Profiling toolbox

Profiling and metrics toolbox.

Contains many features:

Timer API, very much alike symfony/stopwatch with time and memory consumption measurement. Timers can be started within a timer tree which allows to have a multi-dimensional view of timers.
Prometheus compatible various metrics collection, counters, gauges, summaries and histograms. Those metrics can be exposed via a Promotheus compatible scrapping endpoint.
Integration with symfony/stopwatch for Symfony web profiler when in development mode.

Timers uses the monotonic high resolution timer if available using the PHP \hrtime() function for timings, which yields more precision and is resilient to system clock changes in opposition to \microtime() Using \hrtime() function makes this API being suitable for running discretly in production.

Setup

Installation

Simply run:

composer require makinacorpus/profiling

For registering the Symfony bundle, add to your config/bundles.php:

return [
    // ... Your other bundles.
    MakinaCorpus\Profiling\Bridge\Symfony\ProfilingBundle::class => ['all' => true],
];

Enable it by setting this environment variable:

PROFILING_ENABLED=1

Enable prometheus support can be done as well:

PROFILING_PROMOTHEUS_ENABLED=1

Then copy the src/Bridge/Symfony/Resources/packages/profiling.yaml in this package in the config/packages/ directory. You may read it and modify following your needs. All configuration options are documented within the sample configuration file itself.

Storage configuration

Default storage is a PostgreSQL database implementation that uses makinacorpus/query-builder for writing SQL queries.

It can create automatically the missing tables at runtime, although this unperformant and disabled per default. In order to allow automatic table creation, you can set the PROFILING_PROMETHEUS_SCHEMA_AUTOCREATE=1 environment variable.

Recommended method is to run the profiling:prometheus:create-schema console command at least once:

php bin/console profiling:prometheus:create-schema

Usage

Important notes:

For each incomming request, the must be one and only one MakinaCorpus\Profiling\Profiler instance.
By "incomming request", we mean a single workload, which in the context of a message bus consumer can be a single message processing.

Timers

Basic usage

Here is a code sample:

use MakinaCorpus\Profiling\Profiler\DefaultProfiler;

// First, create a profiler. If you are using a framework, you should
// inject in your dependency injection container a global instance.
$profiler = DefaultProfiler();

// Start a new top-level timer, which has no parent.
// Please note that name is optional, it's purely informational.
// A unique identifier will be generated if you don't pass one.
// You need a name later if you wish to stop one timer without
// stopping all the others.
$timer = $profiler->start('doing-something');

// Each time you start a new top-level profiler, it is decoupled from
// the other one, they won't interact with each-ohter.
$otherTimer = $profiler->start('unrelated-other-something');

// From your first timer, you can start children.
$timer1 = $timer->start('1');
$timer2 = $timer->start('2');

// Then subchildren.
$timer21 = $timer2->start('2.1');
$timer22 = $timer2->start('2.2');

// From a parent timer, you can choose stopping only one child.
// You can stop the child directly as well.
// The following two lines are equivalent gives a strictly identical result.
$timer2 = $timer2->stop('2.2');
$timer22->stop();

echo $timer2->isRunning(); // true
echo $timer21->isRunning(); // true
echo $timer22->isRunning(); // false

// When you close a timer, all the children will be stopped as well.
$timer2 = $timer->stop();

echo $timer2->isRunning(); // false
echo $timer21->isRunning(); // false
echo $timer22->isRunning(); // false

// You can fetch timings.
// All given numbers are float, reprensenting a number of milliseconds.
echo $timer2->getElapsedTime(); // 2.2124548
echo $timer21->getElapsedTime(); // 1.88878889
echo $timer22->getElapsedTime(); // 0.98897574

// You can fully reset the global state, which will also free the
// memory it took.
// This is precious for long running deamons, such as message bus
// consumers which will remain alive for hours.
$profiler->flush();

Timer advanced usage

There are many methods on the MakinaCorpus\Profiling\Timer interface, all are documented.

Timer trace handlers

Timer trace handlers are components that listen to all timers being emited, then can log information. A few handlers are provided by default:

MakinaCorpus\Profiling\Timer\Handler\SentryHandler (sentry) can send your timers to a Sentry instance.
MakinaCorpus\Profiling\Timer\Handler\StoreHandler (store) can send your timers to a local storage implementation. Only one implementation exist as of now, which sends data to an SQL database table.
MakinaCorpus\Profiling\Timer\Handler\StreamHandler (file) sends your timers into a log file, each timer gets a line.
MakinaCorpus\Profiling\Timer\Handler\SymfonyStopwatchHandler (stopwatch) sends the timers into the symfony/stopwatch component. This is useful when the web profiler debug toolbar is installed, in development mode.

Handlers can be configured to accept timers from all channels, some channels, or all channels but some channels.

See the example configuration file for more information about handler configuration.

Prometheus metrics

Setup

First, enable it using an environment variable:

PROFILING_PROMOTHEUS_ENABLED=1

Then compute a random access token, with any method of your choice, then set it into your environments variables:

PROFILING_PROMETHEUS_ACCESS_TOKEN: SuperSecretToken

In order to setup the prometheus HTTP endpoint, add into config/routes.yaml:

prometheus:
    resource: "@ProfilingBundle/Resources/config/routes.prometheus.yaml"
    prefix: /prometheus

Then for fetching metrics, simply hit the following URL:

curl http://yoursite/prometheus/metrics/?access_token=SuperSecretToken

Also, please note that if you configured some firewalls, you probably need to put the ^/prometheus/ path into a non-secured firewall.

Default configuration simply works, aside for the driver that needs to be configured. Default is in_memory which means it simply stores nothing.

Define your own metrics

Each sample must be defined in the schema configuration section. If a sample is not defined in this file, then it will simply be a no-op if you attempt collecting it.

Edit your config/packages/profiling.yaml file:

profiling:
    prometheus:
        #
        # Namespace name will prefix all sample names when exported to
        # Prometheus. For example, if you define "some_counter", the final
        # sample name will be "symfony_some_counter".
        #
        namespace: symfony

        #
        # For all sample type, you may set the "labels" entry.
        #
        # Labels are some kind tags, whose values are required when
        # measuring. This is important, please read Prometheus documentation
        # for more information.
        #
        # In all cases, you always should add the [action, method] which then
        # should be populated using respectively the current route name and
        # the HTTP method. There are of course some use cases where you may
        # not need it.
        #
        schema:

            # Gauge is a float value, no more no less, each new measure
            # will erase the existing value.
            some_gauge:
                type: gauge
                help: This is some gauge
                labels: [action, method, foo, bar]

            # A counter is a static value that gets incremented over time.
            # It never gets reseted, always incremented.
            # If you drop the data from your database, the next Prometheus
            # scrap will see the value going down and give invalid data,
            # but as time will pass, data will get eventually consistent
            # soon enough.
            some_counter:
                type: counter
                help: Some counter
                labels: [action, method, foo]

            # Summary is statistical distribution analysis of some value using
            # percentiles. Summaries are computed on the client side (ie.
            # your site) in opposition to histograms which are computed on
            # the service (ie. in Prometheus).
            # You may or may not define quantiles, in this example we define
            # the defaults being applied if none providen.
            some_summary:
                type: summary
                help: Some summary
                labels: [action, method, foo]
                quantiles: [0.01, 0.05, 0.5, 0.95, 0.99]

            # Histogram is a statistical distribution analysis of some value
            # using buckets. Buckets are supposed to be pre-defined in this
            # schema. Histograms are computed in the server side (ie. in
            # Prometheus) in opposition to summaries which are computed on
            # the client side (ie. your site).
            # You may or may not define buckets, in this example we define
            # the defaults being applied if none providen.
            # It is strongly recommended, for histogram usage, that you define
            # explicitely your own buckets depending on expected values for
            # each sample definition.
            some_histogram:
                type: histogram
                help: request durations in milliseconds
                labels: [action, method, foo]
                buckets: [0.005, 0.01, 0.025, 0.05, 0.075, 0.1, 0.25, 0.5, 0.75, 1.0, 2.5, 5.0, 7.5, 10.0]

Then, at the point in code where you need to profile, inject the MakinaCorpus\Profiling\Profiler service and use it.

Gauge

Use the gauge() method:

\assert($profiler instanceof \MakinaCorpus\Profiling\Profiler);

$timer = $profiler->gauge(
    // Name in your schema.
    'some_gauge',
    // Label values, considering you kept "action" and "method"
    // in the (action, method, foo, bar) list:
    [
        $profiler->getContext()->route,
        $profiler->getContext()->method,
        'some_value',
        'some_other_value',
    ],
    // Arbitrary value you actually measure.
    123.456
);

Counter

Use the counter() method:

\assert($profiler instanceof \MakinaCorpus\Profiling\Profiler);

$timer = $profiler->counter(
    // Name in your schema.
    'some_counter',
    // Label values, considering you kept "action" and "method"
    // in the (action, method, foo) list:
    [
        $profiler->getContext()->route,
        $profiler->getContext()->method,
        'some_value',
    ],
    // Arbitrary increment value you actually measure.
    // You can omit this parameter and increment will be 1.
    3,
);

Summary

Use the summary method in conjonction with a timer:

\assert($profiler instanceof \MakinaCorpus\Profiling\Profiler);

try {
    $timer = $profiler->timer();

    // Something happens, then...
} finally {
    if ($timer) {
        $duration = $timer->getElapsedTime();

        $profiler->summary(
            'something_duration_msec',
            // Label values, considering you kept "action" and "method"
            // in the (action, method, foo) list:
            [
                $profiler->getContext()->route,
                $profiler->getContext()->method,
                'some_value',
            ],
            // Arbitrary value you actually measure.
            $duration,
        );
    }
}

Of course, you could measure something else than a duration, any value which yield some meanings to you can be added to summaries.

Important note: histogram are much more performant to use than summaries in both output rendering and storage. Avoid summaries when you know in advance expected values span.

Histogram

Use the histogram method in conjonction with a timer:

\assert($profiler instanceof \MakinaCorpus\Profiling\Profiler);

try {
    $timer = $profiler->timer();

    // Something happens, then...
} finally {
    if ($timer) {
        $duration = $timer->getElapsedTime();

        $profiler->histogram(
            'something_duration_msec',
            // Label values, considering you kept "action" and "method"
            // in the (action, method, foo) list:
            [
                $profiler->getContext()->route,
                $profiler->getContext()->method,
                'some_value',
            ],
            // Arbitrary value you actually measure.
            $duration,
        );
    }
}

Of course, you could measure something else than a duration, any value which yield some meanings to you can be added to summaries.

Important note: histogram are much more performant to use than summaries in both output rendering and storage. Always prefer histogram over summary when when you know in advance expected values span.

Exposed metrics

HTTP requests

NAMESPACE_http_exception_total (counter), {action: ROUTE, method: HTTP_METHOD, type: EXCEPTION_CLASS}
NAMESPACE_http_request_duration_msec (summary), {action: ROUTE, method: HTTP_METHOD, status: HTTP_STATUS_CODE}
NAMESPACE_http_request_total (counter), {action: ROUTE, method: HTTP_METHOD}
NAMESPACE_http_response_total (counter), {action: ROUTE, method: HTTP_METHOD, status: HTTP_STATUS_CODE}
NAMESPACE_instance_name (gauge), {instance_name: HOSTNAME}

Console commands

NAMESPACE_console_command_total (counter), {action: COMMAND_NAME}
NAMESPACE_console_duration_msec (summary), {action: COMMAND_NAME, method: "command", status: EXIT_STATUS_CODE}
NAMESPACE_console_exception_total (counter), {action: COMMAND_NAME, method: "command", type: EXCEPTION_CLASS}
NAMESPACE_console_status_total (counter), {action: COMMAND_NAME, method: "command", status: EXIT_STATUS_CODE}

Messenger

Not implemented yet. It will probably be:

NAMESPACE_message_consumed_total (counter), {action: MESSAGE_CLASS, method: "message"}
NAMESPACE_message_duration_msec (summary), {action: MESSAGE_CLASS, method: "message"}
NAMESPACE_message_exception_total (counter), {action: MESSAGE_CLASS, method: "message", type: EXCEPTION_CLASS}

Monolog

Not implemented yet. It will probably be:

NAMESPACE_monolog_message_total (counter), {action: ROUTE|COMMAND_NAME|MESSAGE_CLASS, method: "message"|"command"|HTTP_METHOD, severity: MONOLOG_LEVEL, channel: MONOLOG_CHANNEL}

System information

If you don't have system monitoring, this bundle can collect a few system information samples.

Please see complete documentation in the src/Bridge/Symfony/Resources/config/packages/profiling.yaml file.

CPU load average samples:

NAMESPACE_sys_load_avg (gauge), {span: INT} - value as a fractional number, for the span last minutes.

Memory usage samples:

NAMESPACE_sys_mem_total (gauge) - value in bytes.
NAMESPACE_sys_mem_free (gauge) - value in bytes.
NAMESPACE_sys_mem_used (gauge) - value in bytes.
NAMESPACE_sys_mem_available (gauge) - value in bytes.
NAMESPACE_sys_mem_buffers (gauge) - value in bytes.
NAMESPACE_sys_mem_cached (gauge) - value in bytes.
NAMESPACE_sys_mem_swap_total (gauge) - value in bytes.
NAMESPACE_sys_mem_swap_free (gauge) - value in bytes.
NAMESPACE_sys_mem_swap_used (gauge) - value in bytes.

Disk usage samples:

NAMESPACE_sys_disk_total (gauge), {name: NAME} - value in bytes.
NAMESPACE_sys_disk_free (gauge), {name: NAME} - value in bytes.
NAMESPACE_sys_disk_used (gauge), {name: NAME} - value in bytes.

Per default, if you don't configure any disk, the current project directory mount point is targeted, and NAME is app.

Warning: because the probes are only collecting data when a request happen you can chose to run the profiling:prometheus:sys-info console command to run as a cron job for collecting system information regularily.

Inject profiler into your services

When working in a Symfony project, the recommended way for registering the profiler onto a service is the following:

namespace MyVendor\MyApp\SomeNamespace;

use MakinaCorpus\Profiling\ProfilerAware;
use MakinaCorpus\Profiling\ProfilerAwareTrait;

/**
 * Implementing the interface allow autoconfiguration.
 */
class SomeService implements ProfilerAware
{
    use ProfilerAwareTrait;
}

By using the \MakinaCorpus\Profiling\ProfilerAwareTrait you allow your code to be resilient in case of misinitialisation:

If the autoconfiguration failed, it will create a default null instance doing nothing, which will have a near-to-zero performance impact.
If the bundle is deactivated, it will create a default null instance doing nothing, which will have a near-to-zero performance impact.

You can then use the profiler:

namespace MyVendor\MyApp\SomeNamespace;

use MakinaCorpus\Profiling\ProfilerAware;
use MakinaCorpus\Profiling\ProfilerAwareTrait;

/**
 * Implementing the interface allows autoconfiguration.
 */
class SomeService implements ProfilerAware
{
    /**
     * Using the trait provides a default working implementation.
     */
    use ProfilerAwareTrait;

    public function doSomething()
    {
        $timer = $this->getProfiler()->start('something');

        try {
            $timer->start('something-else');
            $this->doSomethingElse();
            $timer->stop('something-else');

            $timer->start('something-other');
            $this->doSomethingElse();
            $timer->stop('something-other');

            $timer->start('something-that-fails');
            throw new \Exception("Oups, something bad happened.");
            $timer->stop('something-that-fails');

        } finally {
            // We do heavily recommend that use the try/finally
            // pattern to ensure that exceptions will not betry
            // your timers.
            // The last stop() call within the try block will never
            // be called, by stopping the parent timer here, it
            // stops the child as well.
            $timer->stop();
        }
    }
}

And that's pretty much it.

Memory usage

The timer class also measure memory usage, but beware that those results will be biased by this API itself consuming memory.

CLI killswitch

If you are working in CLI, and with to disable profiling for long running tasks or migration batches, simply add the PROFILING_ENABLE=0 environment variable in your command line.

This will not completely disable the bundle, this is a soft-disable and will only prevent profiliers from being created during this runtime, for example:

PROFILING_ENABLE=0 bin/console app:some-very-long-batch

Roadmap

Allow configuration of formatter in stream handler.
Implement Redis storage for prometheus metrics.
Merge Metrics and Profiler interfaces/classes.
Plug timers in prometheus summary and histogram.
Prometheus doctrine SQL query count metrics.
Prometheus messenger metrics.
Prometheus monolog metrics.
Prometheus response size metrics.
Prometheus unexpected metrics log into monolog.
Purge console command with date.
View console command.
Write documentation site.

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README.md

README.md

Profiling toolbox

Setup

Installation

Storage configuration

Usage

Timers

Basic usage

Timer advanced usage

Timer trace handlers

Prometheus metrics

Setup

Define your own metrics

Gauge

Counter

Summary

Histogram

Exposed metrics

HTTP requests

Console commands

Messenger

Monolog

System information

Inject profiler into your services

Memory usage

CLI killswitch

Roadmap

Files

README.md

Latest commit

History

README.md

File metadata and controls

Profiling toolbox

Setup

Installation

Storage configuration

Usage

Timers

Basic usage

Timer advanced usage

Timer trace handlers

Prometheus metrics

Setup

Define your own metrics

Gauge

Counter

Summary

Histogram

Exposed metrics

HTTP requests

Console commands

Messenger

Monolog

System information

Inject profiler into your services

Memory usage

CLI killswitch

Roadmap