Workflow Orchestration

Introduction

Orchestration = the engine that runs, retries, persists and observes the workflow. Don't roll your own — use Inngest, Temporal, LangGraph, Vercel Workflow, or AWS Step Functions.

Beginner analogy: Kubernetes for AI workflows — schedules and supervises tasks so you don't have to.

Understanding the topic

Core concepts:

• Durable execution survives crashes and restarts.
• Automatic retries with back-off.
• Built-in observability (timelines, traces).
• Versioning of workflow definitions.
• Human-in-the-loop pauses.

Syntax reference

Visual workflow / architecture:

Workflow def ─► Orchestrator ─► Worker pool
                          │
                          ▼
                      State store
                          │
                          ▼
                      Trace UI

Real-world use

Inngest powers many AI startups; Temporal underpins large fintech AI ops; LangGraph for in-process orchestration.

Best practices

• Pick orchestration before scale, not after.
• Version workflows from day one.

Common mistakes

• DIY orchestration — you'll rebuild Temporal poorly.

Hands-on exercise

Interview preparation — practice these questions:

• Q1. Three benefits of an orchestrator.
• Q2. Difference between Temporal and LangGraph.
• Q3. Scenario: your workflow steps need to survive a server restart. How?