Exponential backoff
Also written: exponential retry
The system waits longer between retries when an operation repeatedly fails, to avoid overwhelming a service.
Imagine you're trying to reach a busy customer service line. If you call and it's busy, you hang up and try again immediately. If it's still busy, you might try again a few seconds later. Exponential backoff is like a smarter way to retry.
Instead of trying again right away, the system waits a little longer each time. The first retry might wait 1 second, the next 2 seconds, then 4 seconds, then 8 seconds, and so on. This gives the busy service time to recover and makes it less likely you'll keep hitting a wall. It's a common way to handle temporary problems when using online services or APIs.
Exponential backoff is a retry strategy that increases the delay between successive attempts to connect to a service. The delay typically grows exponentially, often with some random jitter added to prevent synchronized retries from multiple clients. This approach helps to gracefully handle temporary service unavailability or overload by reducing the load on the target system over time.
It is commonly used in distributed systems and APIs to manage network failures, rate limiting, or transient errors. The exponential increase in delay prevents clients from overwhelming a struggling service, improving overall system stability and reliability. The specific formula for the delay can vary, but a common pattern is `base_delay * (factor ^ attempt_number)`.
This term is appearing because Google Gemini's API is implementing automatic retries with exponential backoff for failed code cells. This feature aims to improve the developer experience by making the API more resilient to transient errors.
- Gemini API Cookbook: feat(nb_tester): add cell-level retry logic with exponential backoff (#1368)Google · Gemini API Cookbook ·
- Google Gemini
- Google Gemini's API cookbook shows an implementation of exponential backoff for retrying failed code cells, aiming to improve developer experience.
- Linear backoff
- Linear backoff increases the delay by a fixed amount each time,
- Circuit breaker
- A circuit breaker pattern stops all retries after a certain num
The concept of exponential backoff originated in early computer networking and distributed systems research to manage network congestion and unreliable connections. It's a fundamental technique for building resilient systems. Source ↗
You can observe exponential backoff by intentionally causing a temporary error when interacting with an API. For example, if you are using a service that has a known rate limit, try making requests faster than allowed. The API will likely return an error, and a well-behaved client library will automatically retry with increasing delays.
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Questions people ask
- Why not just retry immediately?
- Retrying immediately can overwhelm a busy or failing service, making the problem worse. Exponential backoff gives the service time to recover.
- What is 'jitter' in exponential backoff?
- Jitter is a small amount of randomness added to the delay. It prevents many clients from retrying at the exact same time, which could cause a new surge of load.
First seen on Subvolts Sep 15, 2026. Updated Sep 22, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.