temporal

name: temporal description: "Design and implement durable workflows using Temporal.io. Use this when building resilient, long-running processes, AI agent orchestration, or any workflow that needs to survive failures."

Temporal Workflow Design

Overview

Help design and implement durable workflows using Temporal.io - an open-source platform for building reliable applications that automatically recover from failures.

When to Use Temporal

Long-running processes: Multi-step workflows that span hours, days, or weeks
AI/Agent orchestration: Resilient AI pipelines that need state management
Order fulfillment: Maintain transaction integrity across service failures
Human-in-the-loop: Workflows requiring human approval steps
Financial transactions: Durable ledgers tracking transactions reliably
CI/CD pipelines: Deployments with built-in retries and rollbacks

Core Concepts

Workflows: Durable functions that define the overall process. They automatically capture state at each step and resume from failures.

Activities: Individual tasks within a workflow (API calls, database operations, file processing). These are the units that can fail and be retried.

Workers: Processes that execute workflows and activities. They poll task queues for work.

Signals: External inputs that can modify workflow behavior mid-execution.

Queries: Read-only operations to inspect workflow state without affecting execution.

Task Queues: Named queues that route work to appropriate workers.

Design Process

1. Identify the workflow boundary:

What triggers the workflow?
What's the final outcome?
How long might it run?

2. Break into activities:

What are the discrete steps?
Which steps can fail and need retries?
What are the retry policies for each?

3. Define state and signals:

What state needs to persist between steps?
What external events need to modify the workflow?
What information should be queryable?

4. Plan failure modes:

What happens if an activity fails permanently?
Are there compensation/rollback requirements?
How should timeouts be handled?

Supported Languages

TypeScript/JavaScript
Python
Go
Java
C# (.NET)
PHP
Ruby

Implementation Patterns

Saga Pattern: Long-running transactions with compensation on failure.

State Machine: Workflows that transition between defined states.

Pipeline: Sequential processing with optional parallelization.

Fan-out/Fan-in: Parallel activity execution with aggregated results.

Polling: Periodic checks until a condition is met.

Human-in-the-Loop: Wait for external signals (approvals, reviews).

Best Practices

Keep workflows deterministic - no random values, current time, or I/O in workflow code
Put all non-deterministic operations in activities
Use meaningful workflow and activity names
Set appropriate retry policies per activity type
Use timeouts at both workflow and activity levels
Design for idempotency in activities
Use versioning for workflow updates in production