of the `cluster` module is using a worker pool via `worker_threads`. Both have distinct use cases though. Clustering is meant to have multiple workers with the same codebase, often sharing a network socket to balance -network traffic. The worker pattern is a way to create specialized workers in charge of executing isolated, CPU intensive +network traffic. Worker threads is a way to create specialized workers in charge of executing isolated, CPU intensive tasks on demand (e.g encrypting or descrypting a file). If we were to identify that under heavy load, the actual bottleneck is ES, maybe exposing a worker thread service and API from core (task_manager would be a perfect example of potential consumer) would make more sense. From 6028899b2ff3f63f17622d83f1517d081142750a Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Tue, 25 May 2021 11:33:53 -0600 Subject: [PATCH 11/18] Add ToC. --- rfcs/text/0015_nodejs_clustering.md | 104 +++++++++++++++++----------- 1 file changed, 63 insertions(+), 41 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 339d9143d67c4..3b343c6faa475 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -3,11 +3,29 @@ - Kibana Issue: https://github.com/elastic/kibana/issues/68626 - POC PR: https://github.com/elastic/kibana/pull/93380 -# Summary +--- + +- [1. Summary](#1-summary) +- [2. Motivation](#2-motivation) +- [3. Architecture](#3-architecture) +- [4. Testing](#4-testing) +- [5. Detailed design](#5-detailed-design) +- [6. Technical impact](#6-technical-impact) + - [6.1 Technical impact on Core](#6.1-technical-impact-on-core) + - [6.2 Technical impact on Plugins](#6.2-technical-impact-on-plugins) + - [6.3 Summary of breaking changes](#6.3-summary-of-breaking-changes) +- [7. Drawbacks](#7-drawbacks) +- [8. Alternatives](#8-alternatives) +- [9. Adoption strategy](#9-adoption-strategy) +- [10. How we teach this](#10-how-we-teach-this) +- [11. Unresolved questions](#11-unresolved-questions) +- [12. Resolved questions](#12-resolved-questions) + +# 1. Summary Leveraging NodeJS clustering API to have multi-processes Kibana instances. -# Motivation +# 2. Motivation Kibana currently uses a single Node process/thread to serve HTTP traffic. This means Kibana cannot take advantage of multi-core hardware making it expensive to scale out Kibana. @@ -18,7 +36,7 @@ section for the difference between clustering and worker pool. This should be an optional way to run Kibana since users running Kibana inside docker containers might choose to rather use their container orchestration to run a container (with a single kibana process)per host CPU. -# Architecture summary +# 3. Architecture In 'classic' mode, the Kibana server is started in the main NodeJS process. @@ -33,14 +51,14 @@ performing http traffic balancing between the workers for us. The coordinator sole responsibility is to orchestrate the workers. It would not be a 'super' worker handling both the job of a worker while being in charge of managing the other workers. -# Performance testing +# 4. Testing -## Local testing +## 4.1 Local testing These tests were performed against a local development machine, with a 8-core cpu (2.4 GHz 8-Core Intel Core i9 - 32 GB 2400 MHz DDR4), using the default configuration of the `kibana-load-testing` tool. -### Raw results +### 4.1.1 Raw results #### Non-clustered mode @@ -54,7 +72,7 @@ using the default configuration of the `kibana-load-testing` tool. ![image](../images/15_clustering/perf-4-workers.png) -### Analysis +### 4.1.2 Analysis - Between non-clustered and 2-worker cluster mode, we observe a 20/25% gain in the 50th percentile response time. Gain for the 75th and 95th are between 10% and 40% @@ -67,7 +85,7 @@ Even if increasing the number of workers doesn’t just linearly increase the pe (which totally make sense, most of our requests response time is caused by awaiting ES response), the improvements of the clustering mode on performance under heavy load are far from negligible. -## Testing against cloud +## 4.2 Testing against cloud There is currently no easy way to test the performance improvements this could provide on Cloud, as we can't deploy custom builds or branches on Cloud at the moment. @@ -77,9 +95,9 @@ On Cloud, Kibana is running in a containerised environment using CPU CFS quota a If we want to investigate the potential perf improvement on Cloud further, our only option would be to setup a similar-ish environment locally (which wasn't done during the initial investigation) -# Implementation proposal +# 5. Detailed design -## enabling clustering mode +## 5.1 Enabling clustering mode Enabling clustering mode will be done using the `clustering.enabled` configuration property. @@ -104,7 +122,7 @@ Notes: - As there isn't really a good way to automatically choose the correct number of workers automatically, It will be required for the user to manually specify `clustering.workers` when clustering is enabled. -## Cross-worker communication +## 5.2 Cross-worker communication For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. This will need to pass through the coordinator, which will also serve as an 'event bus', or IPC forwarder. @@ -127,7 +145,7 @@ Notes: It will avoid to force (most) code to check in which mode Kibana is running before calling them. - We could eventually use an Observable pattern instead of a handler pattern to subscribe to messages. -## Executing code on a single worker +## 5.3 Executing code on a single worker In some scenarios, we would like to have parts of the code executed only from a single process. @@ -151,7 +169,7 @@ Notes: - in non-clustered mode, `isMainWorker` would always return true, to reduce the divergence between clustered and non-clustered modes. -## The clustering service API +## 5.4 The clustering service API We will be adding a new clustering service to core, that will add the necessary cluster APIs, and would be accessible via core's setup and start contracts (`coreSetup.clustering` and `coreStart.clustering`). @@ -201,7 +219,7 @@ export interface ClusteringServiceSetup { } ``` -### Example: SO Migration +### 5.4.1 Example: SO Migration To take the example of SO migration, the `KibanaMigrator.runMigrations` implementation could change to (naive implementation, the function is supposed to return a promise here, did not include that for simplicity): @@ -230,21 +248,21 @@ Notes: This is probably something else we should discuss. -## Sharing state between workers +## 5.5 Sharing state between workers This is not identified as necessary at the moment, and IPC broadcast should be sufficient, hopefully. If we do need shared state, we will probably have to use syscall libraries to share buffers such as [mmap-io](https://www.npmjs.com/package/mmap-io), and expose a higher level API for that from the `clustering` service. -# Technical impact on the codebase +# 6. Technical impact This section is meant to be an exhaustive (even if realistically not at the moment) inventory of the changes that would be required to support clustering mode. -## Technical impact on Core +## 6.1 Technical impact on Core -### Handling multi-process logs +### 6.1.1 Handling multi-process logs This is an example of log output in a 2 workers cluster, coming from the POC: @@ -292,7 +310,7 @@ Notes: for the coordinator process - Even if we add the `%worker` pattern, do we want to also allow users to specify per-worker log files? -### The rolling-file appender +### 6.1.2 The rolling-file appender The rolling process of the `rolling-file` appender is going to be problematic in clustered mode, as it will cause concurrency issues during the rolling. We need to find a way to have this rolling stage clustered-proof. @@ -329,7 +347,7 @@ Overall, if no option is trivial, I feel like option `1.` is still the most prag design, but represents more work. It would probably be fine if all our appenders were impacted, but as only the rolling-file one is, I feel like going with `3.` would be ok. -### The status API +### 6.1.3 The status API In clustering mode, the workers will all have an individual status. One could have a connectivity issue with ES while the other ones are green. Hitting the `/status` endpoint will reach a random (and different each time) worker, @@ -342,7 +360,7 @@ the status endpoint. We may also want to have the `/status` endpoint display each individual worker status in addition to the global status, which may be breaking change in the `/status` API response format. -### PID file +### 6.1.4 PID file Without changes, each worker is going to try to write and read the same PID file. Also, this breaks the whole pid file usage, as the PID stored in the file will be a arbitrary worker’s PID, instead of the coordinator (main process) PID. @@ -350,7 +368,7 @@ usage, as the PID stored in the file will be a arbitrary worker’s PID, instead In clustering mode, we will need to have to coordinator handle the PID file logic, and to disable pid file handling in the worker's environment service. -### SavedObjects migration +### 6.1.5 SavedObjects migration In the current state, all workers are going to try to perform the migration. Ideally, we would have only one process perform the migration, and the other ones just wait for a ready signal. We can’t easily have the coordinator do it, @@ -359,9 +377,9 @@ so we would probably have to leverage the ‘main worker’ concept here. The SO migration v2 is supposed to be resilient to concurrent attempts though, as we already support multi-instances Kibana, so this can probably be considered an improvement. -## Open questions and things to solve +### 6.1.6 Open questions and things to solve -### Memory consumption +#### Memory consumption In clustered mode, node options such as `max-old-space-size` will be used by all processes. @@ -369,7 +387,7 @@ E.g using `--max-old-space-size=1024` in a 2 workers cluster would have a maximu If this something we will need to document somewhere? -### Workers error handling +#### Workers error handling When using `cluster`, the common best practice is to have the coordinator recreate ('restart') workers when they terminate unexpectedly. However, given Kibana's architecture, some failures are not recoverable (workers failing because of config validation, failed migration...). @@ -380,7 +398,7 @@ any sense to have the coordinator recreate them indefinitely, as the error requi Should we try to distinguish recoverable and non-recoverable errors, or are we good terminating the main Kibana process when any worker terminates unexpectedly for any reason (After all, this is already the behavior in non-cluster mode)? -### Data folder +#### Data folder The data folder (`path.data`) is currently the same for all workers. @@ -394,7 +412,7 @@ One pragmatic solution could be, when clustering is enabled, to create a sub fol The data folder is not considered part of our public API, and the implementation and path already changed in previous minor releases, so this should not be considered a breaking change. -### instanceUUID +#### instanceUUID The same instance UUID (`server.uuid` / `{dataFolder}/uuid`) is currently used by all the workers. @@ -404,7 +422,7 @@ instance uuid per workers. Note that this could be a breaking change, as the single `server.uuid` configuration property would not be enough. Could the new `clustering.getWorkerId()` API be used here somehow? We could have a unique worker id with `{serverUUid}-{workerId}`. -### The Dev CLI +#### The Dev CLI In development mode, we are already spawning processes from the main process: The Kibana server running in the main process actually just kickstarts core to get the configuration and services required to instantiate the `CliDevMode` @@ -418,9 +436,9 @@ Note that extracting and refactoring the dev cli is going to be required anyway as it currently relies on the legacy configuration to run (and is running from the legacy service). This task is currently planned for 7.13 or early 7.14, see [the associated GH issue](https://github.com/elastic/kibana/issues/76935) -## Technical impact on our plugins codebase +## 6.2 Technical impact on Plugins -### Identifying things that may break +### 6.2.1 Identifying things that may break - Concurrent access to the same resources @@ -440,7 +458,7 @@ or starting schedulers? An example would be reporting's queueFactory pooling. As we want to only be running a single headless at a time per Kibana instance, only one worker should have pooling enabled. -### Identified required changes +### 6.2.2 Identified required changes (Probably not exhaustive at the moment) @@ -487,9 +505,9 @@ Short term, having only the 'main' worker perform the task claims and executions Do we need the alerting task runner (`TaskRunner`, `TaskRunnerFactory`) to be running on a single worker? -# Summary of the potential user-facing breaking changes +## 6.3 Summary of breaking changes -## status API +### 6.3.1 status API If we want to have the status API returns each individual worker's status, we will need to change the output of the status API in clustering mode. @@ -497,18 +515,18 @@ status API in clustering mode. Note that the new format for /api/status is still behind a v8format flag, meaning that if we do these changes before 8.0, we won't be introducing any breaking change later. -## instanceUUID +### 6.3.2 instanceUUID Depending on our decision regarding the instanceUUID problematic, we may have to change the server.uuid configuration property when clustering mode is enabled, which would be a breaking change. -## distinct logging configuration +### 6.3.3 distinct logging configuration If we decide to have each worker output log in distinct files, we would have to change the logging configuration to add a prefix/suffix to each log file, which would be a breaking change. Note that this option is probably not the one we'll choose. -# Drawbacks +# 7. Drawbacks - Implementation cost is going to be significant, both in core and in plugins. Also, this will have to be a collaborative effort, as we can't enable the clustered mode in production until all the identified breaking changes have been addressed. @@ -524,7 +542,7 @@ ensure clustered mode compatibility when adding new features. - Proper testing of all the edge cases is going to be tedious, if not just realistically impossible. We can't really automate the testing of the clustered mode. -# Alternatives +# 8. Alternatives One alternative of the `cluster` module is using a worker pool via `worker_threads`. Both have distinct use cases though. Clustering is meant to have multiple workers with the same codebase, often sharing a network socket to balance @@ -536,7 +554,7 @@ would make more sense. Another alternative would be to provide tooling to ease the deployment of multi-instance Kibana setups, and only support multi-instance mode. -# Adoption strategy +# 9. Adoption strategy Phase 1: we perform the required changes in `Core`, and add the `clustering.enabled` configuration property for development mode only. That way, we allow developers to test their features against clustering mode and to adapt their code to use the new `clustering` API @@ -545,10 +563,14 @@ and service. Phase 2: when all the required changes have been performed in plugins code, we enable the `clustering` configuration on production mode as a `beta` feature. We would ideally also add telemetry collection for the clustering usages (relevant metrics TBD) to have a precise vision of the adoption of the feature. -# How we teach this +# 10. How we teach this During phase 1, we should create documentation on the clustering mode: best practices, how to identify code that may breaks in clustered mode, and so on. -# Unresolved questions +# 11. Unresolved questions -None (well, except every single section of the document). \ No newline at end of file +None (well, except every single section of the document). + +# 12. Resolved questions + +... From 8be60e9d6f29f9a03faeb066fd19be9ececd84bd Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Tue, 25 May 2021 15:22:22 -0600 Subject: [PATCH 12/18] Initial pass at RFC updates. --- rfcs/text/0015_nodejs_clustering.md | 388 ++++++++++++++++------------ 1 file changed, 218 insertions(+), 170 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 3b343c6faa475..bd784c3e5a126 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -23,40 +23,75 @@ # 1. Summary -Leveraging NodeJS clustering API to have multi-processes Kibana instances. +This RFC proposes a new core service which leverages the [Node.js cluster API](https://nodejs.org/api/cluster.html) +to support multi-process Kibana instances. # 2. Motivation -Kibana currently uses a single Node process/thread to serve HTTP traffic. -This means Kibana cannot take advantage of multi-core hardware making it expensive to scale out Kibana. - -Clustering mode would allow spawning multiple Kibana processes ('workers') from a single Kibana instance. See the `alternatives` -section for the difference between clustering and worker pool. - -This should be an optional way to run Kibana since users running Kibana inside docker containers might -choose to rather use their container orchestration to run a container (with a single kibana process)per host CPU. +The Kibana server currently uses a single Node process to serve HTTP traffic. +This is a byproduct of the single-threaded nature of Node's event loop. + +As a consequence, Kibana cannot take advantage of multi-core hardware: If you run Kibana on an +8-core machine, it will only utilize one of those cores. This makes it expensive to scale out +Kibana, as server hardware will typically have multiple cores, so you end up paying for power +you never use. Since Kibana is generally more CPU-intensive than memory-intensive, it would be +advantageous to use all available cores to maximize the performance we can get out of a single +machine. + +Another benefit of this approach would be improving Kibana's overall performance for most users +without requiring an operator to scale out the server, as it would allow the server to handle +more http requests at once, making it less likely that a single bad request could delay the +event loop and impact subsequent requests. + +The introduction of a clustering mode would allow spawning multiple Kibana processes ('workers') +from a single Kibana instance. (See [Alternatives](#8-alternatives) to learn more about the +difference between clustering and worker pools). You can think of these processes as individual +instances of the Kibana server which listen on the same port on the same machine, and serve +incoming traffic in a round-robin fashion. + +Our intent is to eventually make clustering the default behavior in Kibana, taking advantage of +all available CPUs out of the box. However, this should still be an optional way to run Kibana +since users might have use cases for single-process instances (for example, users running Kibana +inside Docker containers might choose to rather use their container orchestration to run a +container per host CPU with a single Kibana process per container). # 3. Architecture -In 'classic' mode, the Kibana server is started in the main NodeJS process. +In 'classic' mode, the Kibana server is started in the main Node.js process. ![image](../images/15_clustering/no-cluster-mode.png) -In clustering mode, the main NodeJS process would only start the coordinator, which would then fork workers using -Node's `cluster` API. NodeJS underlying socket implementation allows multiple processes to listen to the same ports, -performing http traffic balancing between the workers for us. +In clustering mode, the main Node.js process would only start the coordinator, which would then +fork workers using Node's `cluster` API. Node's underlying socket implementation allows multiple +processes to listen to the same ports, effectively performing http traffic balancing between the +workers for us. ![image](../images/15_clustering/cluster-mode.png) -The coordinator sole responsibility is to orchestrate the workers. It would not be a 'super' worker handling both -the job of a worker while being in charge of managing the other workers. +The coordinator's primary responsibility is to orchestrate the workers. It would not be a 'super' +worker handling both the job of a worker while being in charge of managing the other workers. + +In addition, the coordinator would be responsible for some specific activities that need to be +handled in a centralized manner: +- collecting logs from each of the workers & writing them to a single file or stdout +- gathering basic status information from each worker for use in the `/status` and `/stats` APIs + +Over time, it is possible that the role of the coordinator would expand to serve more purposes, +especially if we start implementing custom routing logic to run different services on specialized +processes. # 4. Testing +Thorough performance testing is critical in evaluating the success of this plan. The results +below reflect some initial testing that was performed against an experimental +[proof-of-concept](https://github.com/elastic/kibana/pull/93380). Should we move forward with this +RFC, one of the first tasks will be to update the POC and build out a more detailed test plan that +covers all of the scenarios we are concerned with. + ## 4.1 Local testing -These tests were performed against a local development machine, with a 8-core cpu (2.4 GHz 8-Core Intel Core i9 - 32 GB 2400 MHz DDR4), -using the default configuration of the `kibana-load-testing` tool. +These tests were performed against a local development machine, with an 8-core CPU(2.4 GHz 8-Core +Intel Core i9 - 32 GB 2400 MHz DDR4), using the default configuration of the `kibana-load-testing` tool. ### 4.1.1 Raw results @@ -93,7 +128,7 @@ deploy custom builds or branches on Cloud at the moment. On Cloud, Kibana is running in a containerised environment using CPU CFS quota and CPU shares. If we want to investigate the potential perf improvement on Cloud further, our only option would be to setup a -similar-ish environment locally (which wasn't done during the initial investigation) +similar-ish environment locally (which wasn't done during the initial investigation). # 5. Detailed design @@ -101,33 +136,30 @@ similar-ish environment locally (which wasn't done during the initial investigat Enabling clustering mode will be done using the `clustering.enabled` configuration property. -The whole `clustering` configuration would look like: - -```ts -export const config = { - path: 'clustering', - schema: schema.object({ - enabled: schema.boolean({ defaultValue: false }), - workers: schema.conditional( - schema.siblingRef('enabled'), - false, - schema.number({ defaultValue: 1 }), - schema.number() - ) - }), -}; +If clustering is enabled by default, then no configuration would be required by users, and +Kibana would automatically use all available cores. However, more detailed configuration +would be available for users with more advanced use cases: +```yaml +clustering: + enabled: true # enabled by default + workers: # when provided, total # of workers would be based on # of items in this list + - name: foo # not technically necessary, but useful for logging purposes + max_old_space_size: 1gb # optional, allows to configure memory limits per-worker + - name: bar + max_old_space_size: 1gb ``` -Notes: -- As there isn't really a good way to automatically choose the correct number of workers automatically, It will be required - for the user to manually specify `clustering.workers` when clustering is enabled. - +This per-worker design would give us the flexibility to eventually provide more fine-grained configuration, +like dedicated workers for http requests or background jobs. We could also eventually add `coordinator` +specific config. + ## 5.2 Cross-worker communication -For some of our changes (such as the /status API, see below), we will need some kind of cross-worker communication. This -will need to pass through the coordinator, which will also serve as an 'event bus', or IPC forwarder. +For some of our changes (such as the `/status` API, see below), we will need some kind of cross-worker +communication. This will need to pass through the coordinator, which will also serve as an 'event bus', +or IPC forwarder. -This IPC API will be exposed from the clustering service. +This IPC API will be exposed from the clustering service: ```ts export interface ClusteringServiceSetup { @@ -137,26 +169,26 @@ export interface ClusteringServiceSetup { } ``` -To preserve isolation and to avoid creating an implicit cross-plugin API, handlers registered from a given plugin will only be -invoked for messages sent by the same plugin. +To preserve isolation and to avoid creating an implicit cross-plugin API, handlers registered from a +given plugin will only be invoked for messages sent by the same plugin. Notes: -- to reduce clustered and non-clustered mode divergence, in non-clustered mode, these APIs would just be no-ops. - It will avoid to force (most) code to check in which mode Kibana is running before calling them. +- To reduce clustered and non-clustered mode divergence, in non-clustered mode, these APIs would just be no-ops. + It will avoid forcing (most) code to check which mode Kibana is running before calling them. - We could eventually use an Observable pattern instead of a handler pattern to subscribe to messages. ## 5.3 Executing code on a single worker In some scenarios, we would like to have parts of the code executed only from a single process. -The SO migration would be a good example: -we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying the migration, -and the others wait for it. Due to the architecture, we can't have the coordinator perform such single-process jobs, -as it doesn't actually run a Kibana server. +Saved object migrations would be a good example: +we don't need to have each worker try to perform the migration, and we'd prefer to have one performing/trying +the migration, and the others waiting for it. Due to the architecture, we can't have the coordinator perform +such single-process jobs, as it doesn't actually run a Kibana server. -There are various ways to address such use-cases. What seems to be the best compromise right now would be the concept of -'main worker'. The coordinator would arbitrary elect a worker as the 'main' one at startup. The clustering service would then expose -an API to let workers identify themselves as main or not. +There are various ways to address such use-cases. What seems to be the best compromise right now would be the +concept of 'main worker'. The coordinator would arbitrarily elect a worker as the 'main' one at startup. The +clustering service would then expose an API to let workers identify themselves as main or not. ```ts export interface ClusteringServiceSetup { @@ -166,16 +198,18 @@ export interface ClusteringServiceSetup { ``` Notes: -- in non-clustered mode, `isMainWorker` would always return true, to reduce the divergence between clustered and +- In non-clustered mode, `isMainWorker` would always return true, to reduce the divergence between clustered and non-clustered modes. ## 5.4 The clustering service API -We will be adding a new clustering service to core, that will add the necessary cluster APIs, and would be accessible via core's setup and start contracts (`coreSetup.clustering` and `coreStart.clustering`). +We propose adding a new clustering service to Core, which will be responsible for adding the necessary cluster APIs, +and handling interaction with Node's `cluster` API. This service would be accessible via Core's setup and start contracts +(`coreSetup.clustering` and `coreStart.clustering`). At the moment, no need to extend Core's request handler context with clustering related APIs has been identified. -The contract interface would look like (more APIs could be added depending on the discussions on this RFC) +The initial contract interface would look like this: ```ts type ClusterMessagePayload = Serializable; @@ -204,35 +238,36 @@ export interface ClusteringServiceSetup { getWorkerId: () => number; /** * Broadcast a message to other workers. - * In non-clustered mode, this is a no-op + * In non-clustered mode, this is a no-op. */ broadcast: (type: string, payload?: ClusterMessagePayload, options?: BroadcastOptions) => void; /** - * Registered a handler for given `type` of IPC messages + * Registers a handler for given `type` of IPC messages * In non-clustered mode, this is a no-op that returns a no-op unsubscription callback. */ addMessageHandler: (type: string, handler: MessageHandler) => MessageHandlerUnsubscribeFn; /** - * Returns true if the current worker has been elected as the main one. In non-clustered mode, will always return true + * Returns true if the current worker has been elected as the main one. + * In non-clustered mode, will always return true */ isMainWorker: () => boolean; } ``` -### 5.4.1 Example: SO Migration +### 5.4.1 Example: Saved Object Migrations To take the example of SO migration, the `KibanaMigrator.runMigrations` implementation could change to (naive implementation, the function is supposed to return a promise here, did not include that for simplicity): ```ts runMigration() { - if(clustering.isMainWorker()) { + if (clustering.isMainWorker()) { this.runMigrationsInternal().then((result) => { applyMigrationState(result); - clustering.broadcast('migration-complete', { payload: result }, { persist: true }); // persist: true will send message even if subscriber subscribe after the message was actually sent + // persist: true will send message even if subscriber subscribes after the message was actually sent + clustering.broadcast('migration-complete', { payload: result }, { persist: true }); }) - } - else { + } else { const unsubscribe = clustering.addMessageHandler('migration-complete', ({ payload: result }) => { applyMigrationState(result); unsubscribe(); @@ -242,23 +277,22 @@ runMigration() { ``` Notes: - - to be sure that we do not encounter a race condition with the event subscribing / sending (workers subscribing after - the main worker actually send the `migration-complete` event and then waiting indefinitely), we are using the `persist` option of the `broadcast` API. - I'm honestly not sure this is the best pattern, but I couldn't come with anything better (maybe shared state instead?). - This is probably something else we should discuss. - + - To be sure that we do not encounter a race condition with the event subscribing / sending (workers subscribing after + the main worker actually sent the `migration-complete` event and then waiting indefinitely), we are using the `persist` + option of the `broadcast` API. We felt this was a better approach than the alternative of having shared state among workers. ## 5.5 Sharing state between workers -This is not identified as necessary at the moment, and IPC broadcast should be sufficient, hopefully. +This is not identified as necessary at the moment, and IPC broadcast should be sufficient, hopefully. We prefer to avoid +the added complexity and risk of implicit dependencies if possible. -If we do need shared state, we will probably have to use syscall libraries to share buffers such as [mmap-io](https://www.npmjs.com/package/mmap-io), -and expose a higher level API for that from the `clustering` service. +If we do eventually need shared state, we would probably have to use syscall libraries to share buffers such as +[mmap-io](https://www.npmjs.com/package/mmap-io), and expose a higher level API for that from the `clustering` service. More +research would be required if this proved to be a necessity. # 6. Technical impact -This section is meant to be an exhaustive (even if realistically not at the moment) inventory of the changes that would -be required to support clustering mode. +This section attempts to be an exhaustive inventory of the changes that would be required to support clustering mode. ## 6.1 Technical impact on Core @@ -276,46 +310,48 @@ This is an example of log output in a 2 workers cluster, coming from the POC: The workers logs are interleaved, and, most importantly, there is no way to see which process each log entry is coming from. We will need to address that. -Our (non-exclusive) options are: +#### Options we considered: -1. Have a distinct logging configuration for each worker +1. Having a distinct logging configuration (with separate log files) for each worker +2. Centralizing log collection in the coordinator and writing all logs to a single file (or stdout) -We could do that by automatically adding a suffix depending on the process to the appropriate file appenders configuration. -Note that this doesn’t solve the problem for the console appender, which is probably a no-go. +#### Our recommended approach: -2. Add the process info to the log pattern and output it with the log message +Overall we recommend keeping a single log file (option 2), and centralizing the logging system in the coordinator, +with each worker sending the coordinator log messages via IPC. While this is a more complex implementation in terms +of our logging system, it solves several problems: +- Preserves backwards compatibility. +- Avoids the issue of interleaved log messages that could occur with multiple processes writing to the same file or stdout. +- Provides a solution for the rolling-file appender (see below), as the coordinator would handle rolling all log file +(small caveat being a slight loss in file size precision). +- The changes to BaseLogger could potentially have the added benefit of paving the way for our future logging MDC. We could add the process name information to the log messages, and add a new conversion to be able to display it with the pattern layout, such as `%worker` for example. -the default pattern could evolve to (ideally, only when clustering is enabled) - +The default pattern could evolve to (ideally, only when clustering is enabled): ``` [%date][%level][%worker][%logger] %message ``` -The logging output would then look like - +The logging output would then look like: ``` [2021-03-02T10:23:41.834+01:00][INFO ][worker-1][plugins-service] Plugin initialization disabled. [2021-03-02T10:23:41.840+01:00][INFO ][worker-2][plugins-service] Plugin initialization disabled. ``` -This will require some non-trivial changes in the logging system implementation, as currently the BaseLogger has no logic to -enhance the log record with context information before forwarding it to its appenders, but this still -seems to be the best solution. (This may even be the first step to implement our MDC) - Notes: - The coordinator will probably need to output logs too. `%worker` would be interpolated to `coordinator` - for the coordinator process -- Even if we add the `%worker` pattern, do we want to also allow users to specify per-worker log files? + for the coordinator process. +- Even if we add the `%worker` pattern, we could still consider letting users configure per-worker log +files as a future enhancement. ### 6.1.2 The rolling-file appender The rolling process of the `rolling-file` appender is going to be problematic in clustered mode, as it will cause concurrency issues during the rolling. We need to find a way to have this rolling stage clustered-proof. -Identified options are: +#### Options we considered: 1. have the rolling file appenders coordinate themselves when rolling @@ -343,9 +379,9 @@ the logging system. The worker’s logger implementation would just send message correct design, the main downside is that the logging implementation would be totally different in cluster and non cluster mode, and seems to be way more work that the other options. -Overall, if no option is trivial, I feel like option `1.` is still the most pragmatic one. Option `3.` may be a better -design, but represents more work. It would probably be fine if all our appenders were impacted, but as only the -rolling-file one is, I feel like going with `3.` would be ok. +#### Our recommended approach: +Even though it's more complex, we feel that centralizing the logging system in the coordinator is the right move here, +as it will also solve for how to enable the coordinator to log its own messages. ### 6.1.3 The status API @@ -353,10 +389,11 @@ In clustering mode, the workers will all have an individual status. One could ha while the other ones are green. Hitting the `/status` endpoint will reach a random (and different each time) worker, meaning that it would not be possible to know the status of the cluster as a whole. -We will need to add a centralized status service in the coordinator. Also, as the `/status` endpoint cannot be served +We will need to add some centralized status state in the coordinator. Also, as the `/status` endpoint cannot be served from the coordinator, we will also need to have the workers retrieve the global status from the coordinator to serve the status endpoint. +TODO: We may also want to have the `/status` endpoint display each individual worker status in addition to the global status, which may be breaking change in the `/status` API response format. @@ -368,7 +405,7 @@ usage, as the PID stored in the file will be a arbitrary worker’s PID, instead In clustering mode, we will need to have to coordinator handle the PID file logic, and to disable pid file handling in the worker's environment service. -### 6.1.5 SavedObjects migration +### 6.1.5 Saved Objects migration In the current state, all workers are going to try to perform the migration. Ideally, we would have only one process perform the migration, and the other ones just wait for a ready signal. We can’t easily have the coordinator do it, @@ -377,17 +414,16 @@ so we would probably have to leverage the ‘main worker’ concept here. The SO migration v2 is supposed to be resilient to concurrent attempts though, as we already support multi-instances Kibana, so this can probably be considered an improvement. -### 6.1.6 Open questions and things to solve - -#### Memory consumption +### 6.1.6 Memory consumption In clustered mode, node options such as `max-old-space-size` will be used by all processes. -E.g using `--max-old-space-size=1024` in a 2 workers cluster would have a maximum memory usage of 3gb (1 coordinator + 2 workers). +e.g. using `--max-old-space-size=1024` in a 2 workers cluster would have a maximum memory usage of 3gb (1 coordinator + 2 workers). -If this something we will need to document somewhere? +TODO: +Our recommendation is to _disable clustering by default when a user has set `max-old-space-size` in the `node.options` file_. -#### Workers error handling +### 6.1.7 Workers error handling When using `cluster`, the common best practice is to have the coordinator recreate ('restart') workers when they terminate unexpectedly. However, given Kibana's architecture, some failures are not recoverable (workers failing because of config validation, failed migration...). @@ -395,73 +431,55 @@ However, given Kibana's architecture, some failures are not recoverable (workers For instance, if a worker (well, all workers) terminates because of an invalid configuration property, it doesn't make any sense to have the coordinator recreate them indefinitely, as the error requires manual intervention. -Should we try to distinguish recoverable and non-recoverable errors, or are we good terminating the main Kibana process -when any worker terminates unexpectedly for any reason (After all, this is already the behavior in non-cluster mode)? +As a first step, we plan to terminate the main Kibana process when any worker terminates unexpectedly for any reason (after all, +this is already the behavior in non-cluster mode). In the future, we will look toward distinguishing between recoverable +and non-recoverable errors as an enhancement, so that we can automatically restart workers on any recoverable error. -#### Data folder +### 6.1.8 Data folder The data folder (`path.data`) is currently the same for all workers. We still have to identify with the teams if this is going to be a problem. It could be, for example, if some plugins are accessing files in write mode, which could result in concurrency issues between the workers. -If that was confirmed, we would have to create and use a distinct data folder for each worker. - -One pragmatic solution could be, when clustering is enabled, to create a sub folder under path.data for each worker. +If that was confirmed, we would plan to create and use a distinct data folder for each worker, which would be non-breaking +as we don't consider the layout of this directory to be part of our public API. -The data folder is not considered part of our public API, and the implementation and path already changed in previous -minor releases, so this should not be considered a breaking change. - -#### instanceUUID +### 6.1.9 instanceUUID The same instance UUID (`server.uuid` / `{dataFolder}/uuid`) is currently used by all the workers. -We still need to identify with the teams if this is going to be a problem, in which case we would need to have distinct -instance uuid per workers. - -Note that this could be a breaking change, as the single `server.uuid` configuration property would not be enough. -Could the new `clustering.getWorkerId()` API be used here somehow? We could have a unique worker id with `{serverUUid}-{workerId}`. - -#### The Dev CLI - -In development mode, we are already spawning processes from the main process: The Kibana server running in the main process -actually just kickstarts core to get the configuration and services required to instantiate the `CliDevMode` -(from the legacy service), which itself spawns a child process to run the actual Kibana server. - -Even if not technically blocking, it would greatly simplify parts of the workers and coordinator logic if we were able -to finally extract the dev cli from Core and to avoid having it create a temporary server just to access the Legacy service -and configuration. +So far, we have not identified any places where this will be problematic, however, we will look to other teams to +help validate this. -Note that extracting and refactoring the dev cli is going to be required anyway to remove the last bits of legacy, -as it currently relies on the legacy configuration to run (and is running from the legacy service). This task is currently -planned for 7.13 or early 7.14, see [the associated GH issue](https://github.com/elastic/kibana/issues/76935) +Note that if we did need to have per-worker UUIDs, this could be a breaking change, as the single `server.uuid` +configuration property would not be enough. If this change becomes necessary, one approach could be to have unique worker +IDs with `${serverUuid}-${workerId}`. ## 6.2 Technical impact on Plugins -### 6.2.1 Identifying things that may break +### 6.2.1 What types of things could break? -- Concurrent access to the same resources +#### Concurrent access to the same resources Is there, for example, some part of the code that is accessing and writing files from the data folder (or anywhere else) and makes the assumption that it is the sole process actually writing to that file? -- Using instanceUUID as a unique Kibana process identifier +#### Using instanceUUID as a unique Kibana process identifier Is there, for example, schedulers that are using the instanceUUID a single process id, in opposition to a single Kibana instance id? Are there situations where having the same instance UUID for all the workers is going to be a problem? -- Things needing to run only once per Kibana instance +#### Things needing to run only once per Kibana instance Is there any part of the code that needs to be executed only once in a multi-worker mode, such as initialization code, or starting schedulers? -An example would be reporting's queueFactory pooling. As we want to only be running a single headless at a time per +An example would be Reporting's queueFactory pooling. As we want to only be running a single headless at a time per Kibana instance, only one worker should have pooling enabled. ### 6.2.2 Identified required changes -(Probably not exhaustive at the moment) - #### Reporting We will probably want to restrict to a single headless per Kibana instance. For that, we will have to change the logic @@ -492,14 +510,22 @@ amount of network bandwidth used, and potentially affecting our customers. We could address that by making sure that the queues are held only in the main worker. -#### TaskManager +#### Task Manager + +Currently, task manager does "claims" for jobs to run based on the server uuid. We think this could still work with +a multi-process setup - each task manager in the worker would be doing "claims" for the same server uuid, which +seems functionally the same as setting max_workers to `current max_workers * number of workers`. -Currently, task manager does "claims" for jobs to run based on the server uuid. I think this would still work with -workers - each task manager in the worker would be doing "claims" for the same server uuid, which I think is basically -the same as setting your max_workers to "current max_workers * number of workers" +However, as a first step we can simply run Task Manager on the main worker. This doesn't completely solve potential +noisy neighbor problems as the main worker will still be receiving & serving http requests, however it will at least +ensure that other worker processes are free to serve http requests without risk of TM interference. Long term, we +could explore manually spawning a dedicated child process for background tasks that can be called from workers, and +thinking of a way for plugins to tell Core when they need to run things in the background. -We probably only want one worker doing the task claims, and then when it gets tasks to run, sends them to a worker to run. -Short term, having only the 'main' worker perform the task claims and executions should be good enough. +It would be ideal if we could eventually solve this with our multi-process setup, however this needs more design work +and could necessitate an RFC in its own right. The key thing to take away here is that the work we are doing in this +RFC would not prevent us from exploring this path further in a subsequent phase. In fact, it could prove to be a +helpful first step in that direction. #### Alerting @@ -515,57 +541,79 @@ status API in clustering mode. Note that the new format for /api/status is still behind a v8format flag, meaning that if we do these changes before 8.0, we won't be introducing any breaking change later. -### 6.3.2 instanceUUID +### 6.3.2 stats API -Depending on our decision regarding the instanceUUID problematic, we may have to change the server.uuid configuration -property when clustering mode is enabled, which would be a breaking change. +TODO: -### 6.3.3 distinct logging configuration +### 6.3.3 instanceUUID -If we decide to have each worker output log in distinct files, we would have to change the logging configuration to -add a prefix/suffix to each log file, which would be a breaking change. Note that this option is probably not the one -we'll choose. +Depending on whether we are able to identify any cases where a shared uuid would be problematic, we may have to change +the server.uuid configuration property when clustering mode is enabled, which would be a breaking change. # 7. Drawbacks -- Implementation cost is going to be significant, both in core and in plugins. Also, this will have to be a collaborative - effort, as we can't enable the clustered mode in production until all the identified breaking changes have been addressed. - -- Even if easier to deploy, it doesn't really provide anything more than a multi-instances Kibana setup. - -- This will complexify the code, especially in Core were some part of the logic will drastically change between clustered and -non-clustered modes (e.g the status API, rolling-file appender). - -- It could introduce subtle bugs in clustered mode, as we may overlook some breaking changes, or developers may omit to -ensure clustered mode compatibility when adding new features. - -- Proper testing of all the edge cases is going to be tedious, if not just realistically impossible. We can't really - automate the testing of the clustered mode. +- Implementation cost is going to be significant as this will require multiple phases, both in core and in plugins. + Also, this will have to be a collaborative effort, as we can't enable cluster mode in production until all of the + identified breaking changes have been addressed. +- Even if it is easier to deploy, at a technical level it doesn't really provide anything more than a multi-instance Kibana setup. +- This will add complexity to the code, especially in Core where some parts of the logic will drastically diverge between + clustered and non-clustered modes (most notably our logging system). +- There is a risk of introducing subtle bugs in clustered mode, as we may overlook some breaking changes, or developers + may neglect to ensure clustered mode compatibility when adding new features. +- Proper testing of all the edge cases is going to be tedious, and in some cases realistically impossible. Proper + education of developers is going to be critical to ensure we are building new features with clustering in mind. # 8. Alternatives -One alternative of the `cluster` module is using a worker pool via `worker_threads`. Both have distinct use cases +One alternative to the `cluster` module is using a worker pool via `worker_threads`. Both have distinct use cases though. Clustering is meant to have multiple workers with the same codebase, often sharing a network socket to balance network traffic. Worker threads is a way to create specialized workers in charge of executing isolated, CPU intensive -tasks on demand (e.g encrypting or descrypting a file). If we were to identify that under heavy load, the actual bottleneck -is ES, maybe exposing a worker thread service and API from core (task_manager would be a perfect example of potential consumer) +tasks on demand (e.g. encrypting or descrypting a file). If we were to identify that under heavy load, the actual bottleneck +is ES, maybe exposing a worker thread service and API from Core (task_manager would be a perfect example of potential consumer) would make more sense. +However, we believe the simplicity and broad acceptance of the `cluster` API in the Node community makes it the +better approach over `worker_threads`, and would prefer to only go down the road of a worker pool as a last resort. + Another alternative would be to provide tooling to ease the deployment of multi-instance Kibana setups, and only support -multi-instance mode. +multi-instance mode moving forward. # 9. Adoption strategy -Phase 1: we perform the required changes in `Core`, and add the `clustering.enabled` configuration property for development mode only. -That way, we allow developers to test their features against clustering mode and to adapt their code to use the new `clustering` API -and service. +Because the changes proposed in this RFC touch the lowest levels of Kibana's core, and therefore have potential to impact +large swaths of Kibana's codebase, we propse a multi-phase strategy: + +## Phase 0 +In the prepratory phase, we will evolve the existing POC to validate the finer details of this RFC, while also putting together +a more detailed testing strategy that can be used to benchmark our future work. -Phase 2: when all the required changes have been performed in plugins code, we enable the `clustering` configuration on production mode as a `beta` feature. -We would ideally also add telemetry collection for the clustering usages (relevant metrics TBD) to have a precise vision of the adoption of the feature. +## Phase 1 +To start implementation, we will make the required changes in Core, adding the `clustering.enabled` configuration property +in development mode only. This way, we allow developers to test their features against clustering mode and to adapt their code +to use the new `clustering` API and service. At this point we will also aim to document any identified breaking changes and +add deprecation notices where applicable, to allow developers time to prepare for 8.0. + +## Phase 2 +When all the required changes have been performed in plugin code, we will enable the `clustering` configuration on production +mode as a `beta` feature. We would ideally also add telemetry collection for the clustering usages (relevant metrics TBD) +to have a precise vision of the adoption of the feature. + +## Phase 3 +Once the new feature has been validated and we are comfortable considering it GA, we will enable `clustering` by default. +(We could alternatively enable it by default from the outset, still with a `beta` label). # 10. How we teach this -During phase 1, we should create documentation on the clustering mode: best practices, how to identify code that may breaks in clustered mode, and so on. +During Phase 1, we should create documentation on the clustering mode: best practices, how to identify code that may break in +clustered mode, and so on. + +We will specifically look to make changes to our docs around contributing to Kibana, specifically we can add a section +in the [best practices](https://www.elastic.co/guide/en/kibana/master/development-best-practices.html#_testing_stability) to +remind contributers to be thinking about the fact that you cannot rely on a 1:1 relationship between the Kibana process and +an individual machine. + +Lastly, we'll take advantage of internal communications to kibana-contributors, and make an effort to individually check in +with the teams who we think will most likely be affected by these changes. # 11. Unresolved questions From 4591a6fb279ed9aa5d3ffd0f72e7844854ff2746 Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Tue, 25 May 2021 15:42:48 -0600 Subject: [PATCH 13/18] Cleanup some TODOs and add questions. --- rfcs/text/0015_nodejs_clustering.md | 33 ++++++++++++++++++++++------- 1 file changed, 25 insertions(+), 8 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index bd784c3e5a126..2a7ea17781b1d 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -142,6 +142,8 @@ would be available for users with more advanced use cases: ```yaml clustering: enabled: true # enabled by default + coordinator: + max_old_space_size: 1gb # optional, allows to configure memory limit for coordinator only workers: # when provided, total # of workers would be based on # of items in this list - name: foo # not technically necessary, but useful for logging purposes max_old_space_size: 1gb # optional, allows to configure memory limits per-worker @@ -150,8 +152,7 @@ clustering: ``` This per-worker design would give us the flexibility to eventually provide more fine-grained configuration, -like dedicated workers for http requests or background jobs. We could also eventually add `coordinator` -specific config. +like dedicated workers for http requests or background jobs. ## 5.2 Cross-worker communication @@ -393,7 +394,6 @@ We will need to add some centralized status state in the coordinator. Also, as t from the coordinator, we will also need to have the workers retrieve the global status from the coordinator to serve the status endpoint. -TODO: We may also want to have the `/status` endpoint display each individual worker status in addition to the global status, which may be breaking change in the `/status` API response format. @@ -418,10 +418,14 @@ Kibana, so this can probably be considered an improvement. In clustered mode, node options such as `max-old-space-size` will be used by all processes. +The `kibana` startup script will read this setting out of the CLI or `config/node.options` and set a NODE_OPTIONS environment +variable, which will be passed to any workers, possibly leading to unexpected behavior. + e.g. using `--max-old-space-size=1024` in a 2 workers cluster would have a maximum memory usage of 3gb (1 coordinator + 2 workers). -TODO: -Our recommendation is to _disable clustering by default when a user has set `max-old-space-size` in the `node.options` file_. +Our plan for addressing this is to _disable clustering if a user has `max-old-space-size` set at all_, which would ensure it isn't +possible to hit unpredictable behavior. To enable clustering, the user would simply remove `max-old-space-size` settings, and +clustering would be on by default. They could alternatively configure memory settings for each worker individually, as shown above. ### 6.1.7 Workers error handling @@ -543,7 +547,7 @@ we won't be introducing any breaking change later. ### 6.3.2 stats API -TODO: +TODO ### 6.3.3 instanceUUID @@ -617,8 +621,21 @@ with the teams who we think will most likely be affected by these changes. # 11. Unresolved questions -None (well, except every single section of the document). +**Is it okay for the workers to share the same `path.data` directory?** + +Still need plugin devs to confirm whether there are any plugins writing to these files, which could cause concurrency issues. +Reporting is the main question here. + +**Is using the same `server.uuid` in each worker going to cause problems?** + +Still need plugin devs to confirm whether this might be an issue, but so far we have no known cases where this would pose problems. # 12. Resolved questions -... +**How do we handle http requests that need to be served by a specific process?** + +The Node.js cluster API is not really the right solution for this, as it won't allow for custom scheduling policies. A custom scheduling policy would basically mean re-implementing the cluster API on our own. At this point we will not be solving this particular issue with the clustering project, however the abstraction proposed in this RFC will not preclude us from changing out the underlying implementation in the future should we choose to do so.  + +**How do we handle http requests that need to have knowledge of all processes?** + +`/status` and `/stats` are the big issues here, as they could be reported differently from each process. The current plan is to manage their state centrally in the coordinator and have each process report this data at a regular interval, so that all processes can retrieve it and serve it in response to any requests against that endpoint. Exact details of the changes to those APIs would need to be determined. I think `status` will likely require breaking changes as pointed out above, however `stats` may not. From 9c4df783b10de595b33cf8b354ed8240217ef71b Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Tue, 15 Jun 2021 12:12:24 -0600 Subject: [PATCH 14/18] Update based on latest feedback. --- rfcs/text/0015_nodejs_clustering.md | 75 +++++++++++++++++------------ 1 file changed, 43 insertions(+), 32 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 2a7ea17781b1d..fd1b46b5278a5 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -134,21 +134,31 @@ similar-ish environment locally (which wasn't done during the initial investigat ## 5.1 Enabling clustering mode -Enabling clustering mode will be done using the `clustering.enabled` configuration property. +Enabling clustering mode will be done using the `node.enabled` configuration property. If clustering is enabled by default, then no configuration would be required by users, and Kibana would automatically use all available cores. However, more detailed configuration would be available for users with more advanced use cases: ```yaml -clustering: +node: enabled: true # enabled by default + coordinator: max_old_space_size: 1gb # optional, allows to configure memory limit for coordinator only - workers: # when provided, total # of workers would be based on # of items in this list - - name: foo # not technically necessary, but useful for logging purposes - max_old_space_size: 1gb # optional, allows to configure memory limits per-worker - - name: bar + + # Basic config for multiple workers with the same options + workers: # when count is provided, all workers share the same config + count: 2 # worker names (for logging) are generated: `worker-1`, `worker-2` + max_old_space_size: 1gb # optional, allows to configure memory limits per-worker + + # Alternative advanced config, allowing for worker "types" to be configured + workers: + foo: # the key here would be used as the worker name + count: 2 max_old_space_size: 1gb + bar: + count: 1 + max_old_space_size: 512mb ``` This per-worker design would give us the flexibility to eventually provide more fine-grained configuration, @@ -160,12 +170,12 @@ For some of our changes (such as the `/status` API, see below), we will need som communication. This will need to pass through the coordinator, which will also serve as an 'event bus', or IPC forwarder. -This IPC API will be exposed from the clustering service: +This IPC API will be exposed from the node service: ```ts -export interface ClusteringServiceSetup { +export interface NodeServiceSetup { // [...] - broadcast: (type: string, payload?: ClusterMessagePayload, options?: BroadcastOptions) => void; + broadcast: (type: string, payload?: WorkerMessagePayload, options?: BroadcastOptions) => void; addMessageHandler: (type: string, handler: MessageHandler) => MessageHandlerUnsubscribeFn; } ``` @@ -176,6 +186,7 @@ given plugin will only be invoked for messages sent by the same plugin. Notes: - To reduce clustered and non-clustered mode divergence, in non-clustered mode, these APIs would just be no-ops. It will avoid forcing (most) code to check which mode Kibana is running before calling them. + - In the case where `sendToSelf` is true, we would still attempt to broadcast the message. - We could eventually use an Observable pattern instead of a handler pattern to subscribe to messages. ## 5.3 Executing code on a single worker @@ -189,10 +200,10 @@ such single-process jobs, as it doesn't actually run a Kibana server. There are various ways to address such use-cases. What seems to be the best compromise right now would be the concept of 'main worker'. The coordinator would arbitrarily elect a worker as the 'main' one at startup. The -clustering service would then expose an API to let workers identify themselves as main or not. +node service would then expose an API to let workers identify themselves as main or not. ```ts -export interface ClusteringServiceSetup { +export interface NodeServiceSetup { // [...] isMainWorker: () => boolean; } @@ -202,18 +213,18 @@ Notes: - In non-clustered mode, `isMainWorker` would always return true, to reduce the divergence between clustered and non-clustered modes. -## 5.4 The clustering service API +## 5.4 The node service API -We propose adding a new clustering service to Core, which will be responsible for adding the necessary cluster APIs, +We propose adding a new node service to Core, which will be responsible for adding the necessary cluster APIs, and handling interaction with Node's `cluster` API. This service would be accessible via Core's setup and start contracts -(`coreSetup.clustering` and `coreStart.clustering`). +(`coreSetup.node` and `coreStart.node`). -At the moment, no need to extend Core's request handler context with clustering related APIs has been identified. +At the moment, no need to extend Core's request handler context with node related APIs has been identified. The initial contract interface would look like this: ```ts -type ClusterMessagePayload = Serializable; +type WorkerMessagePayload = Serializable; interface BroadcastOptions { /** @@ -228,7 +239,7 @@ interface BroadcastOptions { persist?: boolean; } -export interface ClusteringServiceSetup { +export interface NodeServiceSetup { /** * Return true if clustering mode is enabled, false otherwise */ @@ -241,7 +252,7 @@ export interface ClusteringServiceSetup { * Broadcast a message to other workers. * In non-clustered mode, this is a no-op. */ - broadcast: (type: string, payload?: ClusterMessagePayload, options?: BroadcastOptions) => void; + broadcast: (type: string, payload?: WorkerMessagePayload, options?: BroadcastOptions) => void; /** * Registers a handler for given `type` of IPC messages * In non-clustered mode, this is a no-op that returns a no-op unsubscription callback. @@ -262,14 +273,14 @@ To take the example of SO migration, the `KibanaMigrator.runMigrations` implemen ```ts runMigration() { - if (clustering.isMainWorker()) { + if (node.isMainWorker()) { this.runMigrationsInternal().then((result) => { applyMigrationState(result); // persist: true will send message even if subscriber subscribes after the message was actually sent - clustering.broadcast('migration-complete', { payload: result }, { persist: true }); + node.broadcast('migration-complete', { payload: result }, { persist: true }); }) } else { - const unsubscribe = clustering.addMessageHandler('migration-complete', ({ payload: result }) => { + const unsubscribe = node.addMessageHandler('migration-complete', ({ payload: result }) => { applyMigrationState(result); unsubscribe(); }); @@ -288,7 +299,7 @@ This is not identified as necessary at the moment, and IPC broadcast should be s the added complexity and risk of implicit dependencies if possible. If we do eventually need shared state, we would probably have to use syscall libraries to share buffers such as -[mmap-io](https://www.npmjs.com/package/mmap-io), and expose a higher level API for that from the `clustering` service. More +[mmap-io](https://www.npmjs.com/package/mmap-io), and expose a higher level API for that from the `node` service. More research would be required if this proved to be a necessity. # 6. Technical impact @@ -323,8 +334,7 @@ with each worker sending the coordinator log messages via IPC. While this is a m of our logging system, it solves several problems: - Preserves backwards compatibility. - Avoids the issue of interleaved log messages that could occur with multiple processes writing to the same file or stdout. -- Provides a solution for the rolling-file appender (see below), as the coordinator would handle rolling all log file -(small caveat being a slight loss in file size precision). +- Provides a solution for the rolling-file appender (see below), as the coordinator would handle rolling all log files - The changes to BaseLogger could potentially have the added benefit of paving the way for our future logging MDC. We could add the process name information to the log messages, and add a new conversion to be able to display it with @@ -479,8 +489,8 @@ Kibana instance id? Are there situations where having the same instance UUID for Is there any part of the code that needs to be executed only once in a multi-worker mode, such as initialization code, or starting schedulers? -An example would be Reporting's queueFactory pooling. As we want to only be running a single headless at a time per -Kibana instance, only one worker should have pooling enabled. +An example would be Reporting's queueFactory polling. As we want to only be running a single headless at a time per +Kibana instance, only one worker should have polling enabled. ### 6.2.2 Identified required changes @@ -488,7 +498,7 @@ Kibana instance, only one worker should have pooling enabled. We will probably want to restrict to a single headless per Kibana instance. For that, we will have to change the logic in [createQueueFactory](https://github.com/elastic/kibana/blob/4584a8b570402aa07832cf3e5b520e5d2cfa7166/x-pack/plugins/reporting/server/lib/create_queue.ts#L60-L64) -to only have the 'main' worker be pooling for reporting tasks. +to only have the 'main' worker be polling for reporting tasks. #### Telemetry @@ -592,18 +602,19 @@ In the prepratory phase, we will evolve the existing POC to validate the finer d a more detailed testing strategy that can be used to benchmark our future work. ## Phase 1 -To start implementation, we will make the required changes in Core, adding the `clustering.enabled` configuration property -in development mode only. This way, we allow developers to test their features against clustering mode and to adapt their code -to use the new `clustering` API and service. At this point we will also aim to document any identified breaking changes and +To start implementation, we will make the required changes in Core, adding the `node.enabled` configuration property. +At first, we'll include a big warning in the logs to make it clear that this shouldn't be used in production yet. +This way, we allow developers to test their features against clustering mode and to adapt their code +to use the new `node` API and service. At this point we will also aim to document any identified breaking changes and add deprecation notices where applicable, to allow developers time to prepare for 8.0. ## Phase 2 -When all the required changes have been performed in plugin code, we will enable the `clustering` configuration on production +When all the required changes have been performed in plugin code, we will enable the `node` configuration on production mode as a `beta` feature. We would ideally also add telemetry collection for the clustering usages (relevant metrics TBD) to have a precise vision of the adoption of the feature. ## Phase 3 -Once the new feature has been validated and we are comfortable considering it GA, we will enable `clustering` by default. +Once the new feature has been validated and we are comfortable considering it GA, we will enable `node` by default. (We could alternatively enable it by default from the outset, still with a `beta` label). # 10. How we teach this From b1afaa1e90a981ab25fdd88613a90d6ce2e75b36 Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Tue, 15 Jun 2021 14:24:02 -0600 Subject: [PATCH 15/18] Update sections on status and stats --- rfcs/text/0015_nodejs_clustering.md | 87 ++++++++++++++++++++++------- 1 file changed, 67 insertions(+), 20 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index fd1b46b5278a5..0d9d186458823 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -404,10 +404,57 @@ We will need to add some centralized status state in the coordinator. Also, as t from the coordinator, we will also need to have the workers retrieve the global status from the coordinator to serve the status endpoint. -We may also want to have the `/status` endpoint display each individual worker status in addition to the -global status, which may be breaking change in the `/status` API response format. +Ultimately, we'd need to make the following updates to the `/status` API, neither of which +is a breaking change: +1. The response will return the highest-severity status level for each plugin, which will be +determined by looking at the shared global status stored in the coordinator. +2. We will introduce an extension to the existing `/status` response to allow inspecting +per-worker statuses. + +### 6.1.4 The stats API & metrics service + +The `/stats` endpoint is somewhat problematic in that it contains a handful of `process` metrics +which will differ from worker-to-worker: +```json +{ + // ... + "process": { + "memory": { + "heap": { + "total_bytes": 533581824, + "used_bytes": 296297424, + "size_limit": 4345298944 + }, + "resident_set_size_bytes": 563625984 + }, + "pid": 52646, + "event_loop_delay": 0.22967800498008728, + "uptime_ms": 1706021.930404 + }, + // ... +} +``` + +As each request could be routed to a different worker, different results may come back each time. + +This endpoint, registered from the `usage_collection` plugin, is getting these stats from Core's +`metrics` service (`getOpsMetrics$`), which is also used in the `monitoring` plugin for stats +collection. -### 6.1.4 PID file +While we could try to follow a plan similar to `/status` and have each worker report metrics to +the coordinator, there isn't a particularly sensible way to consolidate these. (e.g. Taking +the average of these values isn't really helpful in case there's a scenario where one process +is, for example, experiencing a spike in `event_loop_delay` while the others are operating +normally). + +Ultimately we could extend the API to provide per-worker stats, but the question remains what we +should do with the existing `process` stats: +1. Deprecate them? (breaking change) +2. Accept a situation where they may be round-robined to different workers? (probably no) +3. Try to consolidate them somehow? (can't think of a good way to do this) +4. Always return stats for one process, e.g. main or coordinator? (doesn't give us the full picture) + +### 6.1.5 PID file Without changes, each worker is going to try to write and read the same PID file. Also, this breaks the whole pid file usage, as the PID stored in the file will be a arbitrary worker’s PID, instead of the coordinator (main process) PID. @@ -415,7 +462,7 @@ usage, as the PID stored in the file will be a arbitrary worker’s PID, instead In clustering mode, we will need to have to coordinator handle the PID file logic, and to disable pid file handling in the worker's environment service. -### 6.1.5 Saved Objects migration +### 6.1.6 Saved Objects migration In the current state, all workers are going to try to perform the migration. Ideally, we would have only one process perform the migration, and the other ones just wait for a ready signal. We can’t easily have the coordinator do it, @@ -424,7 +471,7 @@ so we would probably have to leverage the ‘main worker’ concept here. The SO migration v2 is supposed to be resilient to concurrent attempts though, as we already support multi-instances Kibana, so this can probably be considered an improvement. -### 6.1.6 Memory consumption +### 6.1.7 Memory consumption In clustered mode, node options such as `max-old-space-size` will be used by all processes. @@ -437,7 +484,7 @@ Our plan for addressing this is to _disable clustering if a user has `max-old-sp possible to hit unpredictable behavior. To enable clustering, the user would simply remove `max-old-space-size` settings, and clustering would be on by default. They could alternatively configure memory settings for each worker individually, as shown above. -### 6.1.7 Workers error handling +### 6.1.8 Workers error handling When using `cluster`, the common best practice is to have the coordinator recreate ('restart') workers when they terminate unexpectedly. However, given Kibana's architecture, some failures are not recoverable (workers failing because of config validation, failed migration...). @@ -449,7 +496,7 @@ As a first step, we plan to terminate the main Kibana process when any worker te this is already the behavior in non-cluster mode). In the future, we will look toward distinguishing between recoverable and non-recoverable errors as an enhancement, so that we can automatically restart workers on any recoverable error. -### 6.1.8 Data folder +### 6.1.9 Data folder The data folder (`path.data`) is currently the same for all workers. @@ -459,7 +506,7 @@ are accessing files in write mode, which could result in concurrency issues betw If that was confirmed, we would plan to create and use a distinct data folder for each worker, which would be non-breaking as we don't consider the layout of this directory to be part of our public API. -### 6.1.9 instanceUUID +### 6.1.10 instanceUUID The same instance UUID (`server.uuid` / `{dataFolder}/uuid`) is currently used by all the workers. @@ -547,22 +594,18 @@ Do we need the alerting task runner (`TaskRunner`, `TaskRunnerFactory`) to be ru ## 6.3 Summary of breaking changes -### 6.3.1 status API - -If we want to have the status API returns each individual worker's status, we will need to change the output of the -status API in clustering mode. +### 6.3.1 instanceUUID -Note that the new format for /api/status is still behind a v8format flag, meaning that if we do these changes before 8.0, -we won't be introducing any breaking change later. +Depending on whether we are able to identify any cases where a shared uuid would be problematic, we may have to change +the server.uuid configuration property when clustering mode is enabled, which would be a breaking change. -### 6.3.2 stats API +At this point, we have not identified any places where this is strictly necessary. -TODO +### 6.3.2 `/stats` API & metrics service -### 6.3.3 instanceUUID - -Depending on whether we are able to identify any cases where a shared uuid would be problematic, we may have to change -the server.uuid configuration property when clustering mode is enabled, which would be a breaking change. +The `process` memory usage reported here doesn't really make sense in a multi-process Kibana. +One option to consider is breaking the API by deprecating `process`, or turning it into a list of +process stats reported from each worker. This is an open question still. # 7. Drawbacks @@ -632,6 +675,10 @@ with the teams who we think will most likely be affected by these changes. # 11. Unresolved questions +**Are breaking changes required for the `/stats` API & metrics service?** + +See 6.1.4 above. + **Is it okay for the workers to share the same `path.data` directory?** Still need plugin devs to confirm whether there are any plugins writing to these files, which could cause concurrency issues. From 6fcc6a4bcf6e418a22e5b7e96314e7ece19c9b26 Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Mon, 21 Jun 2021 16:41:42 -0600 Subject: [PATCH 16/18] Update based on resolved questions. --- rfcs/text/0015_nodejs_clustering.md | 68 +++++++++++++++++++++-------- 1 file changed, 50 insertions(+), 18 deletions(-) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0015_nodejs_clustering.md index 0d9d186458823..abfbd2dd9be42 100644 --- a/rfcs/text/0015_nodejs_clustering.md +++ b/rfcs/text/0015_nodejs_clustering.md @@ -441,19 +441,46 @@ This endpoint, registered from the `usage_collection` plugin, is getting these s `metrics` service (`getOpsMetrics$`), which is also used in the `monitoring` plugin for stats collection. -While we could try to follow a plan similar to `/status` and have each worker report metrics to -the coordinator, there isn't a particularly sensible way to consolidate these. (e.g. Taking -the average of these values isn't really helpful in case there's a scenario where one process -is, for example, experiencing a spike in `event_loop_delay` while the others are operating -normally). - -Ultimately we could extend the API to provide per-worker stats, but the question remains what we -should do with the existing `process` stats: +Ultimately we will extend the API to provide per-worker stats, but the question remains what we +should do with the existing `process` stats. + +#### Options we considered: 1. Deprecate them? (breaking change) 2. Accept a situation where they may be round-robined to different workers? (probably no) 3. Try to consolidate them somehow? (can't think of a good way to do this) 4. Always return stats for one process, e.g. main or coordinator? (doesn't give us the full picture) +#### Our recommended approach: +We agreed that we would go with (3) and have each worker report metrics to the coordinator for +sharing, with the metrics aggregated as follows: +```json +{ + // ... + "process": { + "memory": { + "heap": { + "total_bytes": 533581824, // sum of coordinator + workers + "used_bytes": 296297424, // sum of coordinator + workers + "size_limit": 4345298944 // sum of coordinator + workers + }, + "resident_set_size_bytes": 563625984 // sum of coordinator + workers + }, + "pid": 52646, // pid of the coordinator + "event_loop_delay": 0.22967800498008728, // max of coordinator + workers + "uptime_ms": 1706021.930404 // uptime of the coordinator + }, + // ... +} +``` + +This has its downsides (`size_limit` in particular could be confusing), but otherwise generally makes sense: +- sum of available/used heap & node rss is straightforward +- `event_loop_delay` max makes sense, as we are mostly only interested in that number if it is high anyway +- `pid` and `uptime_in_millis` from the coordinator make sense, especially as long as we are killing +all workers any time one of them dies. In the future if we respawn workers that die, this could be +misleading, but hopefully by then we can deprecate this and move Metricbeat to using the per-worker +stats. + ### 6.1.5 PID file Without changes, each worker is going to try to write and read the same PID file. Also, this breaks the whole pid file @@ -576,6 +603,8 @@ We could address that by making sure that the queues are held only in the main w Currently, task manager does "claims" for jobs to run based on the server uuid. We think this could still work with a multi-process setup - each task manager in the worker would be doing "claims" for the same server uuid, which seems functionally the same as setting max_workers to `current max_workers * number of workers`. +Another alternative would be to compose something like `${server.uuid}-${worker.Id}`, as TM only +really needs a unique identifier. However, as a first step we can simply run Task Manager on the main worker. This doesn't completely solve potential noisy neighbor problems as the main worker will still be receiving & serving http requests, however it will at least @@ -590,7 +619,8 @@ helpful first step in that direction. #### Alerting -Do we need the alerting task runner (`TaskRunner`, `TaskRunnerFactory`) to be running on a single worker? +Currently haven't identified any Alerting-specific requirements that aren't already covered by the +Task Manager requirements. ## 6.3 Summary of breaking changes @@ -679,15 +709,6 @@ with the teams who we think will most likely be affected by these changes. See 6.1.4 above. -**Is it okay for the workers to share the same `path.data` directory?** - -Still need plugin devs to confirm whether there are any plugins writing to these files, which could cause concurrency issues. -Reporting is the main question here. - -**Is using the same `server.uuid` in each worker going to cause problems?** - -Still need plugin devs to confirm whether this might be an issue, but so far we have no known cases where this would pose problems. - # 12. Resolved questions **How do we handle http requests that need to be served by a specific process?** @@ -697,3 +718,14 @@ The Node.js cluster API is not really the right solution for this, as it won't a **How do we handle http requests that need to have knowledge of all processes?** `/status` and `/stats` are the big issues here, as they could be reported differently from each process. The current plan is to manage their state centrally in the coordinator and have each process report this data at a regular interval, so that all processes can retrieve it and serve it in response to any requests against that endpoint. Exact details of the changes to those APIs would need to be determined. I think `status` will likely require breaking changes as pointed out above, however `stats` may not. + +**Is it okay for the workers to share the same `path.data` directory?** + +We have been unable to identify any plugins which are writing to this directory. +The App Services team has confirmed that `path.data` is no longer in use in the reporting plugin. + +**Is using the same `server.uuid` in each worker going to cause problems?** + +We have been unable to identify any plugins for which this would cause issues. +The Alerting team has confirmed that Task Manager doesn't need server uuid, just a unique +identifier. That means something like server.uuid + worker.id would work. From 0b63a1c776ae725b53d64d24dc5068d585fdd34c Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Mon, 28 Jun 2021 07:52:31 -0600 Subject: [PATCH 17/18] Rename file. --- .../text/{0015_nodejs_clustering.md => 0016_nodejs_clustering.md} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename rfcs/text/{0015_nodejs_clustering.md => 0016_nodejs_clustering.md} (100%) diff --git a/rfcs/text/0015_nodejs_clustering.md b/rfcs/text/0016_nodejs_clustering.md similarity index 100% rename from rfcs/text/0015_nodejs_clustering.md rename to rfcs/text/0016_nodejs_clustering.md From de36e2381b4222bafe78c5995d225c691bd98dd0 Mon Sep 17 00:00:00 2001 From: Luke Elmers Date: Mon, 28 Jun 2021 12:12:00 -0600 Subject: [PATCH 18/18] Clarify language on breaking changes + 1 more file rename. --- ...s_clustering.md => 0020_nodejs_clustering.md} | 16 +++++++--------- 1 file changed, 7 insertions(+), 9 deletions(-) rename rfcs/text/{0016_nodejs_clustering.md => 0020_nodejs_clustering.md} (98%) diff --git a/rfcs/text/0016_nodejs_clustering.md b/rfcs/text/0020_nodejs_clustering.md similarity index 98% rename from rfcs/text/0016_nodejs_clustering.md rename to rfcs/text/0020_nodejs_clustering.md index abfbd2dd9be42..62c4de4d3cbe4 100644 --- a/rfcs/text/0016_nodejs_clustering.md +++ b/rfcs/text/0020_nodejs_clustering.md @@ -624,18 +624,16 @@ Task Manager requirements. ## 6.3 Summary of breaking changes -### 6.3.1 instanceUUID +### 6.3.1 `/stats` API & metrics service -Depending on whether we are able to identify any cases where a shared uuid would be problematic, we may have to change -the server.uuid configuration property when clustering mode is enabled, which would be a breaking change. +Currently the only breaking change we have identified is for the `/stats` API. -At this point, we have not identified any places where this is strictly necessary. +The `process` memory usage reported doesn't really make sense in a multi-process Kibana, and +even though we have a plan to aggregate this data as a temporary solution (see 6.1.4), this +could still lead to confusion for users as it doesn't paint a clear picture of the state of the system. -### 6.3.2 `/stats` API & metrics service - -The `process` memory usage reported here doesn't really make sense in a multi-process Kibana. -One option to consider is breaking the API by deprecating `process`, or turning it into a list of -process stats reported from each worker. This is an open question still. +Our plan is to deprecate the `process` field, and later remove it or change the structure +to better support a multi-process Kibana. # 7. Drawbacks