Documentation Grafana Enterprise Logs Manage Recording Rules

Recording Rules

Recording rules are evaluated by the ruler component. Each ruler acts as its own querier, in the sense that it executes queries against the store without using the query-frontend or querier components. It will respect all query limits put in place for the querier.

The Loki implementation of recording rules largely reuses Prometheus’ code.

Samples generated by recording rules are sent to Prometheus using Prometheus’ remote-write feature.

Write-Ahead Log (WAL)

All samples generated by recording rules are written to a WAL. The WALs main benefit is that it persists the samples generated by recording rules to disk, which means that if your ruler crashes, you won’t lose any data. We are trading off extra memory usage and slower start-up times for this functionality.

A WAL is created per tenant; this is done to prevent cross-tenant interactions. If all samples were to be written to a single WAL, this would increase the chances that one tenant could cause data-loss for others. A typical scenario here is that Prometheus will, for example, reject a remote-write request with 100 samples if just 1 of those samples is invalid in some way.

Start-up

When the ruler starts up, it will load the WALs for the tenants who have recording rules. These WAL files are stored on disk and are loaded into memory.

Truncation

WAL files are regularly truncated to reduce their size on disk. This guide from one of the Prometheus maintainers (Ganesh Vernekar) gives an excellent overview of the truncation, checkpointing, and replaying of the WAL.

Cleaner

WAL Cleaner is an experimental feature.

The WAL Cleaner watches for abandoned WALs (tenants who no longer have recording rules associated) and deletes them. Enable this feature only if you are running into storage concerns with WALs that are too large. WALs should not grow excessively large due to truncation.

Scaling

See Mimir’s guide for configuring Grafana Mimir hash rings for scaling the ruler using a ring.

Deployment

The ruler needs to persist its WAL files to disk, and it incurs a bit of a start-up cost by reading these WALs into memory. As such, it is recommended that you try to minimize churn of individual ruler instances since rule evaluation is blocked while the WALs are being read from disk.

Kubernetes

It is recommended that you run the rulers using StatefulSets. The ruler will write its WAL files to persistent storage, so a Persistent Volume should be utilised.

Remote-Write

Client configuration

Remote-write client configuration is fully compatible with prometheus configuration format.

yaml Copy

remote_write:	
  clients:	
    mimir:	
      url: http://mimir/api/v1/push
      write_relabel_configs:
      - action: replace
        target_label: job
        replacement: loki-recording-rules

Per-Tenant Limits

Remote-write can be configured at a global level in the base configuration, and certain parameters tuned specifically on a per-tenant basis. Most of the configuration options defined here have override options (which can be also applied at runtime!).

Tuning

Remote-write can be tuned if the default configuration is insufficient (see Failure Modes below).

There is a guide on the Prometheus website, all of which applies to Loki, too.

Rules can be evenly distributed across available rulers by using -ruler.enable-sharding=true and -ruler.sharding-strategy="by-rule". Rule groups execute in order; this is a feature inherited from Prometheus’ rule engine (which Loki uses), but Loki has no need for this constraint because rules cannot depend on each other. The default sharding strategy will shard by rule groups, but this may be undesirable as some rule groups could contain more expensive rules, which can lead to subsequent rules missing evaluations. The by-rule sharding strategy creates one rule group for each rule the ruler instance “owns” (based on its hash ring), and these rings are all executed concurrently.

Observability

Since Loki reuses the Prometheus code for recording rules and WALs, it also gains all of Prometheus’ observability.

Prometheus exposes a number of metrics for its WAL implementation, and these have all been prefixed with loki_ruler_wal_.

For example: prometheus_remote_storage_bytes_total → loki_ruler_wal_prometheus_remote_storage_bytes_total

Additional metrics are exposed, also with the prefix loki_ruler_wal_. All per-tenant metrics contain a tenant label, so be aware that cardinality could begin to be a concern if the number of tenants grows sufficiently large.

Some key metrics to note are:

• loki_ruler_wal_appender_ready: whether a WAL appender is ready to accept samples (1) or not (0)
• loki_ruler_wal_prometheus_remote_storage_samples_total: number of samples sent per tenant to remote storage
• loki_ruler_wal_prometheus_remote_storage_samples...
  • loki_ruler_wal_prometheus_remote_storage_samples_pending_total: samples buffered in memory, waiting to be sent to remote storage
  • loki_ruler_wal_prometheus_remote_storage_samples_failed_total: samples that failed when sent to remote storage
  • loki_ruler_wal_prometheus_remote_storage_samples_dropped_total: samples dropped by relabel configurations
  • loki_ruler_wal_prometheus_remote_storage_samples_retried_total: samples re-resent to remote storage
• loki_ruler_wal_prometheus_remote_storage_highest_timestamp_in_seconds: highest timestamp of sample appended to WAL
• loki_ruler_wal_prometheus_remote_storage_queue_highest_sent_timestamp_seconds: highest timestamp of sample sent to remote storage.

We’ve created a basic dashboard in our loki-mixin which you can use to administer recording rules.

Failure Modes

Remote-Write Lagging

Remote-write can lag behind for many reasons:

1. Remote-write storage (Prometheus) is temporarily unavailable
2. A tenant is producing samples too quickly from a recording rule
3. Remote-write is tuned too low, creating backpressure

It can be determined by subtracting loki_ruler_wal_prometheus_remote_storage_queue_highest_sent_timestamp_seconds from loki_ruler_wal_prometheus_remote_storage_highest_timestamp_in_seconds.

In case 1, the ruler will continue to retry sending these samples until the remote storage becomes available again. Be aware that if the remote storage is down for longer than ruler.wal.max-age, data loss may occur after truncation occurs.

In cases 2 and 3, you should consider tuning remote-write appropriately.

Further reading: see this blog post by Prometheus maintainer Callum Styan.

Appender Not Ready

Each tenant’s WAL has an “appender” internally; this appender is used to append samples to the WAL. The appender is marked as not ready until the WAL replay is complete upon startup. If the WAL is corrupted for some reason, or is taking a long time to replay, you can determine this by alerting on loki_ruler_wal_appender_ready < 1.

Corrupt WAL

If a disk fails or the ruler does not terminate correctly, there’s a chance one or more tenant WALs can become corrupted. A mechanism exists for automatically repairing the WAL, but this cannot handle every conceivable scenario. In this case, the loki_ruler_wal_corruptions_repair_failed_total metric will be incremented.

Found another failure mode?

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