Monitoring Azure Function Consumption Plan Instance Scale Out

Monitoring Azure Function Consumption Plan Instance Scale Out

With the Consumption Plan hosting model for Azure Functions, we can take advantage of event-driven scaling to automatically spin up extra instances of a Function app based on load. In this post, we’ll cover how you can view this in real-time and also how to chart the scaled-out instances retrospectively over time.

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E2E Testing Azure Functions

Scenario Recently I was working on a solution which included multiple Azure Function apps, with unit tests (xUnit) giving rapid feedback for discrete components across the solution in isolation. But the next step was to create some automated end-to-end (E2E) tests that exercised the behaviours of the solution as a whole. The goal was to be able to get that feedback as early on in the development process as possible which meant being able to run those E2E tests against a local build on a dev machine when needed with minimal hassle, and in an Azure DevOps CI/CD pipeline, without requiring the Azure Functions to be deployed first. [Read More]

Troubleshooting Azure Function Consumption Plan Scaling

I recently encountered an issue with an Azure Function Event Hub trigger running on a Linux Consumption Plan, whereby events stopped being consumed by the trigger once it went to sleep. I learned a lot about consumption plan scaling and diagnosing what was going on, so in this post I’m going to share the key takeaways that I picked up as it was a bit of a journey. Background: Azure Function Event Hub trigger stopped processing events This was in a low-throughput scenario for testing - so the rate of events coming into the Event Hub was low/sporadic. [Read More]