Serverless Workers for Cloud Run

7/30/2026

This post introduces Temporal Serverless Workers for Google Cloud Run, a new capability that leverages Cloud Run Worker Pools for automated scaling of Temporal workers. It details how Temporal monitors internal metrics to dynamically adjust worker capacity, removing the burden of manual autoscaling configuration for developers. The post explains the integration process, including deploying worker code as Docker containers and configuring Worker Pool specifications, and demonstrates the autoscaling behavior with metrics from Temporal Cloud and Cloud Run.

5/28/2026

This post announces the pre-release of Serverless Workers, which allow Temporal Workers to run on serverless compute, starting with AWS Lambda. Temporal Cloud will automatically manage the invocation, scaling, and shutdown of these workers based on workload volume and metrics, including scaling to zero.

2/24/2026

This post introduces Thand, an open-source implementation of the Serverless Workflows specification that adds extensions for Temporal capabilities, including Nexus. Thand enables distributed provisioning and access management by allowing Serverless Workflows to be routed to specific Temporal Workers and environments using 'providers' and custom Task Queues. It demonstrates how to use Serverless Workflows with Temporal for tasks like checking entitlements via gRPC, running Osquery on local devices, and provisioning AWS access, all while abstracting away the complexity of Task Queue management and Worker topology.

4/12/2025

This post announces the integration of KEDA (Kubernetes-based Event-Driven Autoscaling) with Temporal Workers. It details how KEDA's Temporal scaler can dynamically scale the number of Temporal worker pods based on the size of the Task Queue backlog. This provides benefits such as cost efficiency (scaling to zero), high throughput during traffic spikes, and operational simplicity. A demo application using the Order Management System (OMS) reference app is provided to showcase this functionality, visualizing Task Queue backlogs and worker pod scaling in real-time.

1/6/2025

This post updates the guidance for deploying Temporal Workers on Google Cloud Run by leveraging the new Cloud Run Worker Pools and CREMA (Cloud Run External Metrics Autoscaling). It details the configuration for Worker Pools, the use of a sidecar container with OpenTelemetry Collector for Prometheus metrics, and the configuration of CREMA for autoscaling based on Temporal Task Queue backlog. It also explains the scaling formula and provides CREMA configuration parameters.