How Does Google Pub/Sub Implement Exponential Backoff in RetryPolicies Compared to github.com/cenkalti/backoff?

Exponential Backoff in RetryPolicies

The exponential backoff feature introduced in Google Pub/Sub's RetryPolicy mirrors the concept described in the ExponentialBackOff defined by github.com/cenkalti/backoff that you mentioned.

Minimum and Maximum Backoff

Yes, you are correct. The MinimumBackoff and MaximumBackoff parameters in pubsub.RetryPolicy correspond to InitialInterval and MaxInterval in github.com/cenkalti/backoff, respectively:

• MinimumBackoff: Initial wait period upon retrying a failed operation.
• MaximumBackoff: Maximum amount of time allowed between retries.

Randomization

Cloud Pub/Sub uses the same formula for randomizing the interval as the github.com/cenkalti/backoff:

randomized interval = RetryInterval * (random value in range [1 - RandomizationFactor, 1 + RandomizationFactor])

The RandomizationFactor is set to 0.15 by default in pubsub.RetryPolicy.

Multiplier and MaxElapsedTime

Unlike github.com/cenkalti/backoff, pubsub.RetryPolicy does not have an equivalent to Multiplier, which doubles the RetryInterval after each failure. Instead, the Pub/Sub retry delay increases exponentially at a fixed rate determined by the RandomizationFactor.

Additionally, there is no explicit MaxElapsedTime in pubsub.RetryPolicy. However, Pub/Sub implements a go-routine-based retry mechanism, where retries are effectively bounded by the lifetime of the go-routine that handles the subscription.

Example

Your experiment demonstrates the exponential backoff behavior accurately. The longer backoff intervals (5s to 60s) result in less frequent retries, while the shorter intervals (1s to 2s) result in more frequent retries. The variance in the intervals is due to the randomization factor.

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