Inngest Flow Control

This covers all of Inngest's flow control primitives with a decision tree that actually helps. You get concurrency limits (including multi-tenant keying), throttling, rate limiting, debounce, priority queues, singleton modes, and event batching. The examples are practical: handling OpenAI rate limits with account-level concurrency, debouncing document saves after users stop typing, prioritizing VIP orders ahead in the queue. The quick decision guide at the top is genuinely useful for picking the right primitive. One thing to note is the TypeScript focus, though the concepts translate to Python and Go. If you're building event-driven systems that need backpressure or fairness guarantees, this is comprehensive.

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last updated: Aug 21, 2026

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$ npx -y skills add inngest/inngest-skills --skill inngest-flow-control --agent claude-code

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Inngest Flow Control

Master Inngest flow control mechanisms to manage resources, prevent overloading systems, and ensure application reliability. This skill covers all flow control options with prescriptive guidance on when and how to use each.

These skills are focused on TypeScript. For Python or Go, refer to the Inngest documentation for language-specific guidance. Core concepts apply across all languages.

Quick Decision Guide

"Limit how many run at once" → Concurrency
"Spread runs over time" → Throttling
"Block after N runs in a period" → Rate Limiting
"Wait for activity to stop, then run once" → Debounce
"Only one run at a time for this key" → Singleton
"Process events in groups" → Batching
"Some runs are more important" → Priority

Concurrency

When to use: Limit the number of executing steps (not function runs) to manage computing resources and prevent system overwhelm.

Key insight: Concurrency limits active code execution, not function runs. A function waiting on step.sleep() or step.waitForEvent() doesn't count against the limit.