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Temporal

Deploy Temporal on Render with this template. Get a production-ready cluster with independent autoscaling and advanced visibility via Elasticsearch.

Why deploy Temporal on Render?

Temporal is a durable execution platform that manages the state, retries, and orchestration of long-running workflows and distributed systems. It solves the problem of building reliable applications that need to handle failures, timeouts, and complex multi-step processes without manually implementing retry logic, state persistence, or recovery mechanisms.

This template deploys a complete Temporal cluster with eight interconnected services—frontend, history, matching, and worker components—plus Elasticsearch for advanced visibility, two managed Postgres databases, and a sample Go app to trigger workflows. Setting this up manually means configuring service discovery between components, wiring database connections, and getting the auto-setup scripts right; here it's all pre-configured to work together on deploy. Each Temporal service runs as a separate Render service, so you can independently scale matching or history based on actual load rather than scaling the entire cluster.

Architecture

What you can build

After deploying, you'll have a production-ready Temporal cluster with independently scalable services and Elasticsearch-backed visibility for querying workflow state. The template includes a sample Go app so you can immediately trigger and execute workflows. You can use this as a foundation for building durable, long-running workflows without managing the orchestration infrastructure yourself.

Key features

  • Independent service autoscaling: Each Temporal service (frontend, matching, history, worker) can be scaled independently based on workload demands.
  • Elasticsearch advanced visibility: Includes pre-configured Elasticsearch integration enabling advanced workflow search and filtering capabilities.
  • Production-ready cluster setup: Provides a complete multi-service Temporal deployment architecture designed for production use on Render.
  • Example Go workflow app: Includes a sample Go application demonstrating how to trigger and execute Temporal workflows.
  • One-click Render deployment: Configured with render.yaml for automated infrastructure provisioning via Render's deploy button.

Use cases

  • Backend engineer deploys fault-tolerant workflow orchestration without managing infrastructure
  • Platform team runs autoscaling Temporal cluster with Elasticsearch-backed workflow visibility
  • DevOps engineer migrates long-running payment workflows to production-ready managed hosting
  • Startup founder ships reliable order processing pipelines using pre-configured Go example

What's included

Service
Type
Purpose
esdata
Private Service
Application service
temporal-frontend
Private Service
Serves the user interface
temporal-history
Private Service
Application service
temporal-matching
Private Service
Application service
temporal-worker
Private Service
Application service
temporal-ui
Private Service
Application service
app-workflow-trigger
Web Service
Application service
app-worker
Background Worker
Application service
temporal-db
PostgreSQL
Primary database
temporal-shared
PostgreSQL
Primary database

Next steps

  1. Open the Temporal Web UI service URL — You should see the Temporal dashboard with the default namespace listed and no workflow executions yet
  2. Test the example Go worker by triggering a workflow using the Temporal CLI or SDK against your frontend service URL — You should see the workflow appear in the Web UI with a 'Completed' status within a few seconds
  3. Configure your application's Temporal client to connect to the frontend service URL and run a sample workflow — You should see the workflow execution logged in the Web UI's workflow list with full execution history available

Resources

Stack

go
elasticsearch

Tags

autoscaling
microservices
distributed systems
workflow engine