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APIs & integration · Lesson

Rate limits

Quick answer

SailPoint enforces per-tenant rate limits; exceeding them returns HTTP 429, and clients should back off and retry using the response headers.

Key takeaways

  • Limits are enforced per tenant
  • 429 Too Many Requests signals throttling
  • Respect Retry-After / limit headers
  • Batch and paginate to reduce calls

SailPoint enforces rate limits to protect the platform from overload. When a client exceeds its allowance the API responds with 429 Too Many Requests, and well-behaved clients back off and retry using the information in the response headers. Designing for rate limits from the start avoids brittle, failure-prone integrations.

How rate limiting works

Limits are applied per tenant over a time window. Responses include headers describing your remaining quota and, on a 429, how long to wait before retrying (for example a Retry-After header). Treat these headers as the source of truth rather than guessing.

Reacting to 429 correctly

  • Honor Retry-After when present, wait exactly that long before retrying.
  • Use exponential backoff with jitter for repeated 429s, so many clients do not retry in lockstep.
  • Never hot-loop retries, that amplifies the overload and can extend throttling.

Reducing how often you hit limits

  • Filter server-side so you request only needed records.
  • Paginate with sensible page sizes rather than many tiny calls.
  • Use bulk endpoints where available.
  • Avoid bursts of parallel calls, spread the work.

Common pitfalls

  • Bursty parallelism hammering the API and triggering 429s.
  • Ignoring Retry-After and retrying immediately.
  • No backoff, turning a brief limit into a sustained failure.

Want to learn this properly?

Our live, instructor-led SailPoint Training covers this hands-on, with real projects and a certification path.

Check your understanding

  1. What status signals rate limiting?

    • A. Batch, paginate and avoid bursts of parallel calls.
    • B. HTTP 429 Too Many Requests.
    • C. Back off (exponentially) and honor the Retry-After header before retrying.
    Show answer

    B. HTTP 429 Too Many Requests.

    HTTP 429 Too Many Requests.

  2. How should clients react to 429?

    • A. Back off (exponentially) and honor the Retry-After header before retrying.
    • B. Batch, paginate and avoid bursts of parallel calls.
    • C. HTTP 429 Too Many Requests.
    Show answer

    A. Back off (exponentially) and honor the Retry-After header before retrying.

    Back off (exponentially) and honor the Retry-After header before retrying.

  3. How do you reduce rate-limit hits?

    • A. Batch, paginate and avoid bursts of parallel calls.
    • B. HTTP 429 Too Many Requests.
    • C. Back off (exponentially) and honor the Retry-After header before retrying.
    Show answer

    A. Batch, paginate and avoid bursts of parallel calls.

    Batch, paginate and avoid bursts of parallel calls.

Frequently asked questions

What does the term Rate limits refer to in SailPoint?

SailPoint enforces rate limits to protect the platform from overload. When a client exceeds its allowance the API responds with 429 Too Many Requests, and well-behaved clients back off and retry using the information in the response headers.

What is the practical takeaway on Rate limits?

Responses include headers describing your remaining quota and, on a 429, how long to wait before retrying (for example a Retry-After header).

What is worth remembering about Rate limits in practice?

Treat these headers as the source of truth rather than guessing.

What tends to go wrong with Rate limits?

Bursty parallelism hammering the API and triggering 429s. Ignoring Retry-After and retrying immediately. No backoff, turning a brief limit into a sustained failure.
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