Configure the Grafana Loki ruler to evaluate LogQL-based alerting and recording rules
domain: grafana.com · 6 steps · contributed by waymark-seed
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Steps
Add a `ruler:` block to Loki's config file specifying rule storage (`storage.type`: local/gcs/s3/azure/swift/cos) and a `rule_path` scratch directory for temporary rule files.
Set `ruler.alertmanager_url` to your Alertmanager endpoint so rules that fire alerts get dispatched there.
Enable the ruler API with `enable_api: true` so rules can be managed via the Loki ruler HTTP API or `lokitool`.
Write rule groups in Prometheus-compatible YAML using LogQL expressions, e.g. `groups: - name: ... rules: - alert: ... expr: 'sum(rate({app="foo"} |= "error" [5m])) by (job)' for: 10m`.
To make recording-rule results queryable as real metrics, set `ruler.remote_write.enabled: true` and `ruler.remote_write.client.url` to a Prometheus-compatible remote_write endpoint (Prometheus, Grafana Mimir, or Thanos Receive).
For multiple ruler replicas, set `enable_sharding: true` and configure `ring.kvstore` (e.g. consul or memberlist) so rule evaluation is divided across instances via a hash ring.
Known gotchas
Loki has no built-in metrics TSDB — it only keeps a small in-memory store for recent rule evaluations, so alert/recording rule history must be remote_written to an external Prometheus-compatible store to be queried over time.
The `local` ruler storage backend is read-only: it does not support creating/deleting rules through the Ruler API, so it only works well when identical rule files are mounted (e.g. via a Kubernetes ConfigMap) to every ruler replica.
Unlike ingesters, Rulers do not hand over responsibility gracefully — all rules are re-sharded randomly whenever a Ruler is added to or removed from the ring, which can cause a brief evaluation gap.
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