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worker performance refactor
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INFORMATION-ARCHITECTURE.md

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@@ -152,8 +152,8 @@ These cross-cutting pages live outside any SDK folder:
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- `plugins-guide.mdx` — How to build plugins; architecture guidance.
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- `integrations.mdx` — Hub page linking to SDK-specific integration guides.
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- `safe-deployments.mdx` — Workflow code deployment strategies, replay testing.
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- `worker-performance.mdx` — Performance tuning, slot suppliers, metrics.
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- `worker-tuning-reference.mdx` — Reference tables for worker config.
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- `worker-performance/` — Performance tuning hub (concepts) plus subpages for metrics, configuration, runtime tuning, Workflow cache, and Task Queue performance.
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- `worker-tuning-reference.mdx` — Reference tables for worker config (sidebar: under Worker performance).
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- `task-queue-priority-fairness.mdx` — Task queue priority and fairness features.
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- `activity-retry-simulator.mdx` — Interactive tool for visualizing retry behavior.
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- `run-a-development-server.mdx` — Installing and running the Temporal CLI dev server.
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- **SDK coverage gaps.** Nexus is missing from PHP and Ruby. Interceptors docs exist only for Python and TypeScript.
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Serverless worker guides exist only for Go, Python, and TypeScript. These gaps may reflect SDK support status, but
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that is not documented anywhere in the section.
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- **Cross-cutting content placement.** Pages like `safe-deployments.mdx`, `worker-performance.mdx`, and
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- **Cross-cutting content placement.** Pages like `safe-deployments.mdx`, `worker-performance/`, and
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`worker-tuning-reference.mdx` straddle Develop and Deploy to production. `safe-deployments` in particular is about
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deployment strategy (versioning vs. patching), which reads more like production deployment guidance.
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- **Setup page naming is inconsistent.** Most SDKs use `set-up-your-local-<language>`, TypeScript uses

docs/best-practices/worker-alerting.mdx

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:::note
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`worker_task_slots_available` reports meaningful values only with fixed-size slot suppliers.
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It can't be used with resource-based slot suppliers. See [Slot availability metrics](/develop/worker-performance#slot-availability-metrics).
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It can't be used with resource-based slot suppliers. See [Slot availability metrics](/develop/worker-performance/metrics#slot-availability-metrics).
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If your Workers use resource-based tuning, skip this one and let schedule-to-start latency tell you when capacity is short.
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:::

docs/best-practices/worker.mdx

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how Task slots are assigned to different Task types. Refer to
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[Slot Suppliers](/develop/worker-performance#slot-suppliers) for more details.
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- **Sticky cache size**: Controls the size of the sticky cache for Workflow Executions. Larger caches reduce replay
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overhead but consume more memory. Refer to [Workflow Cache Tuning](/develop/worker-performance#workflow-cache-tuning)
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overhead but consume more memory. Refer to [Workflow Cache Tuning](/develop/worker-performance/workflow-cache)
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for more details.
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- **Poller counts**: Controls the number of pollers for Tasks. We recommend you use the Poller Autoscaling feature to
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automatically adjust the number of pollers based on your workload. Refer to
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[Configuring Poller Options](/develop/worker-performance#configuring-poller-options) for more details.
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[Configuring Poller Options](/develop/worker-performance/configuration#configuring-poller-options) for more details.
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Use the metrics listed in [Interpret metrics as a whole](#interpret-metrics-as-a-whole) to guide your tuning decisions.
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docs/cloud/metrics/openmetrics/metrics-reference.mdx

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It can also reset to zero on an idle Task Queue. If no Worker polls, no new Tasks are added, and no other Task Queue calls occur (such as `DescribeTaskQueue` or `UpdateTaskQueueConfig`) for approximately 5 minutes. The Task Queue is unloaded from memory.
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Infrequent metadata updates and database time-to-live settings can also cause this metric to drift at a smaller magnitude.
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See [backlog accuracy limitations](/develop/worker-performance#backlog-accuracy-limitations) for details.
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See [backlog accuracy limitations](/develop/worker-performance/task-queues#backlog-accuracy-limitations) for details.
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:::
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| Label | Description |

docs/cloud/worker-health.mdx

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- Verify that your Worker setup is optimized for your instance:
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- Check the system CPU usage against `task_slots` and adjust `maxConcurrentWorkflowTaskExecutionSize` and `maxConcurrentActivityExecutionSize` settings as necessary.
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- Check the system memory usage against `sticky_cache_size` and adjust sticky cache size as necessary.
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- For a detailed explanation of settings, see the [Worker Performance](/develop/worker-performance#task-queues-processing-tuning) section.
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- For a detailed explanation of settings, see the [Worker Performance](/develop/worker-performance/task-queues#task-queues-processing-tuning) section.
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- Increase the Worker config for concurrent pollers for Workflow or Activity `task_slots`, if your Worker resources can accommodate the increased load.
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- Reference [Worker Performance > Poller Count](/develop/worker-performance#poller-count).
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- Reference [Worker Performance > Poller Count](/develop/worker-performance/task-queues#poller-count).
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- Increase the number of available Workers.
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:::warning

docs/develop/go/client/temporal-client.mdx

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You can configure Task Queues that are host-specific, Worker-specific or Workflow-specific to distribute your
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application load. For more information, refer to
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[Task Queues Processing Tuning](/develop/worker-performance#task-queues-processing-tuning) and
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[Task Queues Processing Tuning](/develop/worker-performance/task-queues#task-queues-processing-tuning) and
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[Worker Versioning](/worker-versioning).
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### Set custom Workflow Id {/* #workflow-id */}

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