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AzureFunctions

If you use Azure Functions on a regular basis, you’ll likely have grappled with the challenge of testing them. Even now, several years after their introduction, the testing story for Functions is not hugely well defined. In the final post in this series, we show how to ensure specs written using Corvus.SpecFlow.Extensions can run as part of your build pipeline.


If you use Azure Functions on a regular basis, you’ll likely have grappled with the challenge of testing them. Even now, several years after their introduction, the testing story for Functions is not hugely well defined. In the fourth of this series of posts, we look at how configuration can be supplied from your tests to the functions apps being tested.


If you use Azure Functions on a regular basis, you’ll likely have grappled with the challenge of testing them. Even now, several years after their introduction, the testing story for Functions is not hugely well defined. In the third of a series of posts, we look at using classes in the Corvus.SpecFlow.Extensions library to run functions apps via scenario and feature hooks.


If you use Azure Functions on a regular basis, you’ll likely have grappled with the challenge of testing them. Even now, several years after their introduction, the testing story for Functions is not hugely well defined. In the second of a series of posts, we look at using step bindings provided by the Corvus.SpecFlow.Extensions library to run functions apps as part of your SpecFlow scenarios.


If you use Azure Functions on a regular basis, you’ll likely have grappled with the challenge of testing them. Even now, several years after their introduction, the testing story for Functions is not hugely well defined. In the first of a series of posts, we look at some different approaches to testing your functions apps, and introduce the Corvus.SpecFlow.Extensions library.


Optimising C# for a serverless environment

by Carmel Eve

In our recent project with OceanMind we used #AzureFunctions to process marine vessel telemetry from around the world. This involved processing huge quantities of data in close to real time. We optimised our processing for a #serverless environment, the outcome of which being that the compute would cost less than £10 / month!

This post summarises some of the techniques we used, including some concrete examples of optimisations we made.

#bigdata #dataprocessing #dataanalysis #bigcompute


In this post we show how a combination of Kubernetes, Azure Durable Functions and Azure API Management can be used to make legacy batch processing code available as a RESTful API. This is a great example of how serverless technologies can be used to expose legacy software to the public internet in a controlled way, allowing you to reap some of the benefits of a cloud first approach without fully rewriting and migrating existing software.


Long Running Functions in Azure Data Factory

by Jess Panni

Azure Functions are powerful and convenient extension points for your Azure Data Factory pipelines. Put your custom processing logic behind an HTTP triggered Azure Function and you are good to go. Unfortunately many people read the Azure documentation and assume they can merrily run a Function for up to 10 minutes on a consumption plan […]


Running Azure functions in Docker on a Raspberry Pi 4

by Jonathan George

For one of my first experiments with the Raspberry Pi 4, I decided to get an Azure Function running in a Docker container. This post gives a step-by-step guide on how to do it, as well as providing code you can use a starting point for your own experiments.


Building a secure solution on Azure can be a daunting task. Using Azure Functions and Managed Identities, we have built up a pattern for giving services access to one another, woithout the need to store credentials. These managed identities can be given access to necessary resources. For example, they can be granted roles and added to access control lists in ADLS Gen2 accounts, or the ability to access keys in key vault. This means that data can be securely accessed without needing to store connection strings or app passwords.


This post walks through the fix for DLL locking errors when trying to deploy an Azure Function. The solution was to switch over to the new “deploy from package” option when deploying the functions. This fixes the file locking problem because instead of deploying the DLLs, the function will run from a package file added to its directory.