django-influxdb-metrics 0.2.4

A reusable Django app that sends metrics about your project to InfluxDB

A reusable Django app that sends metrics about your project to InfluxDB.

Installation

To get the latest stable release from PyPi

pip install django-influxdb-metrics

To get the latest commit from GitHub

pip install -e git+git://github.com/bitmazk/django-influxdb-metrics.git#egg=influxdb_metrics

Add influxdb_metrics to your INSTALLED_APPS

INSTALLED_APPS = (
    ...,
    'influxdb_metrics',
)

Settings

You need to set the following settings:

INFLUXDB_HOST = 'your.influxdbhost.com'
INFLUXDB_PORT = '8086'
INFLUXDB_USER = 'youruser'
INFLUXDB_PASSWORD = 'yourpassword'
INFLUXDB_DATABASE = 'yourdatabase'

# Optional:
INFLUXDB_SERIES_PREFIX = 'yourservername.'
INFLUXDB_SERIES_POSTFIX = '.whatever'

If you would like to disable sending of metrics (i.e. for local development), you can set:

INFLUXDB_DISABLED = True

Usage

The app comes with several management commands which you should schedule via crontab.

influxdb_get_memory_usage

Collects the total memory of your user, plus the memory and name of the largest process.

You can run it like this:

./manage.py influxdb_get_memory_usage
./manage.py influxdb_get_memory_usage username

If you don’t provide a username, total memory for all users will be collected. This might not be desirable on a shared hosting environment where you can see all user’s processes.

You could schedule it like this:

* * * * * cd /path/to/project/ && /path/to/venv/bin/python /path/to/project/manage.py influxdb_get_memory_usage username > $HOME/mylogs/cron/influxdb-get-memory-usage.log 2>&1

The series created in your InfluxDB will be named <prefix>default.server.memory.usage<postfix> and will have the following columns:

• value: The total memory usage in bytes

• largest_process: Memory usage of the largest process in bytes

• largest_process_name: String representing the largest process name

influxdb_get_cpu_usage

Collects the total %CPU for the given user, plus the %CPU and name of the largest process.

You can run it like this:

./manage.py influxdb_get_cpu_usage
./manage.py influxdb_get_cpu_usage username

If you don’t provide a username, total %CPU for all users will be collected. This might not be desirable on a shared hosting environment where you can see all user’s processes.

You could schedule it like this:

* * * * * cd /path/to/project/ && /path/to/venv/bin/python /path/to/project/manage.py influxdb_get_cpu_usage username > $HOME/mylogs/cron/influxdb-get-cpu-usage.log 2>&1

The series created in your InfluxDB will be named <prefix>default.server.cpu.usage<postfix> and will have the following columns:

• value: The total %CPU

• largest_process: %CPU of the largest process

• largest_process_name: String representing the largest process name

influxdb_get_disk_usage

Collects the total disk usage for the given path.

NOTE: This faciliates the du command with the --block-size flag, therefore it doesn’t work on OSX.

You can run it like this:

./manage.py influxdb_get_disk_usage $HOME

You should give an absolute path to the folder which you want to measure. On a shared hosting environment this would probably be your home folder.

You could schedule it like this:

0 */1 * * * cd /path/to/project/ && /path/to/venv/bin/python /path/to/project/manage.py influxdb_get_disk_usage $HOME > $HOME/mylogs/cron/influxdb-get-disk-usage.log 2>&1

The series created in your InfluxDB will be named <prefix>default.server.disk.usage<postfix> and will have the following columns:

• value: The total memory usage in bytes

influxdb_get_postgresql_size

Collects the total disk usage for the given database.

You can run it like this:

./manage.py influxdb_get_postgresql_size db_role db_name

You shoudl provide role and name for the database you want to measure. Make sure that you have a .pgpass file in place so that you don’t need to enter a password for this user.

You could schedule it like this:

0 */1 * * * cd /path/to/project/ && /path/to/venv/bin/python /path/to/project/manage.py influxdb_get_postgresql_size db_role db_name > $HOME/mylogs/cron/influxdb-get-postgresql-size.log 2>&1

The series created in your InfluxDB will be named <prefix>default.server.postgresql.size<postfix> and will have the following columns:

• value: The total database size in bytes

InfluxDBEmailBackend

If you would like to track tne number of emails sent, you can set your EMAIL_BACKEND:

EMAIL_BACKEND = 'influxdb_metrics.email.InfluxDBEmailBackend'

When the setting is set, metrics will be sent every time you run .manage.py send_mail.

The series created in your InfluxDB will be named <prefix>default.django.email.sent<postfix> and will have the following columns:

• value: The number of emails sent

InfluxDBRequestMiddleware

If you would like to track the number and speed of all requests, you can add the InfluxDBRequestMiddleware at the top of your MIDDLEWARE_CLASSES:

MIDDLEWARE_CLASSES = [
    'influxdb_metrics.middleware.InfluxDBRequestMiddleware',
    ...
]

The series created in your InfluxDB will be named <prefix>default.django.request<postfix> and will have the following columns:

• value: The request time in milliseconds.

• is_ajax: true if it was an AJAX request, otherwise false

• is_authenticated: true if user was authenticated, otherwise false

• is_staff: true if user was a staff user, otherwise false

• is_superuser: true user was a superuser, otherwise false

• method: The request method (GET or POST)

• module: The python module that handled the request

• view: The view class or function that handled the request

• referer: The full URL from request.META[‘HTTP_REFERER’]

• referer_tld: The top level domain of the referer. It tries to be smart

  and regards google.co.uk as a top level domain (instead of co.uk)

• full_path: The full path that was requested

• path: The path without GET params that was requested

If you have a highly frequented site, this table could get big really quick. You should make sure to create a shard with a low retention time for this series (i.e. 7d) and add a continuous query to downsample the data into hourly/daily averages. When doing that, you will obviously lose the detailed information like referer and referer_tld but it might make sense to create a second continuous query to count and downsample at least the referer_tld values.

NOTE: I don’t know what impact this has on overall request time or how much stress this would put on the InfluxDB server if you get thousands of requests. It would probably wise to consider something like statsd to aggregate the requests first and then send them to InfluxDB in bulk.

Tracking User Count

This app’s models.py contains a post_save and a post_delete handler which will detect when a user is created or deleted.

It will create three series in your InfluxDB:

The first one will be named <prefix>default.django.auth.user.create<postfix> and will have the following columns:

• value: 1

The second one will be named <prefix>default.django.auth.user.delete<postfix> and will have the following columns:

• value: 1

The third one will be named <prefix>default.django.auth.user.count<postfix> and will have the following columns:

• value: The total number of users in the database

Tracking User Logins

This app’s models.py contains a handler for the user_logged_in signal.

The series created in your InfluxDB will be named <prefix>default.django.auth.user.login<postfix> and will have the following columns:

• value: 1

Making Queries

If you need to get data out of your InfluxDB instance, you can easily do it like so:

from influxdb_metrics.utils import query
query('select * from series.name', time_precision='s', chunked=False)

The method declaration is the same as the one in InfluxDBClient.query(). This wrapper simply instanciates a client based on your settings.

Contribute

If you want to contribute to this project, please perform the following steps

# Fork this repository
# Clone your fork
mkvirtualenv -p python2.7 django-influxdb-metrics
make develop

git co -b feature_branch master
# Implement your feature and tests
git add . && git commit
git push -u origin feature_branch
# Send us a pull request for your feature branch