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File-Based Encoding and Azure Media Analytics

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1h 13m

This course is focused on creating practical solutions using Azure technologies in areas such as AI, messaging, the Internet of Things, and video media. This will require familiarity with dozens of Azure solutions.

This course will take you through all of the relevant technologies and ensure you know which ones to pick to solve specific problems. This course is for developers, engineering managers, and cloud architects looking to get a better understanding of Azure services.

Whether your app deals with artificial intelligence, managing IoT devices, video media, or push notifications for smartphones, Azure has an answer for every use case. This course will help you get the most out of your Azure account by preparing you to make use of many different solutions.

Learning Objectives

  • Design solutions using Azure AI technologies

  • Design solutions for IoT applications using Azure technologies

  • Create a scalable messaging infrastructure using Azure messaging technologies

  • Design media solutions using Azure media technologies and file encoding

Intended Audience

  • People who want to become Azure cloud architects


  • General knowledge of IT architecture


We will wrap up our lesson on Azure Media with a discussion on media file encoding and an introduction to the Azure Media Analytics tool set.

We aren’t going to go super deep here with respect to compression algorithms or the history of different codecs. For our purposes you just need to know what a video codec is. It is simply a piece of software that compresses or decompresses digital media. An encoder is for compression and a decoder is for decompression, and the codec is the software doing the work. Generally when we talk about encoding we are talking about audio or video files. There are numerous formats such as mp3, wma, mp4. Some forms are lossy or lossless depending on the compression algorithms used. Lossy formats usually take far less space but will lose information over time as the file is compressed and decompressed. Lossless formats take more space but maintain their quality over time. This is why your hipster friend is really into using FLAC for his music collection.

So our focus is file-based encoding. File-based encoding, as you might have guessed, relies on video files. These will be the inputs and outputs for your codec software. So you will start with some raw video file taken from a camera or other source, run that through an encoding program, and the output will be a compressed version of the video that will use less space and be playable in a wide range of media players.

Microsoft Azure has its own Encoding service. See the link below for the full list of supported input file types and output file options. Suffice to say, with Azure Encoding, you should have everything you need to get your video content properly formatted for delivery. The trickier question may be deciding which version of the service to use. Azure offers both a standard and a “Premium Workflow” version. Pause the video on this slide to get a thorough look at the feature differences. Probably the biggest advantage for Premium is the ability to apply conditional logic on file encoding. This will allow you to automate encoding rules and thereby encode large numbers of files quickly. If you only have a small number of video files to manage, the standard service may suit you just fine.

(List of formats: https://docs.microsoft.com/en-us/azure/media-services/previous/media-services-compare-encoders)

In the last part of this section, with the other Azure media services and file encoding now behind us, we will talk about how to gain useful insights from our media using Azure Media Analytics. As you can see in the diagram Media Analytics works in parallel with the components responsible for encoding, streaming, and storing your media.

Media Analytics is actually a combination of several small tools that work together to give you useful intelligence on your video content. There is the Indexer service that makes your content searchable and helps generate closed-captioning tracks. There is the Hyperlapse service that adds video stabilization and time-lapse capability. There is an optical character recognition tool as well as a face and motion detector application. There is a tool for face redaction if needed for legal or security purposes. There are also content moderation and video summarization systems to make administration of large amounts of video content simpler.

Azure Media Analytics is your one stop shop for efficiently analyzing and optimizing your video library. It can save you thousands by baking together several tools that would be expensive if purchased separately.

So that about wraps it up for our lesson on encoding and media analytics. Congratulations. You are now an expert on media management with Azure. Great job!

About the Author

Jonathan Bethune is a senior technical consultant working with several companies including TopTal, BCG, and Instaclustr. He is an experienced devops specialist, data engineer, and software developer. Jonathan has spent years mastering the art of system automation with a variety of different cloud providers and tools. Before he became an engineer, Jonathan was a musician and teacher in New York City. Jonathan is based in Tokyo where he continues to work in technology and write for various publications in his free time.