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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
- Logging
- Worker attributes
- Job urgency specifies queuing and execution SLOs
- Resource boundaries and external dependencies for describing the workload
- Feature categorization
- Database load balancing
ApplicationWorker
All workers should include ApplicationWorker
instead of Sidekiq::Worker
,
which adds some convenience methods and automatically sets the queue based on
the routing rules.
Retries
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.
Instead of:
def perform(project_id)
project = Project.find(project_id)
# ...
end
Do this:
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 Gitlab::SidekiqMiddleware::RetryError
.
ServiceUnavailable = Class.new(::Gitlab::SidekiqMiddleware::RetryError)
def perform
...
raise ServiceUnavailable if external_service_unavailable?
end
Failure handling
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
method.
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
Sidekiq Queues
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
would be 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 default
.
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 bin/rake gitlab:sidekiq:all_queues_yml:generate
to regenerate
app/workers/all_queues.yml
or ee/app/workers/all_queues.yml
so that
it can be picked up by
sidekiq-cluster
in installations that don't use routing rules. For more information about potential changes,
see epic 596.
Additionally, run
bin/rake gitlab:sidekiq:sidekiq_queues_yml:generate
to regenerate
config/sidekiq_queues.yml
.
Queue Namespaces
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 SomeScheduledTaskWorker.queue
to
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. CronjobQueue
, for
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 --queue
(-q
) option, or in the :queues:
section in config/sidekiq_queues.yml
.
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.
Versioning
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 version 1
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.
Job size
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
ExceedLimitError
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.
Job weights
Some jobs have a weight declared. This is only used when running Sidekiq
in the default execution mode - using
sidekiq-cluster
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.
Tests
Each Sidekiq worker must be tested using RSpec, just like any other class. These
tests should be placed in spec/workers
.
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.