openstack-manuals/doc/admin-guide-cloud/source/dashboard_sessions.rst

Set up session storage for the dashboard

The dashboard uses Django sessions framework to handle user session data. However, you can use any available session back end. You customize the session back end through the SESSION_ENGINE setting in your local_settings file (on Fedora/RHEL/ CentOS: /etc/openstack-dashboard/local_settings, on Ubuntu and Debian: /etc/openstack-dashboard/local_settings.py, and on openSUSE: /srv/www/openstack-dashboard/openstack_dashboard/local/local_settings.py).

The following sections describe the pros and cons of each option as it pertains to deploying the dashboard.

Local memory cache

Local memory storage is the quickest and easiest session back end to set up, as it has no external dependencies whatsoever. It has the following significant drawbacks:

• No shared storage across processes or workers.
• No persistence after a process terminates.

The local memory back end is enabled as the default for Horizon solely because it has no dependencies. It is not recommended for production use, or even for serious development work. Enabled by:

SESSION_ENGINE = 'django.contrib.sessions.backends.cache'
CACHES = {
  'default' : {
    'BACKEND': 'django.core.cache.backends.locmem.LocMemCache'
  }
}

You can use applications such as Memcached or Redis for external caching. These applications offer persistence and shared storage and are useful for small-scale deployments and development.

Memcached

Memcached is a high-performance and distributed memory object caching system providing in-memory key-value store for small chunks of arbitrary data.

Requirements:

• Memcached service running and accessible.
• Python module python-memcached installed.

Enabled by:

SESSION_ENGINE = 'django.contrib.sessions.backends.cache'
CACHES = {
  'default': {
    'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
    'LOCATION': 'my_memcached_host:11211',
  }
}

Redis

Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server.

Requirements:

• Redis service running and accessible.
• Python modules redis and django-redis installed.

Enabled by:

SESSION_ENGINE = 'django.contrib.sessions.backends.cache'
CACHES = {
    "default": {
        "BACKEND": "redis_cache.cache.RedisCache",
        "LOCATION": "127.0.0.1:6379:1",
        "OPTIONS": {
            "CLIENT_CLASS": "redis_cache.client.DefaultClient",
        }
    }
}

Initialize and configure the database

Database-backed sessions are scalable, persistent, and can be made high-concurrency and highly-available.

However, database-backed sessions are one of the slower session storages and incur a high overhead under heavy usage. Proper configuration of your database deployment can also be a substantial undertaking and is far beyond the scope of this documentation.

1. Start the mysql command-line client:

   $ mysql -u root -p

2. Enter the MySQL root user's password when prompted.

3. To configure the MySQL database, create the dash database:

   mysql> CREATE DATABASE dash;

4. Create a MySQL user for the newly created dash database that has full control of the database. Replace DASH_DBPASS with a password for the new user:

   mysql> GRANT ALL PRIVILEGES ON dash.* TO 'dash'@'%' IDENTIFIED BY 'DASH_DBPASS';
   mysql> GRANT ALL PRIVILEGES ON dash.* TO 'dash'@'localhost' IDENTIFIED BY 'DASH_DBPASS';

5. Enter quit at the mysql> prompt to exit MySQL.

6. In the local_settings file (on Fedora/RHEL/CentOS: /etc/openstack-dashboard/local_settings, on Ubuntu/Debian: /etc/openstack-dashboard/local_settings.py, and on openSUSE: /srv/www/openstack-dashboard/openstack_dashboard/local/local_settings.py), change these options:

   SESSION_ENGINE = 'django.contrib.sessions.backends.db'
   DATABASES = {
       'default': {
           # Database configuration here
           'ENGINE': 'django.db.backends.mysql',
           'NAME': 'dash',
           'USER': 'dash',
           'PASSWORD': 'DASH_DBPASS',
           'HOST': 'localhost',
           'default-character-set': 'utf8'
       }
   }

7. After configuring the local_settings file as shown, you can run the manage.py syncdb command to populate this newly created database:

   # /usr/share/openstack-dashboard/manage.py syncdb

   Note on openSUSE the path is /srv/www/openstack-dashboard/manage.py.

8. The following output is returned:

   Installing custom SQL ...
   Installing indexes ...
   DEBUG:django.db.backends:(0.008) CREATE INDEX `django_session_c25c2c28` ON `django_session` (`expire_date`);; args=()
   No fixtures found.

9. To avoid a warning when you restart Apache on Ubuntu, create a blackhole directory in the dashboard directory, as follows:

   # mkdir -p /var/lib/dash/.blackhole

10. Restart and refresh Apache:

    On Ubuntu:

    # /etc/init.d/apache2 restart

    On Fedora/RHEL/CentOS:

    # service httpd restart
    # service apache2 restart

    On openSUSE:

    # systemctl restart apache2.service

11. On Ubuntu, restart the nova-api service to ensure that the API server can connect to the dashboard without error:

    # service nova-api restart

Cached database

To mitigate the performance issues of database queries, you can use the Django cached_db session back end, which utilizes both your database and caching infrastructure to perform write-through caching and efficient retrieval.

Enable this hybrid setting by configuring both your database and cache, as discussed previously. Then, set the following value:

SESSION_ENGINE = "django.contrib.sessions.backends.cached_db"

Cookies

If you use Django 1.4 or later, the signed_cookies back end avoids server load and scaling problems.

This back end stores session data in a cookie, which is stored by the user's browser. The back end uses a cryptographic signing technique to ensure session data is not tampered with during transport. This is not the same as encryption; session data is still readable by an attacker.

The pros of this engine are that it requires no additional dependencies or infrastructure overhead, and it scales indefinitely as long as the quantity of session data being stored fits into a normal cookie.

The biggest downside is that it places session data into storage on the user's machine and transports it over the wire. It also limits the quantity of session data that can be stored.

See the Django cookie-based sessions documentation.