GitLab Application Service Level Indicators (SLIs)

Introduced in GitLab 14.4

It is possible to define Service Level Indicators(SLIs) directly in the Ruby codebase. This keeps the definition of operations and their success close to the implementation and allows the people building features to easily define how these features should be monitored.

Defining an SLI causes 2 Prometheus counters to be emitted from the rails application:

  • gitlab_sli:<sli name>:total: incremented for each operation.
  • gitlab_sli:<sli_name>:success_total: incremented for successful operations.

Existing SLIs

  1. rails_request_apdex
  2. global_search_apdex
  3. global_search_error_rate
  4. global_search_indexing_apdex

Defining a new SLI

An SLI can be defined using the Gitlab::Metrics::Sli::Apdex or Gitlab::Metrics::Sli::ErrorRate class. These work in broadly the same way, but for clarity, they define different metric names:

  1.'foo') defines:
    1. gitlab_sli:foo_apdex:total for the total number of measurements.
    2. gitlab_sli:foo_apdex:success_total for the number of successful measurements.
  2.'foo') defines:
    1. gitlab_sli:foo:total for the total number of measurements.
    2. gitlab_sli:foo:error_total for the number of error measurements - as this is an error rate, it’s more natural to talk about errors divided by the total.

As shown in this example, they can share a base name (foo in this example). We recommend this when they refer to the same operation.

Before the first scrape, it is important to have initialized the SLI with all possible label-combinations. This avoid confusing results when using these counters in calculations.

To initialize an SLI, use the .initialize_sli class method, for example:

Gitlab::Metrics::Sli::Apdex.initialize_sli(:received_email, [
    feature_category: :team_planning,
    email_type: :create_issue
    feature_category: :service_desk,
    email_type: :service_desk
    feature_category: :code_review_workflow,
    email_type: :create_merge_request

Metrics must be initialized before they get scraped for the first time. This currently happens during the on_master_start life-cycle event. Since this delays application readiness until metrics initialization returns, make sure the overhead this adds is understood and acceptable.

Tracking operations for an SLI

Tracking an operation in the newly defined SLI can be done like this:

  labels: {
    feature_category: :service_desk,
    email_type: :service_desk
  success: issue_created?

Calling #increment on this SLI will increment the total Prometheus counter

gitlab_sli:received_email_apdex:total{ feature_category='service_desk', email_type='service_desk' }

If the success: argument passed is truthy, then the success counter will also be incremented:

gitlab_sli:received_email_apdex:success_total{ feature_category='service_desk', email_type='service_desk' }

For error rate SLIs, the equivalent argument is called error::

  labels: {
    merge_type: :fast_forward
  error: !merge_success?

Using the SLI in service monitoring and alerts

When the application is emitting metrics for a new SLI, they need to be consumed from the metrics catalog to result in alerts, and included in the error budget for stage groups and’s overall availability.

Start by adding the new SLI to the Application-SLI library. After that, add the following information:

  • name: the name of the SLI as defined in code. For example received_email.
  • significantLabels: an array of Prometheus labels that belong to the metrics. For example: ["email_type"]. If the significant labels for the SLI include feature_category, the metrics will also feed into the error budgets for stage groups.
  • featureCategory: if the SLI applies to a single feature category, you can specify it statically through this field to feed the SLI into the error budgets for stage groups.
  • description: a Markdown string explaining the SLI. It will be shown on dashboards and alerts.
  • kind: the kind of indicator. For example sliDefinition.apdexKind.

When done, run make generate to generate recording rules for the new SLI. This command creates recordings for all services emitting these metrics aggregated over significantLabels.

Open up a merge request with these changes and request review from a Scalability team member.

When these changes are merged, and the aggregations in Thanos recorded, query Thanos to see the success ratio of the new aggregated metrics. For example:

sum by (environment, stage, type)(application_sli_aggregation:rails_request:apdex:success:rate_1h)
sum by (environment, stage, type)(application_sli_aggregation:rails_request:apdex:weight:score_1h)

This shows the success ratio, which can guide you to set an appropriate SLO when adding this SLI to a service.

Then, add the SLI to the appropriate service catalog file. For example, the web service:

    .generateServiceLevelIndicator({ job: 'gitlab-rails' })

To pass extra selectors and override properties of the SLI, see the service monitoring documentation.

SLIs with statically defined feature categories can already receive alerts about the SLI in specified Slack channels. For more information, read the alert routing documentation. In this project we are extending this so alerts for SLIs with a feature_category label in the source metrics can also be routed.

For any question, please don’t hesitate to create an issue in the Scalability issue tracker or come find us in #g_scalability on Slack.