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docs(temporal): add composite metric parameters to temporal scaler docs #1714

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13 changes: 8 additions & 5 deletions content/docs/2.20/scalers/temporal.md
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Expand Up @@ -23,6 +23,8 @@ triggers:
buildId: 1.0.0 # optional
selectAllActive: "false" # optional
selectUnversioned: "false" # optional
includeRunningWorkflowCount: "true" # optional, default: true
workflowTaskQueueForCount: "workflow-task-queue" # optional
minConnectTimeout: "5" # optional
unsafeSsl: "false" # optional
tlsServerName: "custom-tls-servername" # optional
Expand All @@ -40,17 +42,18 @@ triggers:
- `buildId` - Build IDs identify Worker versions for Workflow versioning and task compatibility (Optional)
- `selectAllActive` - Include all active versions (Default:`false`, Optional)
- `selectUnversioned` - Include the unversioned queue (Default:`false`, Optional)
- `includeRunningWorkflowCount` - When `true`, the scaler uses backlog + running workflow count as the metric. This prevents premature scale-down when workers are fast and the backlog is often zero. (Default: `true`, Optional)
- `workflowTaskQueueForCount` - Task queue name used to scope the running workflow count query. Useful when scaling activity workers where the workflow task queue differs from the activity task queue. Falls back to `taskQueue` if not set. (Optional)
- `apiKeyFromEnv` - API key for authentication similar to `apiKey`, but read from an environment variable (Optional)
- `minConnectTimeout` - This is the minimum amount of time we are willing to give a connection to complete. (Default:`5`, Optional)
- `unsafeSsl` - Whether to allow unsafe SSL (Default: `false`, Optional)
- `tlsServerName` - The custom tls server name (Optional)

> 💡 **NOTE:** Activation based on backlog may not be reliable when scaling to zero.
> 💡 **NOTE:** Activation based on backlog alone may not be reliable when scaling to zero.
This approach fails to account for in-flight tasks or workloads with throughput too low to trigger a backlog.
Consequently, scaling to zero could result in undesirable behavior,
such as terminating resources and subsequently having to scale back up to handle queued tasks. To address these challenges, consider customizing the cooldownPeriod or scale-down behavior of the Horizontal Pod Autoscaler (HPA).
By fine-tuning the configurations, you can prevent premature scaling to zero,
ensuring that resources remain available for in-flight tasks or workloads with minimal throughput.
By default, `includeRunningWorkflowCount` is `true`, which adds the count of running workflows to the backlog metric.
This prevents premature scale-down when workers are fast and the backlog is often zero.
For additional protection, consider customizing the `cooldownPeriod` or scale-down behavior of the Horizontal Pod Autoscaler (HPA).


**Authentication Parameters:**
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