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docs/cloud/high-availability/failovers.mdx

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@@ -381,7 +381,7 @@ Failover testing (also known as "<ToolTipTerm term="trigger testing" />)" can:
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Manual testing confirms the failover mechanism works as expected, so your system handles incidents effectively.
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- **Assess replication lag**:
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In multi-region deployment, monitoring [replication lag](/cloud/high-availability/monitoring#replication-lag-metric) between regions is crucial.
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In multi-region deployment, monitoring [replication lag](/cloud/metrics/openmetrics/metrics-reference#temporal_cloud_v1_replication_lag_p99) between regions is crucial.
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Check the lag before initiating a failover to avoid rolling back Workflow progress.
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This is less important when using isolation domains as failover is usually instantaneous.
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Manual testing helps you practice this critical step and understand its impact.

docs/cloud/metrics/general-setup.mdx

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After the page refreshes, the new metrics endpoint appears below **Endpoint**, in the form `https://<account-id>.tmprl.cloud/prometheus`.
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Use the endpoint to configure your observability tool.
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For example, if you use Grafana, see [Grafana data sources configuration](/cloud/metrics/prometheus-grafana#grafana-data-sources-configuration).
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For example, if you use Grafana, see [Grafana data source configuration](/cloud/metrics/prometheus-grafana#grafana-data-source-configuration).
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You can also query via the [Prometheus HTTP API](https://prometheus.io/docs/prometheus/latest/querying/api/) at URLs like:
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docs/cloud/metrics/openmetrics/migration-guide.mdx

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| Old Metric (v0) | New Metric (v1) | New Labels |
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| ------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------- | ---------- |
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| `temporal_cloud_v0_service_latency_bucket temporal_cloud_v0_service_latency_count temporal_cloud_v0_service_latency_sum` | `temporal_cloud_v1_service_latency_p99 temporal_cloud_v1_service_latency_p95 temporal_cloud_v1_service_latency_p50` | `region` |
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| `temporal_cloud_v0_service_latency_bucket temporal_cloud_v0_service_latency_count temporal_cloud_v0_service_latency_sum` | `temporal_cloud_v1_service_latency_p99 temporal_cloud_v1_service_latency_p95 temporal_cloud_v1_service_latency_p50` | `region` |
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| `temporal_cloud_v0_replication_lag_bucket temporal_cloud_v0_replication_lag_count temporal_cloud_v0_replication_lag_sum` | `temporal_cloud_v1_replication_lag_p99 temporal_cloud_v1_replication_lag_p95 temporal_cloud_v1_replication_lag_p50` | `region` |
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#### Schedule Metrics
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| Old Metric (v0) | New Metric (v1) | New Labels |
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| -------------------------------------------------------- | -------------------------------------------------------- | ---------- |
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| `temporal_cloud_v0_schedule_action_success_count` | `temporal_cloud_v1_schedule_action_success_count` | `region` |
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| `temporal_cloud_v0_schedule_action_success_count` | `temporal_cloud_v1_schedule_action_success_count` | `region` |
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| `temporal_cloud_v0_schedule_buffer_overruns_count` | `temporal_cloud_v1_schedule_buffer_overruns_count` | `region` |
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| `temporal_cloud_v0_schedule_missed_catchup_window_count` | `temporal_cloud_v1_schedule_missed_catchup_window_count` | `region` |
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| `temporal_cloud_v0_schedule_rate_limited_count` | `temporal_cloud_v1_schedule_rate_limited_count` | `region` |

docs/cloud/metrics/reference.mdx

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#### temporal_cloud_v0_replication_lag_bucket
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A histogram of [replication lag](/cloud/high-availability/monitoring#replication-lag-metric) during a specific time interval for a Namespace with high availability.
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A histogram of [replication lag](/cloud/metrics/openmetrics/metrics-reference#temporal_cloud_v1_replication_lag_p99) during a specific time interval for a Namespace with high availability.
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Labels: temporal_account, temporal_namespace, le
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#### temporal_cloud_v0_replication_lag_count
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The [replication lag](/cloud/high-availability/monitoring#replication-lag-metric) count during a specific time interval for a Namespace with high availability.
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The [replication lag](/cloud/metrics/openmetrics/metrics-reference#temporal_cloud_v1_replication_lag_p99) count during a specific time interval for a Namespace with high availability.
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Labels: temporal_account, temporal_namespace
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#### temporal_cloud_v0_replication_lag_sum
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The sum of [replication lag](/cloud/high-availability/monitoring#replication-lag-metric) during a specific time interval for a Namespace with high availability.
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The sum of [replication lag](/cloud/metrics/openmetrics/metrics-reference#temporal_cloud_v1_replication_lag_p99) during a specific time interval for a Namespace with high availability.
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Labels: temporal_account, temporal_namespace
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### Schedule metrics {#schedule}

docs/cloud/nexus/limits.mdx

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- [Per-Workflow Nexus Operation limits](/cloud/limits#per-workflow-nexus-operation-limits) - 30 in-flight Operations per Workflow.
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- [Nexus Operation request timeout](/cloud/limits#nexus-operation-request-timeout) - Less than 10 seconds for a handler to process a start or cancel request.
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- [Nexus Operation duration limits](/cloud/limits#nexus-operation-duration-limits) - 60-day maximum ScheduleToClose duration.
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- [Per-Workflow callback limits](/cloud/limits#per-workflow-callback-limits) - 2000 callbacks per Workflow. Governs how many Nexus callers can attach to a handler Workflow.
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- [Per-Workflow callback limits](/cloud/limits#per-workflow-callback-limits) - 2000 callbacks per Workflow. Governs how many Nexus callers can attach to a handler Workflow.

docs/cloud/rto-rpo.mdx

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However, user actions on a Namespace can affect the recovery point. For example, suddenly spiking into much higher throughput than a Namespace has seen before could create a period of replication lag where the replica falls behind the active.
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Temporal provides a [replication lag](/cloud/high-availability/monitoring#replication-lag-metric) metric for each Namespace. This metric approximates the recovery point the Namespace would achieve in a worst case failure at that given moment.
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Temporal provides a [replication lag](/cloud/metrics/openmetrics/metrics-reference#temporal_cloud_v1_replication_lag_p99) metric for each Namespace. This metric approximates the recovery point the Namespace would achieve in a worst case failure at that given moment.
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:::note
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docs/develop/dotnet/standalone-activities.mdx

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Running a Worker for Standalone Activities is the same as running a Worker for Workflow Activities —
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you create a Worker, register the Activity, and run the Worker. The Worker doesn't need to know
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whether the Activity will be invoked from a Workflow or as a Standalone Activity. See [How to develop
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a Worker](/develop/dotnet/core-application#run-a-dev-worker) for more details on Worker setup and
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a Worker](/develop/dotnet/core-application#run-worker-process) for more details on Worker setup and
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configuration options.
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[src/StandaloneActivity/Program.cs](https://github.com/temporalio/samples-dotnet/blob/main/src/StandaloneActivity/Program.cs)

docs/develop/java/set-up.mdx

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String result = workflow.sayHello("Temporal");
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System.out.println("Workflow result: " + result);
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service.shutdown();
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service.awaitTermination(10, java.util.concurrent.TimeUnit.SECONDS);
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}
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}
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```

docs/encyclopedia/context-propagation.mdx

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Here are SDK-specific guides:
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- [Go](/develop/go/observability#context-propagation)
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- [Go](/develop/go/context-propagation)

docs/encyclopedia/temporal-service/temporal-service-configuration.mdx

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- [Temporal Cloud metrics reference](/cloud/metrics/)
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- [Set up Grafana with Temporal Cloud observability to view metrics](/cloud/metrics/prometheus-grafana#grafana-data-sources-configuration)
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- [Set up Grafana with Temporal Cloud observability to view metrics](/cloud/metrics/prometheus-grafana#grafana-data-source-configuration)
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On the self-hosted Temporal Service, expose Prometheus endpoints in your Temporal Service configuration and configure Prometheus to scrape metrics from the endpoints.
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You can then set up your observability platform (such as Grafana) to use Prometheus as a data source.

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