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inngest-flow-control

inngest/inngest-skills

Manage API rate limits, concurrency, debouncing, and event batching in Inngest workflows.

What is inngest-flow-control?

Flow control skill for Inngest that provides mechanisms to handle external API rate limits, prevent duplicate work, spread load over time, and ensure fair resource allocation. Use this when you need to limit concurrent operations, throttle function starts, debounce rapid events, batch process events, or prioritize important runs.

  • Concurrency limits with optional per-key fairness (e.g., per-tenant, per-user)
  • Throttling to spread function starts over time with burst allowance
  • Rate limiting to discard excessive duplicate events within a period
  • Debouncing to wait for activity to stop before processing the latest event
  • Priority queuing to execute important runs ahead of others
  • Singleton mode to ensure only one instance runs at a time (skip or cancel modes)

How to install inngest-flow-control

npx skills add https://github.com/inngest/inngest-skills --skill inngest-flow-control
Prerequisites
  • Inngest TypeScript SDK installed
  • Inngest account and project configured
  • Understanding of Inngest function configuration and triggers
Claude Code
Cursor
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How to use inngest-flow-control

  1. 1.Install the skill via npx skills add
  2. 2.Choose the appropriate flow control mechanism based on your use case (concurrency, throttling, rate limiting, debounce, priority, singleton, or batching)
  3. 3.Configure the mechanism in your function definition with the required parameters (limit, period, key, etc.)
  4. 4.For concurrency and throttling, optionally add a key to apply limits per unique value (e.g., per user or tenant)
  5. 5.Test your configuration to ensure it achieves the desired rate-limiting or load-spreading behavior

Use cases

Good for
  • Handling external API rate limits (OpenAI 429s, HubSpot, Stripe) without overwhelming downstream services
  • Debouncing rapid user actions like document edits or search queries to avoid redundant processing
  • Preventing webhook spam by limiting duplicate events within a time window
  • Ensuring per-tenant fairness in multi-tenant systems to avoid noisy neighbor problems
  • Processing bulk operations (email sends, data syncs) in batches for efficiency
Who it's for
  • Backend engineers building event-driven systems with Inngest
  • Teams managing multi-tenant SaaS applications
  • Developers integrating with rate-limited third-party APIs
  • Product teams needing fair resource allocation across customers

inngest-flow-control FAQ

What's the difference between concurrency and throttling?

Concurrency limits the number of steps executing simultaneously (active code execution), while throttling limits how many function runs can start per time period. Concurrency protects computing resources; throttling spreads load over time.

When should I use rate limiting vs. throttling?

Use throttling to delay function starts and respect API rate limits. Use rate limiting to discard excessive duplicate events within a period. Throttling queues events; rate limiting drops them.

How do I apply flow control per customer in a multi-tenant system?

Use the `key` parameter with a path like `event.data.customer_id` or `event.data.tenant_id`. This applies the limit separately for each unique key value, ensuring fair resource allocation.

What's the difference between singleton skip and cancel modes?

Skip mode preserves the currently running function and ignores new triggers. Cancel mode cancels the running function and starts a new one with the latest event data.

Can I combine multiple flow control mechanisms on one function?

Yes, you can use concurrency, throttling, rate limiting, debounce, priority, singleton, and batching together. Choose combinations that match your use case (e.g., batching + concurrency for bulk processing).

Full instructions (SKILL.md)

Source of truth, from inngest/inngest-skills.


name: inngest-flow-control description: "Use when handling external API rate limits (e.g., OpenAI 429s, HubSpot or Stripe rate limits), preventing duplicate work from rapid event bursts (debouncing user actions), spreading load over time, ensuring per-tenant fairness, processing events in batches, limiting concurrent runs of the same operation, or assigning priority to important runs. Covers Inngest flow control: concurrency limits with keys, throttling, rate limiting, debounce, priority, singleton, and event batching."

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.

Basic Concurrency

inngest.createFunction(
  {
    id: "process-images",
    concurrency: 5,
    triggers: [{ event: "media/image.uploaded" }]
  },
  async ({ event, step }) => {
    // Only 5 steps can execute simultaneously
    await step.run("resize", () => resizeImage(event.data.imageUrl));
  }
);

Concurrency with Keys (Multi-tenant)

Use key parameter to apply limit per unique value of the key.

inngest.createFunction(
  {
    id: "user-sync",
    concurrency: [
      {
        key: "event.data.user_id",
        limit: 1
      }
    ],
    triggers: [{ event: "user/profile.updated" }]
  },
  async ({ event, step }) => {
    // Only 1 step per user can execute at once
    // Prevents race conditions in user-specific operations
  }
);

Account-level Shared Limits

inngest.createFunction(
  {
    id: "ai-summary",
    concurrency: [
      {
        scope: "account",
        key: `"openai"`,
        limit: 60
      }
    ],
    triggers: [{ event: "ai/summary.requested" }]
  },
  async ({ event, step }) => {
    // Share 60 concurrent OpenAI calls across all functions
  }
);

When to use each:

  • Basic: Protect databases or limit general capacity
  • Keyed: Multi-tenant fairness, prevent "noisy neighbor" issues
  • Account-level: Share quotas across multiple functions (API limits)

Throttling

When to use: Control the rate of function starts over time to work around API rate limits or smooth traffic spikes.

Key difference from concurrency: Throttling limits function run starts; concurrency limits step execution.

inngest.createFunction(
  {
    id: "sync-crm-data",
    throttle: {
      limit: 10, // 10 function starts
      period: "60s", // per minute
      burst: 5, // plus 5 immediate bursts
      key: "event.data.customer_id" // per customer
    },
    triggers: [{ event: "crm/contact.updated" }]
  },
  async ({ event, step }) => {
    // Respects CRM API rate limits: 10 calls/min per customer
    await step.run("sync", () => crmApi.updateContact(event.data));
  }
);

Configuration:

  • limit: Functions that can start per period
  • period: Time window (1s to 7d)
  • burst: Extra immediate starts allowed
  • key: Apply limits per unique key value

Rate Limiting

When to use: Hard limit to prevent abuse or skip excessive duplicate events.

Key difference from throttling: Rate limiting discards events; throttling delays them.

inngest.createFunction(
  {
    id: "webhook-processor",
    rateLimit: {
      limit: 1,
      period: "4h",
      key: "event.data.webhook_id"
    },
    triggers: [{ event: "webhook/data.received" }]
  },
  async ({ event, step }) => {
    // Process each webhook only once per 4 hours
    // Prevents duplicate webhook spam
  }
);

Use cases:

  • Prevent webhook duplicates
  • Limit expensive operations per user
  • Protection against abuse

Debounce

When to use: Wait for a series of events to stop arriving before processing the latest one.

inngest.createFunction(
  {
    id: "save-document",
    debounce: {
      period: "5m", // Wait 5min after last edit
      key: "event.data.document_id",
      timeout: "30m" // Force save after 30min max
    },
    triggers: [{ event: "document/content.changed" }]
  },
  async ({ event, step }) => {
    // Saves document only after user stops editing
    // Uses the LAST event received
    await step.run("save", () => saveDocument(event.data));
  }
);

Perfect for:

  • User input that changes rapidly (search, document editing)
  • Noisy webhook events
  • Ensuring latest data is processed

Priority

When to use: Execute some function runs ahead of others based on dynamic data.

inngest.createFunction(
  {
    id: "process-order",
    priority: {
      // VIP users get priority up to 120 seconds ahead
      run: "event.data.user_tier == 'vip' ? 120 : 0"
    },
    triggers: [{ event: "order/placed" }]
  },
  async ({ event, step }) => {
    // VIP orders jump ahead in the queue
  }
);

Advanced example:

inngest.createFunction(
  {
    id: "support-ticket",
    priority: {
      run: `
        event.data.severity == 'critical' ? 300 :
        event.data.severity == 'high' ? 120 :
        event.data.user_plan == 'enterprise' ? 60 : 0
      `
    },
    triggers: [{ event: "support/ticket.created" }]
  },
  async ({ event, step }) => {
    // Critical tickets get highest priority (300s ahead)
    // High severity: 120s ahead
    // Enterprise users: 60s ahead
    // Everyone else: normal priority
  }
);

Singleton

When to use: Ensure only one instance of a function runs at a time.

Skip Mode (Preserve Current Run)

inngest.createFunction(
  {
    id: "data-backup",
    singleton: {
      key: "event.data.database_id",
      mode: "skip"
    },
    triggers: [{ event: "backup/requested" }]
  },
  async ({ event, step }) => {
    // Skip new backups if one is already running for this database
    await step.run("backup", () => performBackup(event.data.database_id));
  }
);

Cancel Mode (Use Latest Event)

inngest.createFunction(
  {
    id: "realtime-sync",
    singleton: {
      key: "event.data.user_id",
      mode: "cancel"
    },
    triggers: [{ event: "user/data.changed" }]
  },
  async ({ event, step }) => {
    // Cancel previous sync and start with latest data
    await step.run("sync", () => syncUserData(event.data));
  }
);

Batching

When to use: Process multiple events together for efficiency.

inngest.createFunction(
  {
    id: "bulk-email-send",
    batchEvents: {
      maxSize: 100, // Up to 100 events
      timeout: "30s", // Or 30 seconds, whichever first
      // `key` groups events into separate batches per unique value
      // This is different from expressions `if` which filters events
      key: "event.data.campaign_id" // Batch per campaign
    },
    triggers: [{ event: "email/send.queued" }]
  },
  async ({ events, step }) => {
    // Process array of events together
    const emails = events.map((evt) => ({
      to: evt.data.email,
      subject: evt.data.subject,
      body: evt.data.body
    }));

    await step.run("send-batch", () => emailService.sendBulk(emails));
  }
);

Combining Flow Control

Example: Fair AI Processing

inngest.createFunction(
  {
    id: "ai-image-processing",
    // Global throttling for API limits
    throttle: {
      limit: 50,
      period: "60s",
      key: `"gpu-cluster"`
    },
    // Per-user concurrency for fairness
    concurrency: [
      {
        key: "event.data.user_id",
        limit: 3
      }
    ],
    // VIP users get priority
    priority: {
      run: "event.data.plan == 'pro' ? 60 : 0"
    },
    triggers: [{ event: "ai/image.generate" }]
  },
  async ({ event, step }) => {
    // Combines multiple flow controls for optimal resource usage
  }
);

Pro tip: Most production functions benefit from combining 1-3 flow control mechanisms for optimal reliability and performance.