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. 

Functions are popular because they can scale out as load increases. Considerations for enabling this scale out are important and these demand that the way the functions respond to load and handle the incoming events be determined. One way to handle parallelism is when the function itself does parallel processing using workers. The FUNCTIONS_WORKER_PROCESS_COUNT setting determines the maximum number of such workers. After this threshold is exceeded, function app is scaled out by creating new instances. When the planning is for throughput and scaling, then the trigger configuration allows us to control the batching behaviors and manage concurrency. Adjusting the values in these options can help each instance scale appropriately. These configuration options are applied to all triggers in a function application, and maintained by the host.json for the application. When we plan for connections, the number for connections on a per-instance basis must be set. This limit affects the Consumption plan and all outbound connections from the function code.