Caching layer

Caching layer

OpenStack Identity supports a caching layer that is above the configurable subsystems (for example, token). This gives you the flexibility to setup caching for all or some subsystems. OpenStack Identity uses the oslo.cache library which allows flexible cache back ends. The majority of the caching configuration options are set in the [cache] section of the /etc/keystone/keystone.conf file. The enabled option of the [cache] section must be set to True in order for any subsystem to cache responses. Each section that has the capability to be cached will have a caching boolean value that toggles caching behavior of that particular subsystem.

So to enable only the token back end caching, set the values as follows:










Each subsystem is configured to cache by default. However, the global toggle for caching defaults to False. A subsystem is only able to cache responses if the global toggle is enabled.

Current functional back ends are:

Memcached back end using the standard python-memcached library.
Memcached back end using the pylibmc library.
Memcached using the python-binary-memcached library.
Redis back end.
Local DBM file back end.
In-memory cache, not suitable for use outside of testing as it does not cleanup its internal cache on cache expiration and does not share cache between processes. This means that caching and cache invalidation will not be consistent or reliable.
MongoDB as caching back end.

Caching for tokens and tokens validation

The token subsystem is OpenStack Identity’s most heavily used API. As a result, all types of tokens benefit from caching, including Fernet tokens. Although Fernet tokens do not need to be persisted, they should still be cached for optimal token validation performance.

The token system has a separate cache_time configuration option, that can be set to a value above or below the global expiration_time default, allowing for different caching behavior from the other systems in OpenStack Identity. This option is set in the [token] section of the configuration file.

The token revocation list cache time is handled by the configuration option revocation_cache_time in the [token] section. The revocation list is refreshed whenever a token is revoked. It typically sees significantly more requests than specific token retrievals or token validation calls.

Here is a list of actions that are affected by the cached time: getting a new token, revoking tokens, validating tokens, checking v2 tokens, and checking v3 tokens.

The delete token API calls invalidate the cache for the tokens being acted upon, as well as invalidating the cache for the revoked token list and the validate/check token calls.

Token caching is configurable independently of the revocation_list caching. Lifted expiration checks from the token drivers to the token manager. This ensures that cached tokens will still raise a TokenNotFound flag when expired.

For cache consistency, all token IDs are transformed into the short token hash at the provider and token driver level. Some methods have access to the full ID (PKI Tokens), and some methods do not. Cache invalidation is inconsistent without token ID normalization.

Caching for non-token resources

Various other keystone components have a separate cache_time configuration option, that can be set to a value above or below the global expiration_time default, allowing for different caching behavior from the other systems in Identity service. This option can be set in various sections (for example, [role] and [resource]) of the configuration file. The create, update, and delete actions for domains, projects and roles will perform proper invalidations of the cached methods listed above.

For more information about the different back ends (and configuration options), see:

Cache invalidation

A common concern with caching is relaying inaccurate information after updating or deleting a resource. Most subsystems within OpenStack Identity invalidate specific cache entries once they have changed. In cases where a specific cache entry cannot be invalidated from the cache, the cache region will be invalidated instead. This invalidates all entries within the cache to prevent returning stale or misleading data. A subsequent request for the resource will be fully processed and cached.


Be aware that if a read-only back end is in use for a particular subsystem, the cache will not immediately reflect changes performed through the back end. Any given change may take up to the cache_time (if set in the subsystem section of the configuration) or the global expiration_time (set in the [cache] section of the configuration) before it is reflected. If this type of delay is an issue, we recommend disabling caching for that particular subsystem.

Configure the Memcached back end example

The following example shows how to configure the memcached back end:


enabled = true
backend = dogpile.cache.memcached
backend_argument = url:

You need to specify the URL to reach the memcached instance with the backend_argument parameter.

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