This document covers architectural concepts of the ODL drivers. Although ‘driver’ is an ML2 term, it’s used widely in ODL to refer to any implementation of APIs. Any mention of ML2 in this document is solely for reference purposes.
The first driver version was a naive implementation which synchronously mirrored all calls to the ODL controller. For example, a create network request would first get written to the DB by Neutron’s ML2 plugin, and then the ODL driver would send the request to POST the network to the ODL controller.
Although this implementation is simple, it has a few problems:
The V2 driver set upon to tackle problems encountered in the V1 driver while maintaining feature parity. The major design concept of the V2 driver is journaling - instead of passing the calls directly to the ODL controller, they get registered in the journal table which keeps a sort of queue of the various operations that occurred on Neutron and should be mirrored to the controller.
The journal is processed mainly by a journaling thread which runs periodically and checks if the journal table has any entries in need of processing. Additionally the thread is triggered in the postcommit hook of the operation (where applicable).
If we take the example of create network again, after it gets stored in the Neutron DB by the ML2 plugin, the ODL driver stores a “journal entry” representing that operation and triggers the journalling thread to take care of the entry.
The journal entry is recorded in the pre-commit phase (whenever applicable) so that in case of a commit failure the journal entry gets aborted along with the original operation, and there’s nothing extra needed.
The first state in which a journal entry is created is the ‘pending’ state. In this state, the entry is awaiting a thread to pick it up and process it. Multiple threads can try to grab the same journal entry, but only one will succeed since the “selection” is done inside a ‘select for update’ clause. Special care is taken for GaleraDB since it reports a deadlock if more than one thread selects the same row simultaneously.
Once an entry has been selected it will be put into the ‘processing’ state which acts as a lock. This is done in the same transaction so that in case multiple threads try to “lock” the same entry only one of them will succeed. When the winning thread succeeds it will continue with processing the entry.
The first thing the thread does is check for dependencies - if the entry depends on another one to complete. If a dependency is found, the entry is put back into the queue and the thread moves on to the next entry.
When there are no dependencies for the entry, the thread analyzes the operation that occurred and performs the appropriate call to the ODL controller. The call is made to the correct resource or collection and the type of call (PUT, POST, DELETE) is determined by the operation type. At this point if the call was successful (i.e. got a 200 class HTTP code) the entry is marked ‘completed’.
In case of a failure the thread determines if this is an expected failure (e.g. network connectivity issue) or an unexpected failure. For unexpected failures a counter is raised, so that a given entry won’t be retried more than a given amount of times. Expected failures don’t change the counter. If the counter exceeds the configured amount of retries, the entry is marked as ‘failed’. Otherwise, the entry is marked back as ‘pending’ so that it can later be retried.