From 56d26ac2ff1fc0051ea99033186838ca3d677254 Mon Sep 17 00:00:00 2001 From: robertgshaw Date: Sun, 27 Nov 2022 20:20:56 -0500 Subject: [PATCH 01/17] Added Prometheus Tutorial --- examples/logging-prometheus/README.md | 212 ++++++++++++++++ .../logging-prometheus/client/all_black.jpeg | Bin 0 -> 1651 bytes examples/logging-prometheus/client/client.py | 52 ++++ .../logging-prometheus/client/goldfish.jpeg | Bin 0 -> 58213 bytes examples/logging-prometheus/custom-fn.py | 6 + .../docker/docker-compose.yaml | 20 ++ .../logging-prometheus/docker/prometheus.yaml | 11 + .../logging-prometheus/grafana/dashboard.json | 230 ++++++++++++++++++ .../image/grafana-dashboard.png | Bin 0 -> 49721 bytes .../image/prometheus-graph.png | Bin 0 -> 85288 bytes .../logging-prometheus/server-config.yaml | 18 ++ 11 files changed, 549 insertions(+) create mode 100644 examples/logging-prometheus/README.md create mode 100644 examples/logging-prometheus/client/all_black.jpeg create mode 100644 examples/logging-prometheus/client/client.py create mode 100644 examples/logging-prometheus/client/goldfish.jpeg create mode 100644 examples/logging-prometheus/custom-fn.py create mode 100644 examples/logging-prometheus/docker/docker-compose.yaml create mode 100644 examples/logging-prometheus/docker/prometheus.yaml create mode 100644 examples/logging-prometheus/grafana/dashboard.json create mode 100644 examples/logging-prometheus/image/grafana-dashboard.png create mode 100644 examples/logging-prometheus/image/prometheus-graph.png create mode 100644 examples/logging-prometheus/server-config.yaml diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md new file mode 100644 index 0000000000..e2b75d31ca --- /dev/null +++ b/examples/logging-prometheus/README.md @@ -0,0 +1,212 @@ +# DeepSparse Server + Prometheus/Grafana + +DeepSparse Logging is compatible with Prometheus/Grafana, making it easy to stand up a model monitoring service. + +This tutorial will show you how to connect DeepSparse Logging to the Prometheus/Grafana stack. + +#### There are four steps: +- Configure DeepSparse Logging to log metrics in Prometheus format to a REST endpoint +- Point Prometheus to the appropriate endpoint to scape the data at a specified interval +- Run the toy client to perform inference +- Visualize data in Prometheus with dashboarding tool like Grafana + +## 0. Setting Up +#### Installation + +To run this tutorial, you need Docker, Docker Compose, and DeepSparse Server +- [Docker Installation](https://docs.docker.com/engine/install/) +- [Docker Compose Installation](https://docs.docker.com/compose/install/) +- DeepSparse Server is installed via PyPi (`pip install deepsparse[server]`) + +#### Code +The repository contains all the code you need: + +```bash +. +├── client +│   ├── client.py # simple client application for interacting with Server +│   └── goldfish.jpeg # photo of a goldfish +| └── all_black.jpeg # photo with just black pixes +├── server-config.yaml # specifies the configuration of the DeepSparse server +├── custom-fn.py # custom function used for the logging +├── docker # specifies the configuration of the containerized Prometheus/Grafana stack +│   ├── docker-compose.yaml +│   └── prometheus.yaml +└── grafana # specifies the design of the Grafana dashboard + └── dashboard.json +``` +## 1. Spin up the DeepSparse Server + +`server-config.yaml` specifies the config of the DeepSparse Server, including for logging: + +```yaml +# server-config.yaml + +loggers: + prometheus: # logs to prometheus on port 6100 + port: 6100 + +endpoints: + - task: image_classification + route: /image_classification/predict + model: zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/pruned95_quant-none + data_logging: + pipeline_inputs.images[0]: # applies to the first image (of the form stage.property[idx]) + - func: fraction_zeros # built-in function + frequency: 1 + target_loggers: + - prometheus + - func: custom-fn.py:mean_pixel_red # custom function + frequency: 1 + target_loggers: + - prometheus +``` + +The config file instructs the server to create an image classification pipeline. Prometheus logs are declared to be exposed on port `6100`, system logging is turned on, and we will log the mean pixel of the red channel as well as the percentage of pixels that are 0 for each image sent to the server.. + +Thus, once launched, the Server exposes two endpoints: +- port `6100`: exposes the `metrics` endpoint through [Prometheus python client](https://github.com/prometheus/client_python). +- port `5543`: exposes the endpoint for inference. + +To spin up the Server execute: +``` +deepsparse.server --config server-config.yaml +``` + +To validate that metrics are being properly exposed, visit `localhost:6100`. It should contain logs in the specific format meant to be used by the PromQL query language. + +## 2. Setup Prometheus/Grafana Stack + +For simplicity, we have provided `docker-compose.yaml` that spins up the containerized Prometheus/Grafana stack. In that file, we instruct `prometheus.yaml` (a [Prometheus config file](https://prometheus.io/docs/prometheus/latest/configuration/configuration/)) to be passed to the Prometheus container. Inside `prometheus.yaml`, the `scrape_config` has the information about the `metrics` endpoint exposed by the server on port `6100`. + +Docker Compose File: + +```yaml +# docker-compose.yaml + +version: "3" + +services: + prometheus: + image: prom/prometheus + extra_hosts: + - "host.docker.internal:host-gateway" # allow a direct connection from container to the local machine + ports: + - "9090:9090" # the default port used by Prometheus + volumes: + - ${PWD}/prometheus.yaml:/etc/prometheus/prometheus.yml # mount Prometheus config file + + grafana: + image: grafana/grafana:latest + depends_on: + - prometheus + ports: + - "3000:3000" # the default port used by Grafana + +``` + +Prometheus Config file: + +```yaml +# prometheus.yaml + +global: + scrape_interval: 15s # how often to scrape from endpoint + evaluation_interval: 30s # time between each evaluation of Prometheus' alerting rules + +scrape_configs: + - job_name: prometheus_logs # your project name + static_configs: + - targets: + - 'host.docker.internal:6100' # should match the port exposed by the PrometheusLogger in the DeepSparse Server config file +``` + + +To start up a Prometheus stack to monitor the DeepSparse Server, run: + +```bash +cd docker +docker-compose up +``` + +## 3. Launch the Python Client and Run Inference + +`client.py` is a simple client that simulates the behavior of some application. In the example, we have two images: + - `goldfish.jpeg`: sample photo of a Goldfish + - `all-black.jpeg`: a photo that is all black (every pixel is a 0) + +The client sends requests to the Server, initially with "just" the Goldfish. Over time, we start to randomly +send the All Black image to the server with increasing probability. This simulates a data issue in the +pipeline that we can detect with the monitoring system. + +Run the following to start inference: + +```bash +python client/client.py +``` +The first argument is the path to the sample image, while the second argument is the port number that matches the inference endpoint of the Server. + +## 4. Inspecting the Prometheus/Grafana Stack + +### Prometheus + +#### Confirm It Is Working + +Visiting `http://localhost:9090/targets` should show that an endpoint `http://host.docker.internal:6100/metrics` is in state `UP`. + +#### Query Prometheus with PromQL + +If you do not want to use Grafana, you can start off by using Prometheus's native graphing functionality. + +Navigate to `http://localhost:9090/graph` and add the following `Expression`: + +``` +rate(image_classification__0__pipeline_inputs__images__fraction_zeros_sum[30s]) +/ +rate(image_classification__0__pipeline_inputs__images__fraction_zeros_count[30s]) +``` +Toggle from `Table` to `Graph`. You should see the following: + +![prometheus-log.png](image/prometheus-log.png) + +This graph shows the percentage of 0's. A the "corrupted" all black images were +sent to the server in increasing numbers, we can clearly see a spike in the graph, alerting us +that something strange is happening with the provided input. + +For more details on working with the Prometheus Query Language PromQL, +see [the official docs](https://prometheus.io/docs/prometheus/latest/querying/basics/). + +### Grafana + +#### Login + +Visit `localhost:3000` to launch Grafana. Log in with the default username (`admin`) and password (`admin`). + +#### Add Prometheus Data Source +Setup the Prometheus data source (`Add your first data source` -> `Prometheus`). On this page, we just +need to update the `url` section. Since Grafana and Prometheus are running separate docker containers, +put we need to put the IP address of the Prometheus container. + +Run `docker container ls` to lookup the `name` of the Prometheus container. It should be something like `docker_prometheus_1`. + +Run the following to lookup the IP address: +``` +docker inspect -f '{{range.NetworkSettings.Networks}}{{.IPAddress}}{{end}}' container_name_or_id +>>> 172.18.0.2 +``` + +So, in our case, the `url` section should be: `http://172.18.0.2:9090`. + +Click `Save & Test`. We should get a green check saying "Data Source Is Working". + +#### Import A Dashboard + +Now you should be ready to create/import your dashboard. + +Grafana's interface for adding metrics is very intuitive (and you can use PromQL), +but we have a simple pre-made dashboard for this use case. + +Click `Dashboard` -> `Import` on the left-hand side bar. You should see an option to upload a file. +Upload `grafana/dashboard.json` and save. Then, you should see the following dashboard: + +![img.png](images/grafana-dashboard.png) \ No newline at end of file diff --git a/examples/logging-prometheus/client/all_black.jpeg b/examples/logging-prometheus/client/all_black.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..c045c5945c1071f3d4bd4e3f0d878cec6899bc17 GIT binary patch literal 1651 zcmex=^(PF6}rMnOeST|r4lSw=>~TvNxu(8R<uA z0}~@NGZPClD=P~NP<1U(o`FS>RY=j$kxe)-kzJ`!#HexNLJno8jR!@8E`CrkPAY2R z|V^&07y2J$~}^+4C1KUw!=a`ODXD-+%o41@afjpD+ON7@EHXf&OA*VPR%r2lxYE#}NLy#lXYN2#h>tK?Zw= 0.): + img_path = None + if random.uniform(0, 1) < cutoff: + img_path = img2_path + else: + img_path = img1_path + + files = [('request', open(img_path, 'rb'))] + resp = requests.post(url=url, files=files) + print(f"Sent File: {img_path}") + + if count == MAX_COUNT: + count = 0 + cutoff -= CUTOFF_INCREMENT + count += 1 + time.sleep(0.25) + +if __name__ == "__main__": + args = vars(parser.parse_args()) + run_example(args["url"], 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prom/prometheus + extra_hosts: + - "host.docker.internal:host-gateway" # allow a direct connection from container to the local machine + ports: + - "9090:9090" # the default port used by Prometheus + volumes: + - ${PWD}/prometheus.yaml:/etc/prometheus/prometheus.yml # mount Prometheus config file + + grafana: + image: grafana/grafana:latest + depends_on: + - prometheus + ports: + - "3000:3000" # the default port used by Grafana diff --git a/examples/logging-prometheus/docker/prometheus.yaml b/examples/logging-prometheus/docker/prometheus.yaml new file mode 100644 index 0000000000..111357c783 --- /dev/null +++ b/examples/logging-prometheus/docker/prometheus.yaml @@ -0,0 +1,11 @@ +# prometheus.yaml + +global: + scrape_interval: 15s # how often to scrape from endpoint + evaluation_interval: 30s # time between each evaluation of Prometheus' alerting rules + +scrape_configs: + - job_name: deepsparse_img_classification # your project name + static_configs: + - targets: + - 'host.docker.internal:6100' # should match the port exposed by the PrometheusLogger in the DeepSparse Server config file \ No newline at end of file diff --git a/examples/logging-prometheus/grafana/dashboard.json b/examples/logging-prometheus/grafana/dashboard.json new file mode 100644 index 0000000000..99145b4c38 --- /dev/null +++ b/examples/logging-prometheus/grafana/dashboard.json @@ -0,0 +1,230 @@ +{ + "annotations": { + "list": [ + { + "builtIn": 1, + "datasource": { + "type": "grafana", + "uid": "-- Grafana --" + }, + "enable": true, + "hide": true, + "iconColor": "rgba(0, 211, 255, 1)", + "name": "Annotations & Alerts", + "target": { + "limit": 100, + "matchAny": false, + "tags": [], + "type": "dashboard" + }, + "type": "dashboard" + } + ] + }, + "editable": true, + "fiscalYearStartMonth": 0, + "graphTooltip": 0, + "links": [], + "liveNow": false, + "panels": [ + { + "datasource": { + "type": "prometheus", + "uid": "ZFVT-gK4z" + }, + "fieldConfig": { + "defaults": { + "color": { + "mode": "palette-classic" + }, + "custom": { + "axisCenteredZero": false, + "axisColorMode": "text", + "axisLabel": "", + "axisPlacement": "auto", + "barAlignment": 0, + "drawStyle": "line", + "fillOpacity": 0, + "gradientMode": "none", + "hideFrom": { + "legend": false, + "tooltip": false, + "viz": false + }, + "lineInterpolation": "linear", + "lineWidth": 1, + "pointSize": 5, + "scaleDistribution": { + "type": "linear" + }, + "showPoints": "auto", + "spanNulls": false, + "stacking": { + "group": "A", + "mode": "none" + }, + "thresholdsStyle": { + "mode": "off" + } + }, + "mappings": [], + "thresholds": { + "mode": "absolute", + "steps": [ + { + "color": "green", + "value": null + }, + { + "color": "red", + "value": 80 + } + ] + } + }, + "overrides": [] + }, + "gridPos": { + "h": 8, + "w": 12, + "x": 0, + "y": 0 + }, + "id": 4, + "options": { + "legend": { + "calcs": [], + "displayMode": "list", + "placement": "bottom", + "showLegend": true + }, + "tooltip": { + "mode": "single", + "sort": "none" + } + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "ZFVT-gK4z" + }, + "editorMode": "code", + "expr": "rate(image_classification__0__pipeline_inputs__images__fraction_zeros_sum[30s])/rate(image_classification__0__pipeline_inputs__images__fraction_zeros_count[30s])", + "legendFormat": "__auto", + "range": true, + "refId": "A" + } + ], + "title": "Percentage of 0 Pixels", + "type": "timeseries" + }, + { + "datasource": { + "type": "prometheus", + "uid": "ZFVT-gK4z" + }, + "fieldConfig": { + "defaults": { + "color": { + "mode": "palette-classic" + }, + "custom": { + "axisCenteredZero": false, + "axisColorMode": "text", + "axisLabel": "", + "axisPlacement": "auto", + "barAlignment": 0, + "drawStyle": "line", + "fillOpacity": 0, + "gradientMode": "none", + "hideFrom": { + "legend": false, + "tooltip": false, + "viz": false + }, + "lineInterpolation": "linear", + "lineWidth": 1, + "pointSize": 5, + "scaleDistribution": { + "type": "linear" + }, + "showPoints": "auto", + "spanNulls": false, + "stacking": { + "group": "A", + "mode": "none" + }, + "thresholdsStyle": { + "mode": "off" + } + }, + "mappings": [], + "thresholds": { + "mode": "absolute", + "steps": [ + { + "color": "green", + "value": null + }, + { + "color": "red", + "value": 80 + } + ] + } + }, + "overrides": [] + }, + "gridPos": { + "h": 9, + "w": 12, + "x": 0, + "y": 8 + }, + "id": 2, + "options": { + "legend": { + "calcs": [], + "displayMode": "list", + "placement": "bottom", + "showLegend": true + }, + "tooltip": { + "mode": "single", + "sort": "none" + } + }, + "targets": [ + { + "datasource": { + "type": "prometheus", + "uid": "ZFVT-gK4z" + }, + "editorMode": "code", + "expr": "rate(image_classification__0__pipeline_inputs__images__mean_pixel_red_sum[30s])\n/\nrate(image_classification__0__pipeline_inputs__images__mean_pixel_red_count[30s])", + "legendFormat": "__auto", + "range": true, + "refId": "A" + } + ], + "title": "Mean Pixel Value Red Channel", + 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Date: Sun, 27 Nov 2022 20:22:14 -0500 Subject: [PATCH 02/17] Update README.md --- examples/logging-prometheus/README.md | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index e2b75d31ca..32863525fe 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -1,8 +1,6 @@ -# DeepSparse Server + Prometheus/Grafana +# DeepSparse + Prometheus/Grafana -DeepSparse Logging is compatible with Prometheus/Grafana, making it easy to stand up a model monitoring service. - -This tutorial will show you how to connect DeepSparse Logging to the Prometheus/Grafana stack. +This is a simple example that shows you how to connect DeepSparse Logging to the Prometheus/Grafana stack. #### There are four steps: - Configure DeepSparse Logging to log metrics in Prometheus format to a REST endpoint @@ -209,4 +207,4 @@ but we have a simple pre-made dashboard for this use case. Click `Dashboard` -> `Import` on the left-hand side bar. You should see an option to upload a file. Upload `grafana/dashboard.json` and save. Then, you should see the following dashboard: -![img.png](images/grafana-dashboard.png) \ No newline at end of file +![img.png](images/grafana-dashboard.png) From 6a636ec3b5cf4deeba5c70e0f892d18022bcf32e Mon Sep 17 00:00:00 2001 From: Robert Shaw <114415538+rsnm2@users.noreply.github.com> Date: Sun, 27 Nov 2022 20:22:40 -0500 Subject: [PATCH 03/17] Update README.md --- examples/logging-prometheus/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index 32863525fe..0a235f93bb 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -24,7 +24,7 @@ The repository contains all the code you need: ├── client │   ├── client.py # simple client application for interacting with Server │   └── goldfish.jpeg # photo of a goldfish -| └── all_black.jpeg # photo with just black pixes +| └── all_black.jpeg # photo with just black pixels ├── server-config.yaml # specifies the configuration of the DeepSparse server ├── custom-fn.py # custom function used for the logging ├── docker # specifies the configuration of the containerized Prometheus/Grafana stack From 73ee9740f099acef798ae5a5a3db7fb00b89824a Mon Sep 17 00:00:00 2001 From: Robert Shaw <114415538+rsnm2@users.noreply.github.com> Date: Sun, 27 Nov 2022 20:23:33 -0500 Subject: [PATCH 04/17] Update README.md --- examples/logging-prometheus/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index 0a235f93bb..b060dd34a4 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -60,7 +60,7 @@ endpoints: - prometheus ``` -The config file instructs the server to create an image classification pipeline. Prometheus logs are declared to be exposed on port `6100`, system logging is turned on, and we will log the mean pixel of the red channel as well as the percentage of pixels that are 0 for each image sent to the server.. +The config file instructs the server to create an image classification pipeline. Prometheus logs are declared to be exposed on port `6100`, system logging is turned on, and we will log the mean pixel of the red channel (a custom function) as well as the percentage of pixels that are 0 (a built-in function) for each image sent to the server. Thus, once launched, the Server exposes two endpoints: - port `6100`: exposes the `metrics` endpoint through [Prometheus python client](https://github.com/prometheus/client_python). From 321061c0ee03e65beff480f23fdf2f296befaa50 Mon Sep 17 00:00:00 2001 From: Robert Shaw <114415538+rsnm2@users.noreply.github.com> Date: Sun, 27 Nov 2022 20:25:00 -0500 Subject: [PATCH 05/17] Update README.md --- examples/logging-prometheus/README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index b060dd34a4..c56ef1a387 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -142,7 +142,8 @@ Run the following to start inference: ```bash python client/client.py ``` -The first argument is the path to the sample image, while the second argument is the port number that matches the inference endpoint of the Server. + +It prints out which image was sent to the server. ## 4. Inspecting the Prometheus/Grafana Stack From fe2998d6f734f6a32a3555c98c237402f00eed30 Mon Sep 17 00:00:00 2001 From: Robert Shaw <114415538+rsnm2@users.noreply.github.com> Date: Sun, 27 Nov 2022 20:25:26 -0500 Subject: [PATCH 06/17] Update README.md --- examples/logging-prometheus/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index c56ef1a387..5a92b6edf3 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -166,7 +166,7 @@ rate(image_classification__0__pipeline_inputs__images__fraction_zeros_count[30s] ``` Toggle from `Table` to `Graph`. You should see the following: -![prometheus-log.png](image/prometheus-log.png) +![prometheus-dashboard.png](image/prometheus-dashboard.png) This graph shows the percentage of 0's. 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zaDVrgzh+YW^~wz#t0evD2rQn`{|jf-$EuJU92SmkFyx@{54rVLv*w$H?*yaEfAXC? zYc0QmV4^kdeKKPhhqqyj)q)j^-7An=l6rj)d6iv~ydOPiJNb>j7WnvQAP*7+wLkOq z73KEN{XxoCmIg$nc*>=DAWa07BeJ}|>&i(p5g z-pMK5;u}rOq%5X0K}5!IGB-l%{2Nxw!-OK?9@b+ZT__eewZW z7T?P~Z%b={CiuO)HDUVSb%p;oUh@C{=({uqbp7wb3I4AWYCm}Jq`G@T90mjo9yy|+ MrgIyo`XJ Date: Sun, 27 Nov 2022 20:27:00 -0500 Subject: [PATCH 09/17] Update README.md --- examples/logging-prometheus/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index 5a92b6edf3..92567ce55e 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -208,4 +208,4 @@ but we have a simple pre-made dashboard for this use case. Click `Dashboard` -> `Import` on the left-hand side bar. You should see an option to upload a file. Upload `grafana/dashboard.json` and save. Then, you should see the following dashboard: -![img.png](images/grafana-dashboard.png) +![img.png](image/grafana-dashboard.png) From a3704444248c0577a57f64c3842b9b190eed318f Mon Sep 17 00:00:00 2001 From: Robert Shaw <114415538+rsnm2@users.noreply.github.com> Date: Sun, 27 Nov 2022 20:30:33 -0500 Subject: [PATCH 10/17] Update README.md --- examples/logging-prometheus/README.md | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index 92567ce55e..aeb5702ef3 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -186,11 +186,17 @@ Setup the Prometheus data source (`Add your first data source` -> `Prometheus`). need to update the `url` section. Since Grafana and Prometheus are running separate docker containers, put we need to put the IP address of the Prometheus container. -Run `docker container ls` to lookup the `name` of the Prometheus container. It should be something like `docker_prometheus_1`. +Run the following to lookup the `name` of your Prometheus container: +``` +docker container ls +>>> CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES +>>> 997521854d84 grafana/grafana:latest "/run.sh" About an hour ago Up About an hour 0.0.0.0:3000->3000/tcp, :::3000->3000/tcp docker_grafana_1 +>>> c611c80ae05e prom/prometheus "/bin/prometheus --c…" About an hour ago Up About an hour 0.0.0.0:9090->9090/tcp, :::9090->9090/tcp docker_prometheus_1 +``` -Run the following to lookup the IP address: +Run the following to lookup the IP address (replace `docker_prometheus_1` with your containers name): ``` -docker inspect -f '{{range.NetworkSettings.Networks}}{{.IPAddress}}{{end}}' container_name_or_id +docker inspect -f '{{range.NetworkSettings.Networks}}{{.IPAddress}}{{end}}' docker_prometheus_1 >>> 172.18.0.2 ``` From abf08a76cf489935447a401f6a12928fa118d927 Mon Sep 17 00:00:00 2001 From: robertgshaw Date: Sun, 27 Nov 2022 20:31:48 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zaDVrgzh+YW^~wz#t0evD2rQn`{|jf-$EuJU92SmkFyx@{54rVLv*w$H?*yaEfAXC? zYc0QmV4^kdeKKPhhqqyj)q)j^-7An=l6rj)d6iv~ydOPiJNb>j7WnvQAP*7+wLkOq z73KEN{XxoCmIg$nc*>=DAWa07BeJ}|>&i(p5g z-pMK5;u}rOq%5X0K}5!IGB-l%{2Nxw!-OK?9@b+ZT__eewZW z7T?P~Z%b={CiuO)HDUVSb%p;oUh@C{=({uqbp7wb3I4AWYCm}Jq`G@T90mjo9yy|+ MrgIyo`XJ Date: Sun, 27 Nov 2022 20:34:11 -0500 Subject: [PATCH 13/17] Update README.md --- examples/logging-prometheus/README.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index aeb5702ef3..9e15d8706b 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -164,12 +164,13 @@ rate(image_classification__0__pipeline_inputs__images__fraction_zeros_sum[30s]) / rate(image_classification__0__pipeline_inputs__images__fraction_zeros_count[30s]) ``` -Toggle from `Table` to `Graph`. You should see the following: + +You should see the following: ![prometheus-dashboard.png](image/prometheus-dashboard.png) -This graph shows the percentage of 0's. A the "corrupted" all black images were -sent to the server in increasing numbers, we can clearly see a spike in the graph, alerting us +This graph shows the percentage of 0's. As the "corrupted" all black images were +sent to the server in increasing probability, we can clearly see a spike in the graph, alerting us that something strange is happening with the provided input. For more details on working with the Prometheus Query Language PromQL, From c413df33c45a337a24dcc7b99db7cda37803839e Mon Sep 17 00:00:00 2001 From: Robert Shaw <114415538+rsnm2@users.noreply.github.com> Date: Sun, 27 Nov 2022 20:38:03 -0500 Subject: [PATCH 14/17] Update README.md --- examples/logging-prometheus/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index 9e15d8706b..ddb1728e39 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -5,7 +5,7 @@ This is a simple example that shows you how to connect DeepSparse Logging to the #### There are four steps: - Configure DeepSparse Logging to log metrics in Prometheus format to a REST endpoint - Point Prometheus to the appropriate endpoint to scape the data at a specified interval -- Run the toy client to perform inference +- Run the client script simulating a data quality/drift issue - Visualize data in Prometheus with dashboarding tool like Grafana ## 0. Setting Up From 6acceb50b62b4fa4c1cd7dfe0a1b631fcc31d398 Mon Sep 17 00:00:00 2001 From: Robert Shaw <114415538+rsnm2@users.noreply.github.com> Date: Sun, 27 Nov 2022 20:41:16 -0500 Subject: [PATCH 15/17] Update README.md --- examples/logging-prometheus/README.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index ddb1728e39..2f31c3709c 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -169,8 +169,9 @@ You should see the following: ![prometheus-dashboard.png](image/prometheus-dashboard.png) -This graph shows the percentage of 0's. As the "corrupted" all black images were -sent to the server in increasing probability, we can clearly see a spike in the graph, alerting us +This graph shows the percentage of 0 pixels in the images sent to the server. +As the "corrupted" all black images were sent to the server in increasing probability, +we can clearly see a spike in the graph, alerting us that something strange is happening with the provided input. For more details on working with the Prometheus Query Language PromQL, @@ -195,7 +196,7 @@ docker container ls >>> c611c80ae05e prom/prometheus "/bin/prometheus --c…" About an hour ago Up About an hour 0.0.0.0:9090->9090/tcp, :::9090->9090/tcp docker_prometheus_1 ``` -Run the following to lookup the IP address (replace `docker_prometheus_1` with your containers name): +Run the following to lookup the IP address (replace `docker_prometheus_1` with your container's name): ``` docker inspect -f '{{range.NetworkSettings.Networks}}{{.IPAddress}}{{end}}' docker_prometheus_1 >>> 172.18.0.2 @@ -210,7 +211,7 @@ Click `Save & Test`. We should get a green check saying "Data Source Is Working" Now you should be ready to create/import your dashboard. Grafana's interface for adding metrics is very intuitive (and you can use PromQL), -but we have a simple pre-made dashboard for this use case. +but we have provided a simple pre-made dashboard for this use case. Click `Dashboard` -> `Import` on the left-hand side bar. You should see an option to upload a file. Upload `grafana/dashboard.json` and save. Then, you should see the following dashboard: From 480896c605b93beeb950fedd8c911464975e75e5 Mon Sep 17 00:00:00 2001 From: robertgshaw Date: Mon, 23 Jan 2023 21:08:43 -0500 Subject: [PATCH 16/17] reran --- examples/logging-prometheus/README.md | 17 +- examples/logging-prometheus/client/client.py | 69 +-- examples/logging-prometheus/custom-fn.py | 1 - .../logging-prometheus/grafana/dashboard.json | 544 +++++++++++------- .../image/grafana-dashboard.png | Bin 49721 -> 67002 bytes 5 files changed, 381 insertions(+), 250 deletions(-) diff --git a/examples/logging-prometheus/README.md b/examples/logging-prometheus/README.md index 2f31c3709c..40a82171a6 100644 --- a/examples/logging-prometheus/README.md +++ b/examples/logging-prometheus/README.md @@ -4,7 +4,7 @@ This is a simple example that shows you how to connect DeepSparse Logging to the #### There are four steps: - Configure DeepSparse Logging to log metrics in Prometheus format to a REST endpoint -- Point Prometheus to the appropriate endpoint to scape the data at a specified interval +- Point Prometheus to the appropriate endpoint to scrape the data at a specified interval - Run the client script simulating a data quality/drift issue - Visualize data in Prometheus with dashboarding tool like Grafana @@ -49,7 +49,7 @@ endpoints: route: /image_classification/predict model: zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/pruned95_quant-none data_logging: - pipeline_inputs.images[0]: # applies to the first image (of the form stage.property[idx]) + pipeline_inputs.images[0]: # applies to the first image (of the form target.property[idx]) - func: fraction_zeros # built-in function frequency: 1 target_loggers: @@ -68,7 +68,7 @@ Thus, once launched, the Server exposes two endpoints: To spin up the Server execute: ``` -deepsparse.server --config server-config.yaml +deepsparse.server --config_file server-config.yaml ``` To validate that metrics are being properly exposed, visit `localhost:6100`. It should contain logs in the specific format meant to be used by the PromQL query language. @@ -174,6 +174,17 @@ As the "corrupted" all black images were sent to the server in increasing probab we can clearly see a spike in the graph, alerting us that something strange is happening with the provided input. +DeepSparse Server also automatically logs prediction latencies for each pipeline stage as well +end-to-end server-side inference time. Add the following query to inspect average latency: + +``` +rate(image_classification__0__prediction_latency__total_inference_sum[30s]) +/ +rate(image_classification__0__prediction_latency__total_inference_count[30s]) +``` + +![prometheus-dashboard-latency.png](image/prometheus-dashboard-latency.png) + For more details on working with the Prometheus Query Language PromQL, see [the official docs](https://prometheus.io/docs/prometheus/latest/querying/basics/). diff --git a/examples/logging-prometheus/client/client.py b/examples/logging-prometheus/client/client.py index 1fc7f7b2d1..10213f74a8 100644 --- a/examples/logging-prometheus/client/client.py +++ b/examples/logging-prometheus/client/client.py @@ -4,49 +4,40 @@ parser.add_argument("--url", type=str, default="http://0.0.0.0:5543/image_classification/predict/from_files") parser.add_argument("--img1_path", type=str, default="client/goldfish.jpeg") parser.add_argument("--img2_path", type=str, default="client/all_black.jpeg") +parser.add_argument("--num_iters", type=int, default=25) +parser.add_argument("--prob_incr", type=float, default=0.1) -MAX_COUNT = 25 -CUTOFF_INCREMENT = 0.1 - -def run_example(url, img1_path, img2_path): - cutoff = 0.0 - - count = 0 - while (cutoff <= 1.0): - img_path = None - if random.uniform(0, 1) < cutoff: - img_path = img2_path - else: - img_path = img1_path - - files = [('request', open(img_path, 'rb'))] - resp = requests.post(url=url, files=files) - print(f"Sent File: {img_path}") +def send_random_img(url, img1_path, img2_path, prob_img2): + img_path = "" + if random.uniform(0, 1) < prob_img2: + img_path = img2_path + else: + img_path = img1_path + + files = [('request', open(img_path, 'rb'))] + resp = requests.post(url=url, files=files) + print(f"Sent File: {img_path}") + +def main(url, img1_path, img2_path, num_iters, prob_incr): + prob_img2 = 0.0 + iters = 0 + increasing = True + + while (increasing or prob_img2 > 0.0): + send_random_img(url, img1_path, img2_path, prob_img2) - if count == MAX_COUNT: - count = 0 - cutoff += CUTOFF_INCREMENT - count += 1 - time.sleep(0.25) + if iters % num_iters == 0 and increasing: + prob_img2 += prob_incr + elif iters % num_iters == 0: + prob_img2 -= prob_incr + iters += 1 + + if prob_img2 >= 1.0: + increasing = False + prob_img2 -= prob_incr - count = 0 - while (cutoff >= 0.): - img_path = None - if random.uniform(0, 1) < cutoff: - img_path = img2_path - else: - img_path = img1_path - - files = [('request', open(img_path, 'rb'))] - resp = requests.post(url=url, files=files) - print(f"Sent File: {img_path}") - - if count == MAX_COUNT: - count = 0 - cutoff -= CUTOFF_INCREMENT - count += 1 time.sleep(0.25) if __name__ == "__main__": args = vars(parser.parse_args()) - run_example(args["url"], args["img1_path"], args["img2_path"]) \ No newline at end of file + main(args["url"], args["img1_path"], args["img2_path"], args["num_iters"], args["prob_incr"]) \ No newline at end of file diff --git a/examples/logging-prometheus/custom-fn.py b/examples/logging-prometheus/custom-fn.py index 3dcd7e8f55..6fe1c1bcc3 100644 --- a/examples/logging-prometheus/custom-fn.py +++ b/examples/logging-prometheus/custom-fn.py @@ -2,5 +2,4 @@ from typing import List def mean_pixel_red(img: np.ndarray): - assert(img.shape[2] == 3) return np.mean(img[:,:,0]) \ No newline at end of file diff --git a/examples/logging-prometheus/grafana/dashboard.json b/examples/logging-prometheus/grafana/dashboard.json index 99145b4c38..2374815e1b 100644 --- a/examples/logging-prometheus/grafana/dashboard.json +++ b/examples/logging-prometheus/grafana/dashboard.json @@ -1,230 +1,360 @@ { - "annotations": { - "list": [ - { - "builtIn": 1, - "datasource": { - "type": "grafana", - "uid": "-- Grafana --" - }, - "enable": true, - "hide": true, - "iconColor": "rgba(0, 211, 255, 1)", - "name": "Annotations & Alerts", - "target": { - "limit": 100, - "matchAny": false, - "tags": [], - "type": "dashboard" - }, - "type": 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