- Failure handling
- Sidekiq Queues
- Queue Namespaces
- Job size
- Job weights
- Interacting with Sidekiq Redis and APIs
Sidekiq development guidelines
We use Sidekiq as our background job processor. These guides are for writing jobs that works well on GitLab.com and be consistent with our existing worker classes. For information on administering GitLab, see configuring Sidekiq.
There are pages with additional detail on the following topics:
- Compatibility across updates
- Job idempotence and job deduplication
- Limited capacity worker: continuously performing work with a specified concurrency
- Job urgency specifies queuing and execution SLOs
- Resource boundaries and external dependencies for describing the workload
- Feature categorization
- Database load balancing
All workers should include
ApplicationWorker instead of
which adds some convenience methods and automatically sets the queue based on
the routing rules.
Sidekiq defaults to using 25 retries, with back-off between each retry. 25 retries means that the last retry would happen around three weeks after the first attempt (assuming all 24 prior retries failed).
This means that a lot can happen in between the job being scheduled and its execution. Therefore, we must guard workers so they don’t fail 25 times when the state changes after they are scheduled. For example, a job should not fail when the project it was scheduled for is deleted.
def perform(project_id) project = Project.find(project_id) # ... end
def perform(project_id) project = Project.find_by_id(project_id) return unless project # ... end
For most workers - especially idempotent workers - the default of 25 retries is more than sufficient. Many of our older workers declare 3 retries, which used to be the default within the GitLab application. 3 retries happen over the course of a couple of minutes, so the jobs are prone to failing completely.
A lower retry count may be applicable if any of the below apply:
- The worker contacts an external service and we do not provide guarantees on delivery. For example, webhooks.
- The worker is not idempotent and running it multiple times could leave the system in an inconsistent state. For example, a worker that posts a system note and then performs an action: if the second step fails and the worker retries, the system note is posted again.
- The worker is a cronjob that runs frequently. For example, if a cron job runs every hour, then we don’t need to retry beyond an hour because we don’t need two of the same job running at once.
Each retry for a worker is counted as a failure in our metrics. A worker which always fails 9 times and succeeds on the 10th would have a 90% error rate.
If you want to manually retry the worker without tracking the exception in Sentry,
use an exception class inherited from
ServiceUnavailable = Class.new(::Gitlab::SidekiqMiddleware::RetryError) def perform ... raise ServiceUnavailable if external_service_unavailable? end
Failures are typically handled by Sidekiq itself, which takes advantage of the inbuilt retry mechanism mentioned above. You should allow exceptions to be raised so that Sidekiq can reschedule the job.
If you need to perform an action when a job fails after all of its retry attempts, add it to the
sidekiq_retries_exhausted do |msg, ex| project = Project.find(msg['args'].first) project.perform_a_rollback # handle the permanent failure end def perform(project_id) project = Project.find(project_id) project.some_action # throws an exception end
Previously, each worker had its own queue, which was automatically set based on the
worker class name. For a worker named
ProcessSomethingWorker, the queue name
process_something. You can now route workers to a specific queue using
queue routing rules.
In GDK, new workers are routed to a queue named
If you’re not sure what queue a worker uses,
you can find it using
SomeWorker.queue. There is almost never a reason to
manually override the queue name using
sidekiq_options queue: :some_queue.
After adding a new worker, run
gitlab:sidekiq:all_queues_yml:generate to regenerate
ee/app/workers/all_queues.yml so that
it can be picked up by
in installations that don’t use routing rules. For more information about potential changes,
see epic 596.
bin/rake gitlab:sidekiq:sidekiq_queues_yml:generate to regenerate
While different workers cannot share a queue, they can share a queue namespace.
Defining a queue namespace for a worker makes it possible to start a Sidekiq
process that automatically handles jobs for all workers in that namespace,
without needing to explicitly list all their queue names. If, for example, all
workers that are managed by
sidekiq-cron use the
cronjob queue namespace, we
can spin up a Sidekiq process specifically for these kinds of scheduled jobs.
If a new worker using the
cronjob namespace is added later on, the Sidekiq
process also picks up jobs for that worker (after having been restarted),
without the need to change any configuration.
A queue namespace can be set using the
queue_namespace DSL class method:
class SomeScheduledTaskWorker include ApplicationWorker queue_namespace :cronjob # ... end
Behind the scenes, this sets
cronjob:some_scheduled_task. Commonly used namespaces have their own
concern module that can easily be included into the worker class, and that may
set other Sidekiq options besides the queue namespace.
example, sets the namespace, but also disables retries.
bundle exec sidekiq is namespace-aware, and listens on all
queues in a namespace (technically: all queues prefixed with the namespace name)
when a namespace is provided instead of a simple queue name in the
-q) option, or in the
:queues: section in
Adding a worker to an existing namespace should be done with care, as the extra jobs take resources away from jobs from workers that were already there, if the resources available to the Sidekiq process handling the namespace are not adjusted appropriately.
Version can be specified on each Sidekiq worker class. This is then sent along when the job is created.
class FooWorker include ApplicationWorker version 2 def perform(*args) if job_version == 2 foo = args.first['foo'] else foo = args.first end end end
Under this schema, any worker is expected to be able to handle any job that was
enqueued by an older version of that worker. This means that when changing the
arguments a worker takes, you must increment the
version (or set
if this is the first time a worker’s arguments are changing), but also make sure
that the worker is still able to handle jobs that were queued with any earlier
version of the arguments. From the worker’s
perform method, you can read
self.job_version if you want to specifically branch on job version, or you
can read the number or type of provided arguments.
GitLab stores Sidekiq jobs and their arguments in Redis. To avoid excessive memory usage, we compress the arguments of Sidekiq jobs if their original size is bigger than 100 KB.
After compression, if their size still exceeds 5 MB, it raises an
error when scheduling the job.
If this happens, rely on other means of making the data available in Sidekiq. There are possible workarounds such as:
- Rebuild the data in Sidekiq with data loaded from the database or elsewhere.
- Store the data in object storage before scheduling the job, and retrieve it inside the job.
Some jobs have a weight declared. This is only used when running Sidekiq
in the default execution mode - using
does not account for weights.
As we are moving towards using
sidekiq-cluster in Free, newly-added
workers do not need to have weights specified. They can use the
default weight, which is 1.
Each Sidekiq worker must be tested using RSpec, just like any other class. These
tests should be placed in
Interacting with Sidekiq Redis and APIs
The application should minimise interaction with of any
Sidekiq.redis and Sidekiq APIs. Such interactions in generic application logic should be abstracted to a Sidekiq middleware for re-use across teams. By decoupling application logic from Sidekiq datastore, it allows for greater freedom when horizontally scaling the GitLab background processing setup.
Some exceptions to this rule would be migration-related logic or administration operations.