Glossary

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Glossary / Evaluation and implementation guide

API Backoff Policy

An API backoff policy defines how a client progressively waits between retry attempts when an API starts rejecting requests, often doubling the delay each round and sometimes adding random jitter so many clients don't retry in unison.

It is the client-side pacing behavior, distinct from Rate Limiting, which is the provider-side cap on how many requests are allowed in the first place.

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A practical example

Example: during a CRM outage, your MAP's lead sync starts receiving 503 responses. With exponential backoff, the first retry waits 2 seconds, then 4, then 8, with jitter added.

The sync slows instead of hammering the recovering server, and queued lead updates are preserved for later attempts.

What to evaluate before investing

  • Ask whether the connector supports exponential backoff with jitter or only fixed-delay retries.
  • Confirm backoff settings are configurable per integration, since a CRM and an enrichment API tolerate different pacing.
  • Check how the policy interacts with your request quota so retries don't consume the budget needed for live syncs.

Limitations and tradeoffs

Aggressive backoff delays data delivery: a lead update may sit for minutes during incidents. Without jitter, synchronized retry waves from many clients can re-overload a recovering API.

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Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.

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