Temporal Serverless Workers on Cloud Run: queue-driven autoscaling, scale to zero
rseroter · x · 2026-10-16
Google Cloud launched Temporal Serverless Workers on Cloud Run (preview), targeting the awkward fit between Temporal's pull-based workers and request-driven serverless platforms.
The problem: Temporal workers poll for tasks instead of serving requests, so teams typically run worker fleets on Kubernetes/VMs — continuously paying for compute, tuning autoscalers, and still lagging behind bursts due to metrics delay.
How it works:
- Workers deploy as a Cloud Run worker pool: no public endpoint, CPU allocated for each instance's full lifetime
- Temporal Cloud sizes the pool against task-queue backlog: scales out ahead of demand, holds capacity 90s after the backlog clears, then steps down to the minimum
- Scales to zero when idle; no cluster or autoscaler to manage, worker code unchanged
A direct ops/cost simplification for teams orchestrating AI agent workloads on Temporal.
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