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Rate Limiting

Infrastructure

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What is Rate Limiting?

Rate limiting is a technique that controls the number of requests a client can make to a server within a given time window, preventing abuse and ensuring fair resource distribution.

What is Rate Limiting?

Rate limiting restricts how many requests a user, application, or IP address can send to a server within a specified time period. When the limit is exceeded, the server typically responds with an HTTP 429 (Too Many Requests) status code and may include a Retry-After header indicating when the client can try again.

How Rate Limiting Works

Rate limiting algorithms track request counts using various strategies:

  • Fixed window — Counts requests within fixed time intervals (e.g., 100 requests per minute). Simple but can allow bursts at window boundaries.
  • Sliding window — Uses a rolling time window, providing smoother rate enforcement without boundary spikes.
  • Token bucket — Tokens accumulate at a fixed rate up to a maximum. Each request consumes a token. This allows controlled bursts while maintaining an average rate.
  • Leaky bucket — Requests enter a queue that drains at a constant rate. Excess requests overflow and are rejected.

    • Rate Limiting in Automation

    When building automated workflows that interact with external APIs or websites, rate limiting is both a constraint you encounter and a practice you should implement:

    As a constraint: Most APIs enforce rate limits. The GitHub API allows 5,000 requests per hour for authenticated users. Google Sheets API limits to 300 requests per minute per project. Exceeding these limits causes your automation to fail or get temporarily blocked.

    As a practice: Your own automation should implement rate limiting to be a good citizen of the web. Hammering a website with thousands of rapid requests can overwhelm their servers and get your IP permanently banned.

    Strategies for Handling Rate Limits

    Effective automation respects rate limits through several techniques:

  • Throttling — Adding deliberate delays between requests to stay under the limit.
  • Exponential backoff — When rate-limited, waiting progressively longer before retrying (1s, 2s, 4s, 8s...).
  • Request queuing — Buffering requests and releasing them at a controlled rate.
  • Distributed requests — Spreading traffic across multiple IP addresses or API keys.
  • Caching — Storing responses to avoid redundant requests.

    • HTTP Headers for Rate Limiting

    Most APIs communicate rate limit status through response headers:

  • X-RateLimit-Limit: Maximum requests allowed in the window
  • X-RateLimit-Remaining: Requests remaining in the current window
  • X-RateLimit-Reset: Timestamp when the window resets
  • Retry-After: Seconds to wait before retrying (on 429 responses)

    • Rate limiting caps how many requests a client may make in a window, a defensive control documented by OWASP. Autonoly respects and adapts to these limits automatically across its API & HTTP calls and data extraction.

    Why It Matters

    Understanding rate limiting is critical for building reliable automations. Ignoring rate limits leads to blocked requests, banned accounts, and failed workflows. Properly handling them ensures your automations run consistently without interruption.

    How Autonoly Solves It

    Autonoly's workflow engine includes built-in retry logic with configurable delays and exponential backoff. When your automation encounters rate limits from APIs or websites, the platform automatically throttles requests, waits for reset windows, and resumes execution without manual intervention.

    Learn more

    Examples

    • An API integration workflow automatically slowing down when it detects X-RateLimit-Remaining dropping below 10, preventing 429 errors.

    • A web scraping pipeline spacing requests 2 seconds apart to respect a site's robots.txt crawl-delay directive.

    • A data sync workflow that batches API calls into groups of 50 with 60-second pauses between batches to stay within quota.

    Frequently Asked Questions

    The server typically returns an HTTP 429 (Too Many Requests) response. Some APIs may also return 503 (Service Unavailable). Repeated violations can lead to longer cooldown periods, temporary IP bans, or permanent API key revocation depending on the service's policies.

    Add delays between requests, use exponential backoff when you receive 429 responses, rotate IP addresses to distribute load, cache previously fetched pages, and respect the site's robots.txt crawl-delay. Monitor response headers for rate limit indicators and adjust your request pace accordingly.

    Rate limiting is the policy that defines the maximum allowed request rate (e.g., 100 requests per minute). Throttling is the mechanism that enforces that policy by slowing down or queuing requests. Rate limiting sets the rule; throttling implements it.

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    Related terms, automations and guides

    Where this concept shows up in practice.

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