==========
grafanalib
.. image:: https://circleci.com/gh/weaveworks/grafanalib.svg?style=shield
:target: https://circleci.com/gh/weaveworks/grafanalib
Do you like Grafana <http://grafana.org/>_ but wish you could version your
dashboard configuration? Do you find yourself repeating common patterns? If
so, grafanalib is for you.
grafanalib lets you generate Grafana dashboards from simple Python scripts.
Writing dashboards
The following will configure a dashboard with a single row, with one QPS graph
broken down by status code and another latency graph showing median and 99th
percentile latency:
.. code-block:: python
from grafanalib.core import *
dashboard = Dashboard(
title="Frontend Stats",
rows=[
Row(panels=[
Graph(
title="Frontend QPS",
dataSource='My Prometheus',
targets=[
Target(
expr='sum(irate(nginx_http_requests_total{job="default/frontend",status=~"1.."}[1m]))',
legendFormat="1xx",
refId='A',
),
Target(
expr='sum(irate(nginx_http_requests_total{job="default/frontend",status=~"2.."}[1m]))',
legendFormat="2xx",
refId='B',
),
Target(
expr='sum(irate(nginx_http_requests_total{job="default/frontend",status=~"3.."}[1m]))',
legendFormat="3xx",
refId='C',
),
Target(
expr='sum(irate(nginx_http_requests_total{job="default/frontend",status=~"4.."}[1m]))',
legendFormat="4xx",
refId='D',
),
Target(
expr='sum(irate(nginx_http_requests_total{job="default/frontend",status=~"5.."}[1m]))',
legendFormat="5xx",
refId='E',
),
],
yAxes=YAxes(
YAxis(format=OPS_FORMAT),
YAxis(format=SHORT_FORMAT),
),
alert=Alert(
name="Too many 500s on Nginx",
message="More than 5 QPS of 500s on Nginx for 5 minutes",
alertConditions=[
AlertCondition(
Target(
expr='sum(irate(nginx_http_requests_total{job="default/frontend",status=~"5.."}[1m]))',
legendFormat="5xx",
refId='A',
),
timeRange=TimeRange("5m", "now"),
evaluator=GreaterThan(5),
operator=OP_AND,
reducerType=RTYPE_SUM,
),
],
)
),
Graph(
title="Frontend latency",
dataSource='My Prometheus',
targets=[
Target(
expr='histogram_quantile(0.5, sum(irate(nginx_http_request_duration_seconds_bucket{job="default/frontend"}[1m])) by (le))',
legendFormat="0.5 quantile",
refId='A',
),
Target(
expr='histogram_quantile(0.99, sum(irate(nginx_http_request_duration_seconds_bucket{job="default/frontend"}[1m])) by (le))',
legendFormat="0.99 quantile",
refId='B',
),
],
yAxes=single_y_axis(format=SECONDS_FORMAT),
),
]),
],
).auto_panel_ids()
There is a fair bit of repetition here, but once you figure out what works for
your needs, you can factor that out.
See our Weave-specific customizations <grafanalib/weave.py>_ for inspiration.
Generating dashboards
If you save the above as frontend.dashboard.py (the suffix must be
.dashboard.py), you can then generate the JSON dashboard with:
.. code-block:: console
$ generate-dashboard -o frontend.json frontend.dashboard.py
Installation
grafanalib is just a Python package, so:
.. code-block:: console
$ pip install grafanalib
Support
This library is in its very early stages. We'll probably make changes that
break backwards compatibility, although we'll try hard not to.
grafanalib works with Python 2.7, 3.4, 3.5, and 3.6.
Developing
If you're working on the project, and need to build from source, it's done as follows:
.. code-block:: console
$ virtualenv .env
$ . ./.env/bin/activate
$ pip install -e .
gfdatasource
This module also provides a script and docker image which can configure grafana
with new sources, or enable app plugins.
The script answers the --help with full usage information, but basic
invocation looks like this:
.. code-block:: console
$ --grafana-url http://grafana. datasource --data-source-url http://datasource
$ --grafana-url http://grafana. app --id my-plugin
Getting Help
If you have any questions about, feedback for or problems with grafanalib:
- Invite yourself to the
Weave Users Slack <https://slack.weave.works/>_. - Ask a question on the
#general <https://weave-community.slack.com/messages/general/>_ slack channel. File an issue <https://github.com/weaveworks/grafanalib/issues/new>_.
Your feedback is always welcome!