![]() Exponential back-off adds some small randomization to delays to stagger retries in high-throughput scenarios. On subsequent retries, time is added exponentially to the initial duration for each retry, until the maximum delay is reached. The first retry waits for the minimum delay. As a best practice, you should catch all exceptions in your code and rethrow any errors that you want to result in a retry.Ī specified amount of time is allowed to elapse between each retry. The retry policy tells the runtime to rerun a failed execution until either successful completion occurs or the maximum number of retries is reached.Ī retry policy is evaluated when a Timer, Kafka, or Event Hubs-triggered function raises an uncaught exception. Starting with version 3.x of the Azure Functions runtime, you can define retry policies for Timer, Kafka, and Event Hubs triggers that are enforced by the Functions runtime. It also links to more information about errors that come from the underlying services. The following table indicates which triggers support retries and where the retry behavior is configured. Retry policies provided by the Functions runtime.Built-in retry behaviors of individual trigger extensions.There are two kinds of retries available for your functions: To learn more, see Designing Azure Functions for identical input. It's important to consider what happens when the error occurs and how to avoid duplicate processing. The occurrence of errors when you're processing data can be a problem for your functions, especially when you're processing messages. For triggers that don't provide retry behaviors, you might want to implement your own retry scheme. In addition, the runtime lets you define retry policies for Timer, Kafka, and Event Hubs-triggered functions. Several Functions bindings extensions provide built-in support for retries. For information about what errors might be raised by bindings, see Binding error codes. In the catch block, you can capture and log errors. The top-most level of any function code should include a try/catch block. Use structured error handlingĬapturing and logging errors is critical to monitoring the health of your application. To learn more, see Monitor Azure Functions. You should use Application Insights to discover and better understand errors that occur in your function executions. Enable Application InsightsĪzure Functions integrates with Application Insights to collect error data, performance data, and runtime logs. This section describes some recommended error-handling practices and provides links to more information. To avoid loss of data or missed messages, it's important to practice good error handling. Calls to client libraries, packages, or third-party APIs.Calls to APIs of underlying Azure services.Use of built-in Azure Functions triggers and bindings. ![]() Handling errorsĮrrors that occur in an Azure function can result from any of the following: For more information, see the Retries section. Preview retry policy support for all triggers other than Timer and Event Hubs was removed in December 2022. Thanks for the awesome lib, love it! Checklistīeta Was this translation helpful? Give feedback.We're removing retry policy support in the runtime for triggers other than Timer, Kafka, and Event Hubs after this feature becomes generally available (GA). I´m aware that I could just catch the 404 and then do the retry manually, just asking for a way of doing it internal. Is it somehow possible to force a retry manually by just using Got? If this is not possible, see my comment in the code.How can I extend the HTTP statusCodes that allow running a retry?. ![]()
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