Rule Evaluation

Rules evaluate at a fixed interval, default 1m. The evaluation_interval is global. Each group of rules is evaluated together.

A rule that fails (e.g. the underlying metric is absent) produces no series for that evaluation; the rule does not raise an error. The absence is the symptom.

A missing series can mean the rule is wrong, the source data is wrong, or the source is not yet scraped. The platform returns no value to the dashboard; the operator must investigate.

What it is

A precise definition of rule evaluation, scoped to production operations.

Why a sysadmin cares

Production framing. The operational pain this concept addresses, or the incident class it prevents.

How it works

The mental model.

How to configure it

# Configuration snippet illustrating the lesson topic
example_setting: value

How to validate it

promtool check config /etc/prometheus/prometheus.yml

How it can fail

The high-frequency failure modes:

1. Silent misconfiguration.
2. Crash on load.
3. Performance regression.
4. Permissions failure.
5. Schema / version drift.

How to troubleshoot it

The diagnostic order:

1. Was it working before?
2. What does the service’s view say?
3. What does the platform’s view say?
4. Form hypothesis, find evidence, test, validate.

Security implications

Rule Evaluation has security implications wherever the relevant component exposes an HTTP endpoint, an authentication layer, or a credential.

Performance implications

Performance implications come from cardinality, scrape / push interval, rule size, retention, and query cost.

Production guidance

• Validate before applying.
• Test changes in a non-production environment.
• Document operational defaults in the team’s instrumentation guide.

Verification

You should now be able to answer:

• What is rule evaluation in production terms?
• Why does a sysadmin care about it?
• How does it fail and how do you diagnose the failure?

Quiz