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How Exponential Backoff Works in Google Pub/Sub's RetryPolicy
Home Backend Development Golang How does Google Pub/Sub\'s RetryPolicy implement exponential backoff, and how does it differ from other backoff libraries?

How does Google Pub/Sub\'s RetryPolicy implement exponential backoff, and how does it differ from other backoff libraries?

Oct 31, 2024 pm 07:41 PM

How does Google Pub/Sub's RetryPolicy implement exponential backoff, and how does it differ from other backoff libraries?

How Exponential Backoff Works in Google Pub/Sub's RetryPolicy

The RetryPolicy in Google Pub/Sub's cloud.google.com/go/pubsub library offers exponential backoff as a configurable feature to enhance reliability in communication between Pub/Sub and its clients.

Understanding Exponential Backoff

Exponential backoff involves increasing the delay between retries by a factor exponentially. This prevents overwhelming servers with excessive retries and ensures a more gradual reconnection.

MinimumBackoff and MaximumBackoff

In the RetryPolicy configuration, MinimumBackoff is equivalent to the InitialInterval in the github.com/cenkalti/backoff library, and MaximumBackoff corresponds to the MaxInterval.

MinimumBackoff sets the initial wait period before the first retry, while MaximumBackoff represents the maximum delay allowed between retries. By default, MinimumBackoff is 10 seconds and MaximumBackoff is 10 minutes.

Calculating Wait Intervals

Pub/Sub calculates the wait intervals between retries based on the randomized exponential backoff formula:

`

randomized interval =</p>
<div class="code" style="position:relative; padding:0px; margin:0px;"><pre class="brush:php;toolbar:false">RetryInterval * (random value in range [1 - RandomizationFactor, 1 + RandomizationFactor])
Copy after login

`

where RetryInterval is the current retry interval, initially MinimumBackoff, and is subject to the MaximumBackoff limit.

Maximum Retry Attempts

Unlike the github.com/cenkalti/backoff library's MaxElapsedTime feature, the Pub/Sub RetryPolicy does not have an equivalent option to limit retry attempts. Instead, it recommends using Dead Letter Queues (DLQs) for situations where retries should be capped.

Randomization

The Pub/Sub RetryPolicy employs a random component to introduce variance in retry intervals, ensuring that multiple clients with the same configuration do not retry at the exact same intervals.

Observations from Your Experiment

Your experimental observations reflect the exponential backoff behavior. Using a MinimumBackoff of 1s and MaximumBackoff of 2s, you noticed a relatively consistent ~3s delay between nacks, representing the maximum backoff of 2s.

The absence of doubling intervals between retries suggests that there is no explicit multiplier applied. Additionally, you did not observe any hard limit on the number of retries, supporting the recommendation to use DLQs for limiting retry attempts.

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