Grafana Alerting uses the Prometheus model of separating the evaluation of alert rules from the delivering of notifications. In this model, the evaluation of alert rules is done in the alert generator and the delivering of notifications is done in the alert receiver. In Grafana Alerting, the alert generator is the Scheduler and the receiver is the Alertmanager.
When running multiple instances of Grafana, all alert rules are evaluated on all instances. You can think of the evaluation of alert rules as being duplicated by the number of running Grafana instances. This is how Grafana Alerting makes sure that as long as at least one Grafana instance is working, alert rules are still be evaluated and notifications for alerts are still sent.
While the alert generator evaluates all alert rules on all instances, the alert receiver makes a best-effort attempt to avoid duplicate notifications. The alertmanagers use a gossip protocol to share information between them to prevent sending duplicated notifications.
Alertmanager chooses availability over consistency, which may result in occasional duplicated or out-of-order notifications. It takes the opinion that duplicate or out-of-order notifications are better than no notifications.
Alertmanagers also gossip silences, which means a silence created on one Grafana instance is replicated to all other Grafana instances. Both notifications and silences are persisted to the database periodically, and during graceful shut down.
Since gossiping of notifications and silences uses both TCP and UDP port `9094`, ensure that each Grafana instance is able to accept incoming connections on these ports.
**To enable high availability support:**
1. In your custom configuration file ($WORKING_DIR/conf/custom.ini), go to the `[unified_alerting]` section.
1. Set `[ha_peers]` to the number of hosts for each Grafana instance in the cluster (using a format of host:port), for example, `ha_peers=10.0.0.5:9094,10.0.0.6:9094,10.0.0.7:9094`.
1. Set `[ha_listen_address]` to the instance IP address using a format of `host:port` (or the [Pod's](https://kubernetes.io/docs/concepts/workloads/pods/) IP in the case of using Kubernetes).
1. Set `[ha_advertise_address]` to the instance's hostname or IP address in the format "host:port". Use this setting when the instance is behind NAT (Network Address Translation), such as in Docker Swarm or Kubernetes service, where external and internal addresses differ. This address helps other cluster instances communicate with it. The setting is optional.
1. Set `[ha_peer_timeout]` in the `[unified_alerting]` section of the custom.ini to specify the time to wait for an instance to send a notification via the Alertmanager. The default value is 15s, but it may increase if Grafana servers are located in different geographic regions or if the network latency between them is high.
As an alternative to Memberlist, you can configure Redis to enable high availability. Redis standalone, Redis Cluster and Redis Sentinel modes are supported.
Memberlist is the preferred option for high availability. Use Redis only in environments where direct communication between Grafana servers is not possible, such as when TCP or UDP ports are blocked.
1. Set `ha_redis_address` to the Redis server address or addresses Grafana should connect to. It can be a single Redis address if using Redis standalone, or a list of comma-separated addresses if using Redis Cluster or Sentinel.
1. Optional: Set `ha_redis_cluster_mode_enabled` to `true` if you are using Redis Cluster.
1. Optional: Set `ha_redis_sentinel_mode_enabled` to `true` if you are using Redis Sentinel. Also set `ha_redis_sentinel_master_name` to the Redis Sentinel master name.
1. Optional: Set the username and password if authentication is enabled on Redis Sentinel using `ha_redis_sentinel_username` and `ha_redis_sentinel_password`.
1. Optional: Set `ha_redis_prefix` to something unique if you plan to share the Redis server with multiple Grafana instances.
1. Optional: Set `ha_redis_tls_enabled` to `true` and configure the corresponding `ha_redis_tls_*` fields to secure communications between Grafana and Redis with Transport Layer Security (TLS).
1. Set `[ha_advertise_address]` to `ha_advertise_address = "${POD_IP}:9094"` This is required if the instance doesn't have an IP address that is part of RFC 6890 with a default route.
1. You can expose the Pod IP [through an environment variable](https://kubernetes.io/docs/tasks/inject-data-application/environment-variable-expose-pod-information/) via the container definition.
When running multiple Grafana instances, all alert rules are evaluated on every instance. This multiple evaluation of alert rules is visible in the [state history](ref:state-history) and provides a straightforward way to verify that your high availability configuration is working correctly.
If using a mix of `execute_alerts=false` and `execute_alerts=true` on the HA nodes, since the alert state is not shared amongst the Grafana instances, the instances with `execute_alerts=false` do not show any alert status.
The HA settings (`ha_peers`, etc.) apply only to communication between alertmanagers, synchronizing silences and attempting to avoid duplicate notifications, as described in the introduction.
| alertmanager_cluster_members | Number indicating current number of members in cluster. |
| alertmanager_cluster_messages_received_total | Total number of cluster messages received. |
| alertmanager_cluster_messages_received_size_total | Total size of cluster messages received. |
| alertmanager_cluster_messages_sent_total | Total number of cluster messages sent. |
| alertmanager_cluster_messages_sent_size_total | Total number of cluster messages received. |
| alertmanager_cluster_messages_publish_failures_total | Total number of messages that failed to be published. |
| alertmanager_cluster_pings_seconds | Histogram of latencies for ping messages. |
| alertmanager_cluster_pings_failures_total | Total number of failed pings. |
| alertmanager_peer_position | The position an Alertmanager instance believes it holds, which defines its role in the cluster. Peers should be numbered sequentially, starting from zero. |
You can confirm the number of Grafana instances in your alerting high availability setup by querying the `alertmanager_cluster_members` and `alertmanager_peer_position` metrics.
Note that these alerting high availability metrics are exposed via the `/metrics` endpoint in Grafana, and are not automatically collected or displayed. If you have a Prometheus instance connected to Grafana, add a `scrape_config` to scrape Grafana metrics and then query these metrics in Explore.
```yaml
- job_name: grafana
honor_timestamps: true
scrape_interval: 15s
scrape_timeout: 10s
metrics_path: /metrics
scheme: http
follow_redirects: true
static_configs:
- targets:
- grafana:3000
```
For more information on monitoring alerting metrics, refer to [Alerting meta-monitoring](ref:meta-monitoring). For a demo, see [alerting high availability examples using Docker Compose](https://github.com/grafana/alerting-ha-docker-examples/).
In high-availability mode, each Grafana instance runs its own pre-configured alertmanager to handle alert notifications.
When multiple Grafana instances are running, all alert rules are evaluated on each instance. By default, each instance sends firing alerts to its respective alertmanager. This results in notification handling being duplicated across all running Grafana instances.
Alertmanagers in HA mode communicate with each other to coordinate notification delivery. However, this setup can sometimes lead to duplicated or out-of-order notifications. By design, HA prioritizes sending duplicate notifications over the risk of missing notifications.
To avoid duplicate notifications, you can configure a shared alertmanager to manage notifications for all Grafana instances. For more information, refer to [add an external alertmanager](/docs/grafana/<GRAFANA_VERSION>/alerting/set-up/configure-alertmanager/).
