Custom Chart Debug Page

This count excludes transaction restart/abort errors. However, it will include other errors expected during normal operation, such as ConditionFailedError. This metric is thus not an indicator of KV health.

This measures requests already addressed to a single replica, from the moment at which they arrive at the internal gRPC endpoint to the moment at which the response (or an error) is returned.

This latency includes in particular commit waits, conflict resolution and replication, and end-users can easily produce high measurements via long-running transactions that conflict with foreground traffic. This metric thus does not provide a good signal for understanding the health of the KV layer.

A request is considered to have executed 'successfully' if it either returns a result or a transaction restart/abort error.

This measurement is taken on the Raft apply loops of all Replicas (leaders and followers alike), meaning that it does not measure the number of Raft commands proposed (in the hypothetical extreme case, all Replicas may apply all commands through snapshots, thus not increasing this metric at all). Instead, it is a proxy for how much work is being done advancing the Replica state machines on this node.

This metric is misnamed: it measures the latency for applying a batch of committed Raft commands to a Replica state machine. This requires only non-durable I/O (except for replication configuration changes).

Note that a "batch" in this context is really a sub-batch of the batch received for application during raft ready handling. The 'raft.process.applycommitted.latency' histogram is likely more suitable in most cases, as it measures the total latency across all sub-batches (i.e. the sum of commandcommit.latency for a complete batch).

This measures the latency of durably committing a group of newly received Raft entries as well as the HardState entry to disk. This excludes any data processing, i.e. we measure purely the commit latency of the resulting Engine write. Homogeneous bands of p50-p99 latencies (in the presence of regular Raft traffic), make it likely that the storage layer is healthy. Spikes in the latency bands can either hint at the presence of large sets of Raft entries being received, or at performance issues at the storage layer.

This is the sum of the measurements passed to the raft.process.handleready.latency histogram.

This gauge provides a view of the aggregate number of log entries the Raft leaders on this node think the followers are behind. Since a raft leader may not always have a good estimate for this information for all of its followers, and since followers are expected to be behind (when they are not required as part of a quorum) and the aggregate thus scales like the count of such followers, it is difficult to meaningfully interpret this metric.

A Range will backpressure (roughly) non-system traffic when the range is above the configured size until the range splits. When the rate of this metric is nonzero over extended periods of time, it should be investigated why splits are not occurring.

Note that this is not a good signal for KV health. The remote side of the RPCs tracked here may experience contention, so an end user can easily cause values for this metric to be emitted by leaving a transaction open for a long time and contending with it using a second transaction.

This gauge registering a nonzero value usually indicates range or replica unavailability, and should be investigated. In the common case, we also expect to see 'requests.slow.raft' to register a nonzero value, indicating that the lease requests are not getting a timely response from the replication layer.

An (evaluated) request has to pass through the replication layer, notably the quota pool and raft. If it fails to do so within a highly permissive duration, the gauge is incremented (and decremented again once the request is either applied or returns an error).

A nonzero value indicates range or replica unavailability, and should be investigated.

This only reflects successful heartbeats and measures gRPC overhead as well as possible head-of-line blocking. Elevated values in this metric may hint at network issues and/or saturation, but they are no proof of them. CPU overload can similarly elevate this metric. The operator should look towards OS-level metrics such as packet loss, retransmits, etc, to conclusively diagnose network issues. Heartbeats are not very frequent (~seconds), so they may not capture rare or short-lived degradations.

Dividing this Gauge by rpc.connection.healthy gives an approximation of average latency, but the top-level round-trip-latency histogram is more useful. Instead, users should consult the label families of this metric if they are available (which requires prometheus and the cluster setting 'server.child_metrics.enabled'); these provide per-peer moving averages.

This metric does not track failed connection. A failed connection's contribution is reset to zero.

This includes both the event in which a healthy connection terminates as well as unsuccessful reconnection attempts.

Connections that are terminated as part of local node shutdown are excluded. Decommissioned peers are excluded.

On the prometheus endpoint scraped with the cluster setting 'server.child_metrics.enabled' set, the constituent parts of this metric are available on a per-peer basis and one can read off for how long a given peer has been connected

On the prometheus endpoint scraped with the cluster setting 'server.child_metrics.enabled' set, the constituent parts of this metric are available on a per-peer basis and one can read off for how long a given peer has been unreachable