Inngest

Inngest

Durable execution platform for reliable workflows and AI agents.

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Overview

What is Inngest?

Inngest is an event-driven durable execution platform that helps developers build reliable background jobs, workflows, scheduled tasks, and AI-powered applications without managing separate queues or worker infrastructure. Developers can add Inngest functions and steps to existing TypeScript, Python, or Go applications, while the platform handles automatic retries, state persistence, concurrency, throttling, scheduling, and observability. It is also designed for AI workflows and agents, allowing multi-step LLM processes to run reliably even when APIs fail, requests take a long time, or human approval is required.
Deep dive

More about Inngest

How to Get Started?

  1. Visit the Inngest website.
  2. Create an account or start with the free plan.
  3. Install the Inngest SDK for your preferred language.
  4. Create functions and define triggers and steps.
  5. Connect Inngest with your application.
  6. Test and monitor your workflows using the development server and observability tools

Pricing Info

  • Hobby: Free, with 50,000 executions/month.
  • Pro: Starts at $99/month, with 1 million executions included.
  • Enterprise: Custom pricing.
  • A free plan is available without a credit card.
  • Pricing: Prices are subject to change. Check the official website for the latest pricing and plan details.

Use Cases

  • AI agent workflows
  • Multi-step AI pipelines
  • Background jobs
  • Scheduled and cron jobs
  • Webhooks and event processing
  • Data synchronization
  • Payment and transaction workflows

Do’s & Don’ts

Do’s

  • Use it for long-running and background workflows.
  • Break complex processes into independent steps.
  • Use retries and checkpoints for failure-prone tasks.
  • Use flow controls for high-volume workloads.
  • Monitor workflow execution through traces and metrics.

Don’ts

  • Don’t treat automatic retries as a replacement for proper error handling.
  • Don’t run untested AI workflows in production.
  • Don’t ignore concurrency limits for multi-tenant applications.
  • Don’t expose sensitive data unnecessarily in workflow logs.
The verdict

Pros & cons

Pros

Handles retries and state automatically.

Reduces the need to manage queues and workers.

Strong support for AI workflows and agents.

Provides detailed workflow observability.

Supports multiple programming languages.

Open-source and self-hosting options are available

Cons

Primarily aimed at developers.

Requires programming knowledge to build workflows.

Usage-based pricing can increase with scale.

Complex workflows may require understanding of durable execution concepts.

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