Temporal — Durable Workflow Execution Platform

What it is

Temporal is an open-source platform for building reliable distributed applications. It provides durable execution -- your application code runs to completion even through process crashes, server restarts, and network failures. Instead of writing retry logic, timeout handling, and state management, you write normal code and Temporal handles the durability.

Temporal is designed for backend engineers building long-running processes like payment flows, order fulfillment, user onboarding sequences, data pipelines, and any workflow that spans multiple services and must not silently fail.

How it saves time or tokens

Temporal eliminates the need to write and maintain infrastructure code for reliability. Without Temporal, a multi-step payment flow requires message queues, dead-letter queues, retry policies, idempotency keys, state machines, and monitoring for each step. With Temporal, you write sequential code and the platform handles all failure modes. SDKs are available for Go, TypeScript, Python, Java, and .NET.

How to use

1. Install the Temporal CLI: brew install temporal (macOS) or download from the releases page.
2. Start a local dev server: temporal server start-dev and open the Web UI at http://localhost:8233.
3. Write a workflow function in your language of choice, register it with a worker, and start it via the SDK or CLI.

Example

from temporalio import workflow, activity
import asyncio

@activity.defn
async def send_email(to: str, subject: str) -> str:
    # Actual email sending logic
    return f'Email sent to {to}'

@activity.defn
async def charge_payment(amount: float) -> str:
    # Payment processing logic
    return f'Charged ${amount}'

@workflow.defn
class OrderWorkflow:
    @workflow.run
    async def run(self, order_id: str) -> str:
        # Step 1: Charge payment (retried automatically on failure)
        await workflow.execute_activity(
            charge_payment, 99.99,
            start_to_close_timeout=timedelta(seconds=30)
        )
        # Step 2: Send confirmation email
        await workflow.execute_activity(
            send_email, 'user@example.com', 'Order confirmed',
            start_to_close_timeout=timedelta(seconds=10)
        )
        return f'Order {order_id} completed'

Related on TokRepo

• AI tools for automation -- workflow automation tools and platforms
• AI tools for coding -- developer productivity tools

Common pitfalls

• Making workflow code non-deterministic. Temporal replays workflow history to recover state, so workflows must be deterministic. Do not use random numbers, current time, or external API calls directly in workflow code -- use activities instead.
• Not setting appropriate timeouts for activities. Without timeouts, a stuck activity blocks the entire workflow indefinitely. Always set start_to_close_timeout and consider schedule_to_close_timeout.
• Running the dev server in production. The temporal server start-dev command is for local development only. Production deployments require Temporal Cloud or a self-hosted cluster with persistence (PostgreSQL, MySQL, or Cassandra).