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Copy file name to clipboardExpand all lines: articles/azure-functions/functions-bindings-error-pages.md
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@@ -14,7 +14,7 @@ Handling errors in Azure Functions is important to help you avoid lost data, avo
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This article describes general strategies for error handling and the available retry strategies.
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> [!IMPORTANT]
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> Preview retry policy support for certain triggers was removed in December 2022. Retry policies for supported triggers is now generally available (GA). For a list of extensions that currently support retry policies, see the [Retries](#retries) section.
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> Preview retry policy support for certain triggers was removed in December 2022. Retry policies for supported triggers are now generally available (GA). For a list of extensions that currently support retry policies, see the [Retries](#retries) section.
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## Handling errors
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- Calls to REST endpoints.
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- Calls to client libraries, packages, or third-party APIs.
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To avoid loss of data or missed messages, it's important to practice good error handling. This section describes some recommended error-handling practices and provides links to more information.
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To avoid loss of data or missed messages, it's important to practice good error handling. This table describes some recommended error-handling practices and provides links to more information.
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| Recommendation | Details |
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| ---- | ---- |
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<sup>*</sup>Requires version 5.x of the Azure Service Bus extension. In older extension versions, retry behaviors are implemented by the [Service Bus dead letter queue](../service-bus-messaging/service-bus-dead-letter-queues.md#maximum-delivery-count).
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###Retry policies
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## Retry policies
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Azure Functions lets you define retry policies for specific trigger types, which are enforced by the runtime. These trigger types currently support retry policies:
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>
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> The version 5.x of the Event Hubs extension supports additional retry capabilities for interactions between the Functions host and the event hub. For more information, see `clientRetryOptions` in the [Event Hubs host.json reference](functions-bindings-event-hubs.md#host-json).
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####Retry strategies
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### Retry strategies
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You can configure two retry strategies that are supported by policy:
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#####[Fixed delay](#tab/fixed-delay)
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#### [Fixed delay](#tab/fixed-delay)
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A specified amount of time is allowed to elapse between each retry.
The first retry waits for the minimum delay. On subsequent retries, time is added exponentially to the initial duration for each retry, until the maximum delay is reached. Exponential back-off adds some small randomization to delays to stagger retries in high-throughput scenarios.
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---
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When running in a Consumption plan, you are only billed for time your function code is executing. You aren't billed for the wait time between executions in either of these retry strategies.
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####Max retry counts
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### Max retry counts
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You can configure the maximum number of times that a function execution is retried before eventual failure. The current retry count is stored in memory of the instance.
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It's possible for an instance to have a failure between retry attempts. When an instance fails during a retry policy, the retry count is lost. When there are instance failures, the Event Hubs trigger is able to resume processing and retry the batch on a new instance, with the retry count reset to zero. The timer trigger doesn't resume on a new instance.
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This behavior means that the maximum retry count is a best effort. In some rare cases, an execution could be retried more than the requested maximum number of times. For Timer triggers, the retries can be less than the maximum number requested.
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####Retry examples
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### Retry examples
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::: zone pivot="programming-language-python,programming-language-csharp"
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Examples are provided for both fixed delay and exponential backoff strategies. To see examples for a specific strategy, you must first select that strategy in the previous tab.
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