Building and Deploying Azure Functions on NET..png

azurefunctions.tar.gz

Basic Function Job

Function with a HTTP client

Basic Function Job with HTTPS

Azure Functions allows businesses and individual developers to run workloads of varying intensity in the cloud without the need to manage servers. These serverless applications can automatically scale based on demand, ensuring that resources are always available when needed. Azure Functions is also very cost-effective since it bills you only for the functions you use.

In this course, you’ll focus on the .NET implementations of Azure Functions. You’ll start by learning how to build, configure, and deploy these functions. Next, you’ll explore running Azure Functions in a development environment and examine the different types of functions and the various ways to trigger them. Finally, you’ll learn how to orchestrate, scale, and secure Azure Functions.

By the end of this course, you will have gained a comprehensive understanding of the full development cycle of .NET-based Azure functions. You will be equipped to build, deploy, and manage Azure functions in a .NET environment.

Building and Deploying Azure Functions in .NET

Scaling out refers to a setting that determines how many instances of the function can be executed simultaneously. Concurrency refers to the setting that determines how many instances of the function host can be run at the same time.

Concurrency refers to a setting that determines how many instances of the function can be executed simultaneously. Scaling out is how we control how many instances of the function host can be run at the same time.

Scaling out refers to the process of allocating more computational resources to the function host. Concurrency refers to how many instances of the app we can run.

What is the difference between scaling out and concurrency?

What is the difference between scaling out and concurrency?

It can only be applied for Service Bus bindings under the `serviceBus` extension settings in the `host.json` file.

By setting the `dynamicConcurrencyEnabled` setting to `true` under the `concurrency` section of the `host.json` file.

By setting the `DynamicConcurrencyEnabled` setting to `true` in the main application settings.

By setting the `dynamicConcurrencyEnabled` and `snapshotPersistenceEnabled` settings to `true` in the `host.json` file.

Which best describes how dynamic concurrency can be enabled in a function app?

Which best describes how dynamic concurrency can be enabled in a function app?

To make sure it still runs if any specific instance of it fails

To ensure that our app can handle a large number of incoming requests

To ensure that the app can perform a calculation faster

To make sure each instance can store more data in memory while processing requests

Which best describes why we would need to scale our app?

Which best describes why we would need to scale our app?

It won’t because throttling makes the system slower.

By removing excessive load from other parts of the system.

By forcing multiple instances of the application to spin up.

How would the throttling of incoming requests improve the performance of the system?

How would the throttling of incoming requests improve the performance of the system?

Test your knowledge on scaling Azure Functions.

Introduction

Azure Functions Basics

Azure Functions Triggers and Bindings

Using Durable Functions For Long-Running Operations

Azure Functions Reliability and Availability

Scaling Azure Functions

Securing Azure Functions

Conclusion

Appendix

Quiz: Scaling Azure Functions