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Service health

Temporal Cloud metrics help monitor the Service health of production deployments. This documentation covers best practices for monitoring Service health.

Monitor availability issues​

When you see a sudden drop in Worker resource utilization, verify whether Temporal Cloud's API is showing increased latency and error rates.

Reference Metrics​

This metric measures latency for SignalWithStartWorkflowExecution, SignalWorkflowExecution, StartWorkflowExecution operations. These operations are mission critical and never throttled. This metric is a good indicator of your lowest possible latency.

Prometheus Query for this Metric​

P99 service lag (histogram):

histogram_quantile(0.99, sum(rate(temporal_cloud_v0_service_latency_bucket[$__rate_interval])) by (temporal_namespace, operation, le))

Monitor Temporal Service errors​

Check for Temporal Service gRPC API errors. Note that Service API errors are not equivalent to guarantees mentioned in the Temporal Cloud SLA.

Reference Metrics​

Prometheus Query for this Metric​

Measure your daily average errors over 10-minute windows:

avg_over_time((
    (

        (
            sum(increase(temporal_cloud_v0_frontend_service_request_count{temporal_namespace=~"$namespace", operation=~"StartWorkflowExecution|SignalWorkflowExecution|SignalWithStartWorkflowExecution|RequestCancelWorkflowExecution|TerminateWorkflowExecution"}[10m]))
            -
            sum(increase(temporal_cloud_v0_frontend_service_error_count{temporal_namespace=~"$namespace", operation=~"StartWorkflowExecution|SignalWorkflowExecution|SignalWithStartWorkflowExecution|RequestCancelWorkflowExecution|TerminateWorkflowExecution"}[10m]))
        )
        /
        sum(increase(temporal_cloud_v0_frontend_service_request_count{temporal_namespace=~"$namespace", operation=~"StartWorkflowExecution|SignalWorkflowExecution|SignalWithStartWorkflowExecution|RequestCancelWorkflowExecution|TerminateWorkflowExecution"}[10m]))
    )
    
    or vector(1)

    )[1d:10m])

Monitor multi-region Namespace replication lag​

Replication lag refers to the transmission delay of Workflow updates and history events from the active region to the standby region. Always check the metric replication lag before initiating a failover. A forced failover when there is a large replication lag has a higher likelihood of rolling back Workflow progress.

Who owns the replication lag? Temporal owns replication lag.

What guarantees are available? There is no SLA for replication lag. Temporal recommends that customers do not trigger failovers except for testing or emergency situations. Multi-region's four-9 guarantee SLA means Temporal will handle failovers and ensure high availability. Temporal also monitors replication lag. Customer who decide to trigger failovers should look at this metric before moving forward.

If the lag is high, what should you do? We don't expect users to failover. Please contact Temporal support if you feel you have a pressing need.

Where can you read more? See multi-region Namespaces.

Reference Metrics​

Prometheus Query for this Metric​

P99 replication lag (histogram):

histogram_quantile(0.99, sum(rate(temporal_cloud_v0_replication_lag_bucket[$__rate_interval])) by (temporal_namespace, le))

Average replication lag:

sum(rate(temporal_cloud_v0_replication_lag_sum[$__rate_interval])) by (temporal_namespace)
/
sum(rate(temporal_cloud_v0_replication_lag_count[$__rate_interval])) by (temporal_namespace)