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[Feature flag] Rollout of `log_large_in_list_queries`

Summary

This issue is to roll out the feature on production, that is currently behind the log_large_in_list_queries feature flag.

Owners

  • Most appropriate Slack channel to reach out to: #g_database
  • Best individual to reach out to: @l.rosa

Expectations

What are we expecting to happen?

We're rolling out a feature-flag that will process certain types of queries and detect when a bad pattern happens. Soon as we roll out the FF on production, we expect to keep the same levels of memory usage and processing power the same.

Timeline

Time Event Link
Jan, 23rd ~"workflow::staging-canary" gitlab-org/gitlab!141150 (comment 1739346905)
Jan, 23rd ~"workflow::canary" gitlab-org/gitlab!141150 (comment 1739371673)
Jan, 23rd ~"workflow::staging" gitlab-org/gitlab!141150 (comment 1739444754)
Jan, 24th workflowproduction gitlab-org/gitlab!141150 (comment 1739467906)

What can go wrong and how would we detect it?

Rollout Steps

Note: Please make sure to run the chatops commands in the Slack channel that gets impacted by the command.

Rollout on non-production environments

  • Verify the MR with the feature flag is merged to master and have been deployed to non-production environments with /chatops run auto_deploy status e4de7cc6daf007c27b4939cad6e08e1fa478635f - ✅

chatops1

  • Deploy the feature flag at a percentage (recommended percentage: 50%) with /chatops run feature set log_large_in_list_queries 0.01 --actors --dev --pre --staging --staging-ref

It's enabled in staging:

[ gstg ] production> Feature::FlipperGate.where(feature_key: "log_large_in_list_queries", key: "percentage_of_actors")

[#<Feature::FlipperGate:0x00007f3d0da57c00
  id: 1215123,
  feature_key: "[FILTERED]",
  key: "[FILTERED]",
  value: "0.01",
  created_at: Fri, 26 Jan 2024 18:58:30.706166000 UTC +00:00,
  updated_at: Fri, 26 Jan 2024 18:58:30.706166000 UTC +00:00>]
  • Enable the feature globally on non-production environments with /chatops run feature set log_large_in_list_queries true --dev --pre --staging --staging-ref Not applicable here. It's an ops type flag.
  • Verify that the feature works as expected. The best environment to validate the feature in is staging-canary as this is the first environment deployed to. Make sure you are configured to use canary.
# 1. Enable the analyzer
Thread.current[:query_analyzer_enabled_analyzers] = [Gitlab::Database::QueryAnalyzers::LogLargeInLists]

# 2. Perform a query
Project.select(:id).where(id: (1..2600).to_a)

# 3. Check the logs
path = Gitlab::AppLogger.primary_logger.full_log_path
[] unless File.readable?(path)
tail_output, _ = Gitlab::Popen.popen(%W[tail -n 2000 #{path}])
tail_output.split("\n")

# 4. Log is present
[..."{\"severity\":\"WARN\",\"time\":\"2024-01-29T14:31:24.426Z\",\"message\":\"large_in_list_found\",\"matches\":1,\"event_name\":\"load\",\"in_list_size\":\"2600\",\"stacktrace\":[]}"]
  • If the feature flag causes end-to-end tests to fail, disable the feature flag on staging to avoid blocking deployments.

For assistance with end-to-end test failures, please reach out via the #test-platform Slack channel. Note that end-to-end test failures on staging-ref don't block deployments.

Specific rollout on production

For visibility, all /chatops commands that target production should be executed in the #production Slack channel and cross-posted (with the command results) to the responsible team's Slack channel.

  • Ensure that the feature MRs have been deployed to both production and canary with /chatops run auto_deploy status <merge-commit-of-your-feature>

chatops2

  • Depending on the type of actor you are using, pick one of these options:
    • For project-actor: /chatops run feature set --project=gitlab-org/gitlab,gitlab-org/gitlab-foss,gitlab-com/www-gitlab-com log_large_in_list_queries true
    • For group-actor: /chatops run feature set --group=gitlab-org,gitlab-com log_large_in_list_queries true
    • For user-actor: /chatops run feature set --user=<gitlab-username-of-dri> log_large_in_list_queries true
    • For current-request: /chatops run feature set log_large_in_list_queries 0.01 --actors --production
  • Verify that the feature works for the specific actors.

Preparation before global rollout

  • Set a milestone to this rollout issue to signal for enabling and removing the feature flag when it is stable.
  • Check if the feature flag change needs to be accompanied with a change management issue. Cross link the issue here if it does.
  • Ensure that you or a representative in development can be available for at least 2 hours after feature flag updates in production. If a different developer will be covering, or an exception is needed, please inform the oncall SRE by using the @sre-oncall Slack alias.
  • Ensure that documentation exists for the feature, and the version history text has been updated.
  • Leave a comment on the feature issue announcing estimated time when this feature flag will be enabled on GitLab.com.
  • Ensure that any breaking changes have been announced following the release post process to ensure GitLab customers are aware.
  • Notify the #support_gitlab-com Slack channel and your team channel (more guidance when this is necessary in the dev docs).
  • Ensure that the feature flag rollout plan is reviewed by another developer familiar with the domain.

Global rollout on production

For visibility, all /chatops commands that target production should be executed in the #production Slack channel and cross-posted (with the command results) to the responsible team's Slack channel (#g_database).

  • (Optional) Incrementally roll out the feature on production environment.
    • Between every step wait for at least 15 minutes and monitor the appropriate graphs on https://dashboards.gitlab.net.
    • Perform actor-based rollout: /chatops run feature set log_large_in_list_queries <rollout-percentage> --actors
  • Enable the feature globally on production environment: /chatops run feature set log_large_in_list_queries true
  • Observe appropriate graphs on https://dashboards.gitlab.net and verify that services are not affected.
  • Leave a comment on [the feature issue][main-issue] announcing that the feature has been globally enabled.
  • Wait for at least one day for the verification term.

(Optional) Release the feature with the feature flag

WARNING: This approach has the downside that it makes it difficult for us to clean up the flag. For example, on-premise users could disable the feature on their GitLab instance. But when you remove the flag at some point, they suddenly see the feature as enabled and they can't roll it back to the previous behavior. To avoid this potential breaking change, use this approach only for urgent matters.

See instructions if you're sure about enabling the feature globally through the feature flag definition

If you're still unsure whether the feature is deemed stable but want to release it in the current milestone, you can change the default state of the feature flag to be enabled. To do so, follow these steps:

  • Create a merge request with the following changes. Ask for review and merge it.
  • Ensure that the default-enabling MR has been included in the release package. If the merge request was deployed before the monthly release was tagged, the feature can be officially announced in a release blog post: /chatops run release check <merge-request-url> 16.9
  • Consider cleaning up the feature flag from all environments by running these chatops command in #production channel. Otherwise these settings may override the default enabled: /chatops run feature delete log_large_in_list_queries --dev --pre --staging --staging-ref --production
  • Close [the feature issue][main-issue] to indicate the feature will be released in the current milestone.
  • Set the next milestone to this rollout issue for scheduling the flag removal.
  • (Optional) You can create a separate issue for scheduling the steps below to Release the feature.
    • Set the title to "[Feature flag] Cleanup log_large_in_list_queries".
    • Execute the /copy_metadata <this-rollout-issue-link> quick action to copy the labels from this rollout issue.
    • Link this rollout issue as a related issue.
    • Close this rollout issue.

Release the feature

After the feature has been deemed stable, the clean up should be done as soon as possible to permanently enable the feature and reduce complexity in the codebase.

You can either create a follow-up issue for Feature Flag Cleanup or use the checklist below in this same issue.

  • Create a merge request to remove the log_large_in_list_queries feature flag. Ask for review/approval/merge as usual. The MR should include the following changes:
    • Remove all references to the feature flag from the codebase.
    • Remove the YAML definitions for the feature from the repository.
    • Create a changelog entry.
  • Ensure that the cleanup MR has been included in the release package. If the merge request was deployed before the monthly release was tagged, the feature can be officially announced in a release blog post: /chatops run release check <merge-request-url> 16.9
  • Close [the feature issue][main-issue] to indicate the feature will be released in the current milestone.
  • Clean up the feature flag from all environments by running these chatops command in #production channel: /chatops run feature delete log_large_in_list_queries --dev --pre --staging --staging-ref --production
  • Close this rollout issue.

Rollback Steps

  • This feature can be disabled by running the following Chatops command:
/chatops run feature set log_large_in_list_queries false
Edited by Leonardo da Rosa