w3ll1ngt commented on code in PR #13130: URL: https://github.com/apache/ignite/pull/13130#discussion_r3603421426
########## docs/_docs/perf-and-troubleshooting/general-perf-tips.adoc: ########## @@ -47,3 +47,345 @@ queries with JOINs at massive scale and expect significant performance benefits. * Adjust link:data-rebalancing[data rebalancing settings] to ensure that rebalancing completes faster when your cluster topology changes. +== How to assess cluster health + +Cluster health is a complex thing. Apache Ignite is capable of demonstrating great performance across different scenarios with varying loads. Therefore, in general terms, a healthy cluster is one whose behavior aligns with your expectations. However, there are some universal aspects that apply to all deployments and warrant attention. + +It is important to understand that a healthy cluster may undergo planned topology changes or temporary load spikes. + +The key properties are: +- The cluster serves operations allowed by its intended state. +- Data remains consistent (`idle_verify` passes, meaning partitions are intact and there are no conflicts). +- Expected nodes are present. +- No pending transactions and no split brain. +- No lost partitions. +- Transient activity such as rebalancing or queue growth converges instead of accumulating. + +But the thing is, there is no universal single health metric. + +Use several signals together. +For example, `SELECT 1` can confirm that a client or SQL query path is reachable, but it does not check user partitions, backup consistency, baseline membership, or all server nodes. +Similarly, `control.sh --cache idle_verify` is an important consistency check, but it is not a complete health check. + +=== Check the Intended State and Node Membership +Start with the link:monitoring-metrics/cluster-states[cluster state]. + +Run: + +[source,shell] +---- +./control.sh --state +---- + +Relevant output: + +[source,text] +---- +Command [STATE] started +Arguments: --state +-------------------------------------------------------------------------------- +Cluster state: ACTIVE +Command [STATE] finished with code: 0 +---- + +`ACTIVE` is expected for normal read-write operation. +`ACTIVE_READ_ONLY` is normal when read-only operation was intentionally enabled. +`INACTIVE` is acceptable only when it matches the current operation, for example planned maintenance; an inactive cluster does not serve the data workload. +The criterion is whether the actual state matches the state that was intentionally set for the deployment. + +If baseline topology is enabled, check the baseline as well: + +Run: + +[source,shell] +---- +./control.sh --baseline +---- + +Relevant output for a cluster where all baseline nodes are online: + +[source,text] +---- +Cluster state: ACTIVE +Current topology version: 3 +Baseline auto adjustment disabled: softTimeout=300000 + +Current topology version: 3 (Coordinator: ConsistentId=node-1, Order=1) + +Baseline nodes: + ConsistentId=node-1, State=ONLINE, Order=1 + ConsistentId=node-2, State=ONLINE, Order=2 + ConsistentId=node-3, State=ONLINE, Order=3 +-------------------------------------------------------------------------------- +Number of baseline nodes: 3 + +Other nodes not found. +---- + +If an online server node has joined the cluster but is not in the baseline, the command shows it under `Other nodes`: + +[source,text] +---- +Other nodes: + ConsistentId=node-4, Order=4 +Number of other nodes: 1 +---- + +The baseline contains server nodes that are intended to store data. +Client nodes are not part of the baseline. +An online server node in `Other nodes` is not always an error: the node may have been prepared intentionally but not yet introduced into the data topology. +If the node is expected to store data, first check the link:clustering/baseline-topology#baseline-topology-autoadjustment[baseline auto-adjustment policy] and the deployment plan, then use the documented baseline change procedure. +Changing the baseline can start link:data-rebalancing[rebalancing]. This is often not an easy procedure for a cluster with data in persistence storage. + +Frequent unexpected topology changes are not normal and usually indicate node instability, network issues, or misconfigured discovery. However, a temporary topology change does not make the cluster unhealthy by itself. +Server `JOIN`, `LEFT`, and `FAIL` events change cluster membership and the major topology version. +Cache start or stop, distributed cache creation, SQL table creation, and other affinity-changing events can change the minor affinity topology version without a node loss. +Planned events are normal. +Investigate unexpected repeated membership churn, node segmentation, network failures, or a partition map exchange that does not finish. Review Comment: Commands added, could be expanded with logs anyway.. Should we expand split-brain situations? It is kinda vague and misty in this doc from my point of view now -- This is an automated message from the Apache Git Service. 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