7.2 KiB
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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
Defining a new SLI
An SLI can be defined using the Gitlab::Metrics::Sli
class.
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 .inilialize_sli
class method, for
example:
Gitlab::Metrics::Sli.initialize_sli(:received_email, [
{
feature_category: :team_planning,
email_type: :create_issue
},
{
feature_category: :service_desk,
email_type: :service_desk
},
{
feature_category: :code_review,
email_type: :create_merge_request
}
])
Metrics must be initialized before they get scraped for the first time. This could be done at the start time of the process that will emit them, in which case we need to pay attention not to increase application's boot time too much. This is preferable if possible.
Alternatively, if initializing would take too long, this can be done during the first scrape. We need to make sure we don't do it for every scrape. This can be done as follows:
def initialize_request_slis_if_needed!
return if Gitlab::Metrics::Sli.initialized?(:rails_request_apdex)
Gitlab::Metrics::Sli.initialize_sli(:rails_request_apdex, possible_request_labels)
end
Also pay attention to do it for the different metrics
endpoints we have. Currently the
WebExporter
and the
HealthController
for Rails and
SidekiqExporter
for Sidekiq.
Tracking operations for an SLI
Tracking an operation in the newly defined SLI can be done like this:
Gitlab::Metrics::Sli[:received_email].increment(
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: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:success_total{ feature_category='service_desk', email_type='service_desk' }
So far, only tracking apdex
using a success rate is supported. If you
need to track errors this way, please upvote
this issue
and leave a comment so we can prioritize this.
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 GitLab.com'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 examplereceived_email
.significantLabels
: an array of Prometheus labels that belong to the metrics. For example:["email_type"]
. If the significant labels for the SLI includefeature_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. OnlysliDefinition.apdexKind
is supported at the moment. Reach out in this issue if you want to implement an SLI for success or error rates.
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)(gitlab_sli_aggregation:rails_request_apdex:apdex:success:rate_1h)
/
sum by (environment, stage, type)(gitlab_sli_aggregation:rails_request_apdex:apdex:weight:rate_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:
rails_requests:
sliLibrary.get('rails_request_apdex')
.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 souce 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.