Introducing Admin User Guide dashboard content to the Cloud Admin Guide as a part of the reorganisation goal. This patch is the first step in creating a new Dashboard section for Admin Users in the Cloud Admin Guide, as disucssed in the User Guide Specialty team meetings. 1.) Moving: dashboard_manage_host_aggregates.rst dashboard_manage_flavors.rst dashboard_admin_manage_stacks.rst dashboard_manage_instances.rst dashboard_manage_images.rst shared_file_systems_manage_shares_dashboard.rst 2). Remove the Images and Instances content from the compute-images-instances.rst 3.) Move the Shared file system dashboard content out of shared_file_system.rst, and into the Dashboard.rst chapter. Change-Id: I1e3c122e58349853b61be4ba514e469da407c1c9 Implements: blueprint user-guides-reorganised
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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.py
file.
After architecting and implementing the core OpenStack services and other required services, combined with the Dashboard service steps below, users and administrators can use the OpenStack dashboard. Refer to the OpenStack Dashboard <http://docs.openstack.org/ user-guide/dashboard.html>__ chapter of the User Guide for further instructions on logging in to the Dashboard.
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.
= 'django.contrib.sessions.backends.cache'
SESSION_ENGINE = {
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.
= 'django.contrib.sessions.backends.cache'
SESSION_ENGINE = {
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
anddjango-redis
installed.
= 'django.contrib.sessions.backends.cache'
SESSION_ENGINE = {
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.
Start the MySQL command-line client.
$ mysql -u root -p
Enter the MySQL root user's password when prompted.
To configure the MySQL database, create the dash database.
mysql> CREATE DATABASE dash;
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';
Enter
quit
at themysql>
prompt to exit MySQL.In the
local_settings.py
file, change these options:= 'django.contrib.sessions.backends.db' SESSION_ENGINE = { DATABASES 'default': { # Database configuration here 'ENGINE': 'django.db.backends.mysql', 'NAME': 'dash', 'USER': 'dash', 'PASSWORD': 'DASH_DBPASS', 'HOST': 'localhost', 'default-character-set': 'utf8' } }
After configuring the
local_settings.py
file as shown, you can run themanage.py syncdb
command to populate this newly created database.# /usr/share/openstack-dashboard/manage.py syncdb
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.
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
Restart the Apache service.
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:
= "django.contrib.sessions.backends.cached_db" SESSION_ENGINE
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.