Azure Functions:

 

This is a continuation of a series of articles on Azure services from an operational engineering perspective with the most recent introduction to Azure Function core tools with the link here. This article discusses Azure Functions best practices.

When we want code to be triggered by events, Azure Functions become very useful because it is a compute-on-demand experience. It extends the existing Azure App Service platform with capabilities to implement code triggered by events occurring in Azure, in third-party service, and in on-premises systems. Functions can be built to be reactive, but they are also useful to process data from various data sources. Functions are hosted in environments that like VMs are susceptible to faults such as restarts, moves or upgrades. Functions may also have the same reliability as the APIs it invokes. But functions can scale out so that they never become a bottleneck. The article details some of the best practices for designing and efficient function apps.

A function app must have a proper hosting plan.  There are three basic plans available which include: Consumption plan, Premium plan, Dedicated (App Service) plan. Function apps work on both Linux and Windows so the hosting plans are generally available (GA) on both. The hosting plan chosen determines the following behaviors:

-          How the function app is scaled based on demand and how instances allocation is managed

-          The resources available to each function app instance

-          The support for advanced functionality, such as Azure Virtual Network connectivity

Functions provide a limited range of options to switch hosting plans so proper choice at the time of function creation matters.

Functions require a storage account to be associated with a function app.  The storage account connection helps the functions to manage triggers and log entries. It is also used when dynamically scaling out the function apps. Proper configuration helps with the reliability and the performance of the function apps.

There are settings that determine whether the function application is run from the Azure Files endpoint or from the file servers. ARM templates with proper settings are available for Consumption plan, Dedicated plan, Premium plan with VNET integration and Consumption plan with a deployment slot.

Large data sets require special handling. For this purpose, extra storage can be mounted as a file share.

A solution can comprise of multiple functions. Their deployment can be authored via a DevOps release. All functions in a function app are deployed at the same time. When the functions are run from a deployment package, it can be deployed directly to production and reduce cold start times.

Continuous deployment is required for source control solution. A warmup trigger can reduce latencies when new instances are added. Deployment downtimes can be minimized, and rollbacks can be enabled when using deployment slots. These are some strategies for successful deployments.

Several design principles can come helpful to writing reliable robust functions. These include avoiding long running functions, planning cross function communication, writing functions to be stateless, and writing defensive functions.