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SLO measurement should mention a month as a period

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Closes #39312

Signed-off-by: Alexander Schwartz <aschwart@redhat.com>
Signed-off-by: Michal Hajas <mhajas@redhat.com>
Co-authored-by: Michal Hajas <mhajas@redhat.com>
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Alexander Schwartz 2025-04-29 14:19:19 +02:00 committed by GitHub
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20
docs/guides/observability/keycloak-service-level-indicators.adoc
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@ -58,12 +58,12 @@ At the same time, if you enter a Service Level Agreement (SLA) with stakeholders
| Latency
| Response time for authentication related HTTP requests as measured by the server
| 95% of all authentication related requests should be faster than 250 ms within a 5-minute-range.
| 95% of all authentication related requests should be faster than 250 ms within 30 days.
| {project_name} server-side metrics to track latency for specific endpoints along with Response Time Distribution using `http_server_requests_seconds_bucket` and `http_server_requests_seconds_count`.
| Errors
| Failed authentication requests due to server problems as measured by the server
| The rate of errors due to server problems for authentication requests should be less than 0.1% within a 5-minute-range.
| The rate of errors due to server problems for authentication requests should be less than 0.1% within 30 days.
| Identify server side error by filtering the metric `http_server_requests_seconds_count` on the tag `outcome` for value `SERVER_ERROR`.
|===
@ -103,7 +103,7 @@ NOTE: In Grafana you can replace value `30d:15s` with `$__range:$__interval` to
=== Latency of authentication requests
This Prometheus query calculates the percentage of authentication requests that completed within 0.25 seconds relative to all authentication requests for specific {project_name} endpoints, targeting a particular namespace and pod, over the past 5 minutes.
This Prometheus query calculates the percentage of authentication requests that completed within 0.25 seconds relative to all authentication requests for specific {project_name} endpoints, targeting a particular namespace and pod, over the past 30 days.
This example requires the {project_name} configuration `http-metrics-slos` to contain value `250` indicating that buckets for requests faster and slower than 250 ms should be recorded.
Setting `http-metrics-histograms-enabled` to `true` would capture additional buckets which can help with performance troubleshooting.
@ -116,7 +116,7 @@ sum(
le="0.25", # <2>
container="keycloak", # <3>
namespace="$namespace"}
[5m] # <4>
[30d] # <4>
)
) without (le,uri,status,outcome,method,pod,instance) # <5>
/
@ -126,7 +126,7 @@ sum(
uri=~"/realms/{realm}/protocol/{protocol}.*|/realms/{realm}/login-actions.*", # <1>
container="keycloak",
namespace="$namespace"}
[5m] # <3>
[30d] # <3>
)
) without (le,uri,status,outcome,method,pod,instance) # <5>
----
@ -136,13 +136,13 @@ sum(
<4> Time range as specified by the SLO
<5> Ignore as many labels necessary to create a single sum
NOTE: In Grafana you can replace value `5m` with `$__range` to compute latency SLI in the time range selected for the dashboard.
NOTE: In Grafana, you can replace value `30d` with `$__range` to compute latency SLI in the time range selected for the dashboard.
=== Errors for authentication requests
This Prometheus query calculates the percentage of authentication requests
that returned a server side error for all authentication requests,
targeting a particular namespace, over the past 5 minutes.
targeting a particular namespace, over the past 30 days.
[source,plaintext]
----
@ -153,7 +153,7 @@ sum(
outcome="SERVER_ERROR", # <2>
container="keycloak", # <3>
namespace="$namespace"}
[5m] # <4>
[30d] # <4>
)
) without (le,uri,status,outcome,method,pod,instance) # <5>
/
@ -163,7 +163,7 @@ sum(
uri=~"/realms/{realm}/protocol/{protocol}.*|/realms/{realm}/login-actions.*", # <1>
container="keycloak", # <3>
namespace="$namespace"}
[5m] # <4>
[30d] # <4>
)
) without (le,uri,status,outcome,method,pod,instance) # <5>
----
@ -173,6 +173,8 @@ sum(
<4> Time range as specified by the SLO
<5> Ignore as many labels necessary to create a single sum
NOTE: In Grafana, you can replace value `30d` with `$__range` to compute errors SLI in the time range selected for the dashboard.
== Further Reading
* https://sre.google/sre-book/service-level-objectives/[Google SRE Book on Service Level Objectives]