Sidekiq Compatibility across Updates
The arguments for a Sidekiq job are stored in a queue while it is scheduled for execution. During a online update, this could lead to several possible situations:
- An older version of the application publishes a job, which is executed by an upgraded Sidekiq node.
- A job is queued before an upgrade, but executed after an upgrade.
- A job is queued by a node running the newer version of the application, but executed on a node running an older version of the application.
Adding new workers
On GitLab.com, we do not currently have a Sidekiq deployment in the canary stage. This means that a new worker than can be scheduled from an HTTP endpoint may be scheduled from canary but not run on Sidekiq until the full production deployment is complete. This can be several hours later than scheduling the job. For some workers, this will not be a problem. For others - particularly latency-sensitive jobs - this will result in a poor user experience.
This only applies to new worker classes when they are first introduced. As we recommend using feature flags as a general development process, it's best to control the entire change (including scheduling of the new Sidekiq worker) with a feature flag.
Changing the arguments for a worker
Jobs need to be backward and forward compatible between consecutive versions of the application. Adding or removing an argument may cause problems during deployment before all Rails and Sidekiq nodes have the updated code.
Deprecate and remove an argument
Before you remove arguments from the perform_async
and perform
methods., deprecate them. The
following example deprecates and then removes arg2
from the perform_async
method:
-
Provide a default value (usually
nil
) and use a comment to mark the argument as deprecated in the coming minor release. (Release M)class ExampleWorker # Keep arg2 parameter for backwards compatibility. def perform(object_id, arg1, arg2 = nil) # ... end end
-
One minor release later, stop using the argument in
perform_async
. (Release M+1)ExampleWorker.perform_async(object_id, arg1)
-
At the next major release, remove the value from the worker class. (Next major release)
class ExampleWorker def perform(object_id, arg1) # ... end end
Add an argument
There are two options for safely adding new arguments to Sidekiq workers:
- Set up a multi-step deployment in which the new argument is first added to the worker.
- Use a parameter hash for additional arguments. This is perhaps the most flexible option.
Multi-step deployment
This approach requires multiple releases.
-
Add the argument to the worker with a default value (Release M).
class ExampleWorker def perform(object_id, new_arg = nil) # ... end end
-
Add the new argument to all the invocations of the worker (Release M+1).
ExampleWorker.perform_async(object_id, new_arg)
-
Remove the default value (Release M+2).
class ExampleWorker def perform(object_id, new_arg) # ... end end
Parameter hash
This approach doesn't require multiple releases if an existing worker already uses a parameter hash.
-
Use a parameter hash in the worker to allow future flexibility.
class ExampleWorker def perform(object_id, params = {}) # ... end end
Removing workers
Try to avoid removing workers and their queues in minor and patch releases.
During online update instance can have pending jobs and removing the queue can lead to those jobs being stuck forever. If you can't write migration for those Sidekiq jobs, please consider removing the worker in a major release only.
Renaming queues
For the same reasons that removing workers is dangerous, care should be taken when renaming queues.
When renaming queues, use the sidekiq_queue_migrate
helper migration method
in a post-deployment migration:
class MigrateTheRenamedSidekiqQueue < Gitlab::Database::Migration[2.0]
restrict_gitlab_migration gitlab_schema: :gitlab_main
disable_ddl_transaction!
def up
sidekiq_queue_migrate 'old_queue_name', to: 'new_queue_name'
end
def down
sidekiq_queue_migrate 'new_queue_name', to: 'old_queue_name'
end
end
You must rename the queue in a post-deployment migration not in a normal migration. Otherwise, it runs too early, before all the workers that schedule these jobs have stopped running. See also other examples.