Grafana Metrics Enterprise (GME) allows for forwarding metrics evaluated from the Ruler to any Prometheus remote-write compatible backend.
This works by loading rule groups into the Ruler with an extra config field as shown in the example below:
# A regular Cortex rule group groups: - name: group_one interval: 5m rules: - expr: 'rate(prometheus_remote_storage_samples_in_total[5m])' record: 'prometheus_remote_storage_samples_in_total:rate5m' - name: group_two interval: 1m rules: - expr: 'rate(prometheus_remote_storage_samples_in_total[1m])' record: 'prometheus_remote_storage_samples_in_total:rate1m' remote_write: - url: 'http://user:email@example.com/api/v1/push'
In the above example, when
group_2 is loaded into Grafana Metrics Enterprise, the Ruler Module
will evaluate the expression
and forward the generated metric with name
group_1 will continue to work as expected, the evaluated
prometheus_remote_storage_samples_in_total:rate5m will be stored within the same cortex
instance that is running the Ruler.
Remote write rules are compatible with the following backends:
- Azure Blob Storage
The following backends are not supported:
- local filesystem
Write-ahead log (WAL)
When a rule group is configured with a remote-write config, GME buffers the generated metrics in a write-ahead log (WAL) before forwarding them to the remote-write endpoint. This is done to increase reliability in case either the GME instance or the remote endpoint crashes. If the GME instance crashes, it reads from the WAL and continues to forward metrics to the configured backend from the last sent timestamp. If the remote endpoint crashes, GME continues to retry requests until it is available again. If multiple rule groups have been configured to send to the same remote-write endpoint, the GME instance will use a common WAL for the metrics generated by those rule groups.
By default, the WAL is stored in the
wal folder in the GME binary working directory.
$ ls metrics-enterprise-binary wal/
The directory can be configured as shown:
enterprise_features: ruler_remote_write: wal_dir: /tmp/wal
The following is a complete example of the above mentioned config options using a ruler with sharding enabled and S3 as its rule storage backend:
ruler: external_url: localhost:9090 rule_path: "/tmp/rules" storage: type: s3 s3: endpoint: minio:9000 access_key_id: cortex secret_access_key: supersecret bucketnames: "gme-ruler" insecure: true s3forcepathstyle: true poll_interval: 10s enable_api: true enable_sharding: true ring: kvstore: store: memberlist enterprise_features: ruler_remote_write: enabled: true wal_dir: /tmp/wal
Loading remote-write groups
cortextool project, as of version
v0.3.1, is compatible with Prometheus rule files that contain the remote-write rule group syntax. You can download and use the latest version of the
You can also use the docker image of the
docker pull grafana/cortex-tools:latest
Once you have GME running with remote-write rule groups enabled you can load remote-write rule groups using the following procedure.
- Save the following file to your workspace:
groups: - name: remote_write_group interval: 5m rules: - expr: 'sum(up)' record: 'sum_up' remote_write: - url: 'http://user:firstname.lastname@example.org/api/v1/push'
- Run the following command with
$ cortextool rules sync \ --rule-files=rules.yaml \ --id=<instance-name> \ --address=<gme-url> \ --key=<valid-gme-write-token>