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Worker Affinity
Temporal
Temporal logoTemporal · Feature trail

Worker Affinity

1 post · May 2026

What this trail covers

Worker Affinity with Task Queues allows ensuring that multiple Activities within a workflow execute on the same Worker. This is achieved by using a combination of shared and unique task queues. The workflow first discovers an available worker via a shared queue and then routes all subsequent activities to that worker's unique queue, maintaining data locality for scenarios like file processing, ML model caching, and database connection pooling. This post details how to route specialized workloads.

All Temporal trails
  1. May 2026Route Specialized Workloads with Task QueuesThis post details how to route specialized workloads with diverse resource requirements (e.g., GPU-intensive ML, video processing, data analytics) by using separate Task Queues for different Worker types. This prevents wasted resources, inefficient usage, and conflicts between dependencies, building upon the existing Worker Affinity feature.
  2. May 2026Worker Affinity with Task QueuesThis post details the Temporal Validated Pattern for ensuring Activity execution on the same Worker using Worker-specific Task Queues. It explains how a shared queue is used to discover an available Worker's unique queue name, and how subsequent Activities are routed to that unique queue to maintain data locality for scenarios like file processing, ML model caching, and database connection pooling.
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What this trail covers

Worker Affinity with Task Queues allows ensuring that multiple Activities within a workflow execute on the same Worker. This is achieved by using a combination of shared and unique task queues. The workflow first discovers an available worker via a shared queue and then routes all subsequent activities to that worker's unique queue, maintaining data locality for scenarios like file processing, ML model caching, and database connection pooling. This post details how to route specialized workloads.

All Temporal trails

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