100 Days of Cloud – Day 55: Azure Functions

Its Day 55 of my 100 Days of Cloud journey, and today I’m going to attempt to understand and explain Azure Functions.

What are Azure Functions?

Azure Functions is one of the ways that allow you to create serverless applications in Azure. All you need to do is write the code you need for the problem or task that you wish to perform, without having to worry about create a whole application or infrastructure to run the code for you.

Depending on what language you need your application to use, this link gives full details for the languages that are supported for Azure Functions. There are also Developer References for each of the languages which give full details of how to develop your desired functions using the supported languages. Azure Functions uses a code-first (imperative) development model

All functions contain 2 pieces – your code and the config file, which is called function.json. The function.json file contains the function’s trigger, bindings and other configuration settings.

Function App

A function app provides an execution context in Azure in which your functions run. As such, it is the unit of deployment and management for your functions. A function app is comprised of one or more individual functions that are managed, deployed, and scaled together.

A function app requires a general Azure Storage account, which supports Azure Blob, Queue, Files, and Table storage.

Hosting Plans

When you create a function app in Azure, you must choose a hosting plan for your app. There are three basic hosting plans available for Azure Functions:

  • Consumption plan – This is the default hosting plan. It scales automatically and you only pay for compute resources when your functions are running. Instances of the Functions host are dynamically added and removed based on the number of incoming events.
  • Functions Premium plan – Automatically scales based on demand using pre-warmed workers which run applications with no delay after being idle, runs on more powerful instances, and connects to virtual networks.
  • App service plan – Run your functions within an App Service plan at regular App Service plan rates. Best for long-running scenarios where Durable Functions can’t be used.

Triggers and Bindings

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A different kind of Trigger ……

Azure Functions are event driven – this means that an event or trigger is required in order for the function to run and the underlying code to execute. Each function must only have one trigger.

The most common types of triggers are:

  • Timer – Execute a function at a set interval.
  • HTTP – Execute a function when an HTTP request is received.
  • Blob – Execute a function when a file is uploaded or updated in Azure Blob storage.
  • Queue – Execute a function when a message is added to an Azure Storage queue.
  • Azure Cosmos DB – Execute a function when a document changes in a collection.
  • Event Hub – Execute a function when an event hub receives a new event.

Bindings are a way to both declaratively connect resources to functions and also to pass parameters from resources into a function. Bindings can be created as Input bindings, Output bindings or both.

Triggers and bindings let you avoid hardcoding access to other services within your code, therefore making it re-usable. Your function receives data (for example, the content of a queue message) in function parameters. You send data (for example, to create a queue message) by using the return value of the function.

Scaling

We can see in our hosting plans above that depending on which one you choose, this wil dictate how Azure Functions will scale and the maxiumum resouirces that are assigned to a function app.

Azure Functions uses a component called the scale controller to monitor the rate of events and determine whether to scale out or scale in. The scale controller uses heuristics for each trigger type. For example, when you’re using an Azure Queue storage trigger, it scales based on the queue length and the age of the oldest queue message.

Scaling can vary on a number of factors, and scale differently based on the trigger and language selected. There are a some scaling behaviors to be aware of:

  • Maximum instances: A single function app only scales out to a maximum of 200 instances. A single instance may process more than one message or request at a time though, so there isn’t a set limit on number of concurrent executions.
  • New instance rate: For HTTP triggers, new instances are allocated, at most, once per second. For non-HTTP triggers, new instances are allocated, at most, once every 30 seconds. Scaling is faster when running in a Premium plan.

By default, Consumption plan functions scale out to as many as 200 instances, and Premium plan functions will scale out to as many as 100 instances. You can specify lower maximum instances for each app if required.

Real-World Examples

So while all of the above theory is interesting, we still haven’t answered the key question which is where would we need to use Azure Functions?

Lets take a look at some real world examples of where Azure Functions would be useful:

  • Take a snapshot of a Virtual Machine before updates are scheduled to be applied.
  • Monitor expiry dates of Certificates and trigger an email to be sent 30 days before they expire.
  • When a Virtual machine is deleted, remove it from Monitoring.
  • When a CPU spikes above 90%, send a message to a Teams Channel.

Conclusion

So thats a whistle stop overview of Azure Functions. There are tons of brilliant resources out there where you can dive in and learn about Azure Functions in greater depth, such as the Microsoft Learn Module as part of the AZ-204 learning path which gives a full lab on creating your own function using a HTTP trigger.

Hope you enjoyed this post, until next time!

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