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Task Queue Priority and Fairness

Task Queue Priority and Fairness

5
posts
2025–2026

Task Queue Priority and Fairness provide mechanisms to control task execution order and resource distribution within Temporal. Priority allows assigning integer levels (1-5) to Workflows and Activities to ensure higher-priority tasks are processed first. Fairness uses weighted round-robin scheduling based on Fairness Keys to ensure equitable resource distribution among tenants or logical groups, preventing monopolization of Workers. These features can be combined to support differentiated service levels. This post introduces a validated pattern for using separate Task Queues with rate limiting configuration to protect downstream APIs, leveraging `max_task_queue_activities_per_second`, `max_activities_per_second`, and `max_concurrent_activities` to prevent exceeding API rate limits.

2026

Rate-Limit Downstream APIs with Task Queues

5/25/2026

Introduces a validated pattern for rate-limiting downstream API calls by using separate Task Queues with specific rate limiting configurations (`max_task_queue_activities_per_second`, `max_activities_per_second`, `max_concurrent_activities`) to prevent exceeding external API rate limits and avoid errors, wasted execution, and account suspension.

Task Queue Priority and Fairness: Your Task Queue, your way

5/12/2026

Introduces Task Queue Priority and Fairness as Generally Available features. Priority allows assigning integer priority levels to Workflows and Activities for ordered execution. Fairness uses Fairness Keys and weights for weighted round-robin task dispatching within a Task Queue, ensuring equitable resource distribution among logical groups (e.g., tenants). The post details how to use these features in code (Python SDK example provided), their use cases, how they combine, and configuration steps for Temporal Cloud and self-hosted Temporal Server. Best practices for implementation and monitoring are also discussed.

Route Specialized Workloads with Task Queues

5/11/2026

This post details a Temporal Validated Pattern for routing specialized workloads using separate Task Queues. It explains how to create dedicated Worker pools for GPU-intensive ML workloads, standard CPU workloads, high-memory analytics, or specialized hardware to avoid wasted resources, inefficient usage, and dependency conflicts that arise when running all Activities on the same Worker type.

Durable Digest: March 2026

3/31/2026

Task Queue Priority and Fairness are now in Public Preview. This allows users to specify task dispatch order based on priority and use fairness keys for equitable resource distribution across task types.

2025

Durable Digest: April 2025

4/29/2025

This post announces the pre-release availability of Task Queue Priority, a feature that allows assigning integer levels (1-5) to Workflows, Activities, and Child Workflows to control their execution order.