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https://github.com/skar404/prometheus-sanic

Actual forke for sanic-prometheus. Prometheus metrics for Sanic, an async python web server
https://github.com/skar404/prometheus-sanic

monitoring pip prometheus python python-library sanic

Last synced: 30 days ago
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Actual forke for sanic-prometheus. Prometheus metrics for Sanic, an async python web server

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README 

        
Sanic prometheus metrics

=========================

|Build Status| |PyPI| |PyPI version|



After googling for a while I didn't find a library that would enable some `prometheus `_ metrics for `Sanic `_-based apps, so I had to write one. It makes adding monitoring to your Sanic app super easy, just add one line to your code (ok, two if you count import :) and point Prometheus to a newly appeared `/metrics` endpoint.



Installation and enabling monitoring

-------------------------------------



Installatio:



.. code:: bash



  pip install prometheus-sanic



Easy-peasy:



.. code:: python



  from sanic import Sanic

  from prometheus_sanic import monitor



  app = Sanic()

  ...



  if __name__ == "__main__":

    monitor(app).expose_endpoint() # adds /metrics endpoint to your Sanic server

    app.run(host="0.0.0.0", port=8000)



Actually, there're two ways to run monitoring:



1. The one you've seen above, ``monitor(app).expose_endpoint()``. 

   It just adds a new ``route`` to your Sanic app, exposing ``/metrics`` endpoint

   on the same host and port your Sanic server runs. It might be useful if you run your

   app in a container and you do not want to expose different ports for metrics and everything else.

   You can customize the ``/metrics`` endpoint by passing the ``metrics_path`` keyword argument:

   ``monitor(app, metrics_path='/my_metrics_path').expose_endpoint()``.

2. ``monitor(app).start_server(addr=..., port=...)``.

   Runs a HTTP server on given address and port and exposes ``/metrics`` endpoint on it.

   This might be useful if you want to restrict access to your ``/metrics`` endpoint using some

   firewall rules



Versions compatibility

----------------------



* ☑︎ use **0.1.0** for Sanic <= 0.4.1

* ☑︎ use **0.1.3** for Sanic >= 0.5.0

* ☑︎ use >= **0.1.4** if you need multiprocessing support

* ☑︎ use **0.1.6** if you have to use `promtheus-client` <= 0.4.2

* ☑︎ use **0.1.8** with `prometheus-client` >= 0.5.0

* ☑︎ use **0.2.0** with `prometheus-client` >= 0.7.1 and Sanic >= 18.12



Exposed metrics

-----------------



At the moment ``prometheus-sanic`` provides four metrics:



* **sanic_request_count** - total number of requests (labels: *method*, *endpoint*, *status*) [`counter `_]

* **sanic_request_latency_sec** - request latency in seconds (labels: *method*, *endpoint*) [`histogram `_]

* **sanic_mem_rss_bytes** - resident memory used by the process (in bytes) [`gauge `_]

* **sanic_mem_rss_perc** - a percent of total physical memory used by the process running Sanic [`gauge `_]

  

Labels

-----------------



* **method**: a HTTP method (i.e. GET/POST/DELETE/etc)

* **endpoint**: just a string, a name identifying a point handling a group of requests. By default it's just the first element of the relative path of the URL being called (i.e. for http://myhost/a/b/c you'll end up having ``/a`` as your endpoint). It is quite configurable, in fact it's up you what's gonna get to the ``endpoint`` label (see ``help(prometheus_sanic.monitor)`` for more details)

* **http_status**: a HTTP status code



Multiprocess mode

-----------------



Sanic allows to launch multiple worker processes to utilise parallelisation, which is great but makes metrics collection much trickier (`read more `_) and introduces some limitations. 



In order to collect metrics from multiple workers, create a directory and point a ``prometheus_multiproc_dir`` environment variable to it. Make sure the directory is empty before you launch your service::



     % rm -rf /path/to/your/directory/*

     % env prometheus_multiproc_dir=/path/to/your/directory python your_sanic_app.py



Unfortunately you can not use ``monitor(app).start_server(addr=..., port=...)`` in multiprocess mode as it exposes a prometheus endpoint from a newly created process.



Configuration

-----------------



Best you can do is::



     % ipython

     In [1]: from prometheus_sanic import monitor

     In [2]: help(monitor)



Prometheus quering examples:

-----------------------------



* *Average latency over last 30 minutes*::



    rate(sanic_request_latency_sec_sum{endpoint='/your-endpoint'}[30m]) / 

    rate(sanic_request_latency_sec_count{endpoint='/your-endpoint'}[30m])



* *95th percentile of request latency*:: 



    histogram_quantile(0.95, sum(rate(sanic_request_latency_sec_bucket[5m])) by (le))



* *Physical memory usage percent over last 10 minutes*::



    rate(sanic_mem_rss_perc[10m])



.. |Build Status| image:: https://github.com/skar404/prometheus-sanic/workflows/Tests/badge.svg

   :target: https://github.com/skar404/prometheus-sanic/actions/

.. |PyPI| image:: https://img.shields.io/pypi/v/prometheus-sanic.svg

   :target: https://pypi.python.org/pypi/prometheus-sanic/

.. |PyPI version| image:: https://img.shields.io/pypi/pyversions/prometheus-sanic.svg

   :target: https://pypi.python.org/pypi/prometheus-sanic/