Docker Desktop Enterprise Preview: Version Packs

This is the first in a series of articles we are publishing to provide more details on Docker Desktop Enterprise, which we announced at DockerCon Barcelona. Keep up with the latest Docker Desktop Enterprise news and release updates by signing up for the Docker Desktop Enterprise announcement list.

Docker’s engineers have been hard at work completing features and getting everything in ship-shape (pun intended) following our announcement of Docker Desktop Enterprise, a new desktop product that is the easiest, fastest and most secure way to develop production-ready containerized applications and the easiest way for developers to get Kubernetes running on their own machine.
In the first post of this series I want to highlight how we are working to bridge the gap between development and production with Docker Desktop Enterprise using our new Version Packs feature. Version Packs let you easily swap your Docker Engine and Kubernetes orchestrator versions to match the versions running in production on your Docker Enterprise clusters. For example, imagine you have a production environment running Docker Enterprise 2.0. As a developer, in order to make sure you don’t use any APIs or incompatible features that will break when you push an application to production you would like to be certain your working environment exactly matches what’s running in Docker Enterprise production systems. With Docker Desktop Enterprise you can easily do that through the use of Version Packs. Later, when the platform operators decide to upgrade production systems to Docker Enterprise 2.1, all that needs to be done in Docker Desktop Enterprise is to add the Enterprise 2.1 version pack and easy as that, you’re in sync. If you have different environments, you can even switch back forth, all with a single click.
 



We’re building Docker Desktop Enterprise as a cohesive extension of the Docker Enterprise container platform that runs right on developers’ systems. Developers code and test locally using the same tools they use today and Docker Desktop Enterprise helps to quickly iterate and then produce a containerized service that is ready for their production Docker Enterprise clusters.

In future previews, we’ll share more details on how Docker Desktop Enterprise capabilities can be centrally administered and controlled; using the Application Designer to create an application with zero Docker CLI commands; and how to ensure developers start building with safe, approved templates. Sign up for the Docker Desktop Enterprise announcement list or keep watching this blog for more in the coming weeks.

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To learn more:

Sign up for Docker Desktop Enterprise announcements
Check out the Docker Desktop Enterprise demonstration from DockerCon Barcelona
Get started with the free Docker Desktop Community and run some containers [ Windows | macOS ]

The post Docker Desktop Enterprise Preview: Version Packs appeared first on Docker Blog.
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Live stream analysis using Video Indexer

Video Indexer is an Azure service designed to extract deep insights from video and audio files offline. This is to analyze a given media file already created in advance. However, for some use cases it's important to get the media insights from a live feed as quick as possible to unlock operational and other use cases pressed in time. For example, such rich metadata on a live stream could be used by content producers to automate TV production, like our example of EndemolShine Group, by journalists of a newsroom to search into live feeds, to build notification services based on content and more.

To that end, I joined forces with Victor Pikula a Cloud Solution Architect at Microsoft, in order to architect and build a solution that allows customers to use Video Indexer in near real-time resolutions on live feeds. The delay in indexing can be as low as four minutes using this solution, depending on the chunks of data being indexed, the input resolution, the type of content and the compute powered used for this process.

Figure 1 – Sample player displaying the Video Indexer metadata on the live stream

The stream analysis solution at hand, uses Azure Functions and two Logic Apps to process a live program from a live channel in Azure Media Services with Video Indexer and displays the result with Azure Media Player showing the near real-time resulted stream.

In high level, it is comprised of two main steps. The first step runs every 60 seconds, and takes a sub-clip of the last 60 seconds played, creates an asset from it and indexes it via Video Indexer. Then the second step is called once indexing is complete. The insights captured are processed, sent to Azure Cosmos DB, and the sub-clip indexed is deleted.

The sample player plays the live stream and gets the insights from Azure Cosmos DB, using a dedicated Azure Function. It displays the metadata and thumbnails in sync with the live video.

Figure 2 – The two logic apps processing the live stream every minute in the cloud.

Near real-time indexing for video production

At the EBU Production Technology Seminar in Geneva last month, an end-to-end solution was demonstrated by Microsoft. Several live feeds were ingested to Azure using Dejero technology or the webRTC protocol, and sent to Make.TV Live Video Cloud to switch inputs. The selected input was sent as a transcoded stream to Azure Media Services for multi bitrate transcoding and OTT delivery in low latency mode.  The same stream was also processed in near real time with Video Indexer.

Figure 3 – Example of live stream processing in Azure

Next steps

The full code and a step-by-step guide to deploy the results can be found in this GitHub project for Live media analytics with Video Indexer. Need near real-time analytics for your content? Now you have a ready-made solution for that, go ahead and give it a try!

Have questions or feedback? We would love to hear from you! Visit our UserVoice to help us prioritize features, or email VISupport@Microsoft.com with any questions.
Quelle: Azure