A lot is happening in the area of hybrid cloud in Microsoft Azure. Despite striving for perfection in the field of public cloud, there is still a large group of customers attached to private data centers. There are many reasons, such as data processing location, no fees for outbound Internet traffic, the possibility of using unusual private equipment, etc. Microsoft sees this trend and addresses it by developing the Azure Arc service – a single tool for multi-cloud management as well as hybrid / private and on-premises. See what has changed in Azure Arc after Ignite.
Azure Arc after Ignite gets new features!
Microsoft has got us used to the fact that after large events such as Ignite or Build, it announces news and moves services from Preview to General Availability. This is exactly the case this time, after the last Ignite which took place on March 2-4, 2021. Below, I will summarize the biggest changes to Azure Arc.
Azure Arc-enabled Kubernetes (GA)
Azure Arc-enabled Kubernetes is now generally available, allows organizations to connect, secure, and manage any Kubernetes cluster in their own data centers, multiple clouds, and the edge from the same Azure portal. Customers can deploy a common set of Kubernetes configurations across their clusters directly from the Azure Portal, consistently and at scale. Arc-enabled Kubernetes also allows developers to program and securely deploy applications to any Kubernetes cluster at any location using GitOps.
Azure Arc-enabled Machine Learning (Preview)
Azure Arc-enabled machine learning is in preview, which means customers can innovate with Azure Machine Learning by running model training from any Kubernetes cluster, be it on-premises, in any cloud or edge. Organizations can leverage their existing Kubernetes infrastructure investments to lower costs and increase operational efficiency by modernizing machine learning to run close to where the data is and automatically scale it anywhere.
In addition, Azure Arc provides management, consistency, and reliability so that all resources can be managed through one unified panel in Azure. With the simple deployment of a machine learning agent, data scientists and developers can create models using familiar tools in Azure Machine Learning without having to learn Kubernetes. All models, wherever built, can be stored and tracked centrally in Azure Machine Learning for sharing, repeatability, and compliance. Starting today, customers can register here to access the preview.
FastTrack for Azure extended with a hybrid approach
FastTrack for Azure is a technical support program that helps in the implementation of cloud solutions, now offers new services:
- Acceleration of production deployments for cloud-native applications, so customers can receive best implementation practices for applications running on Kubernetes, OpenShift, serverless and event-driven applications.
- Hybrid deployment support / Azure Arc, starting with servers.
Azure Arc after Ignite gaining importance
The management of Kubernetes with Azure Arc which entered GA, shows that Microsoft is addressing the problems of on-premises environments with increasing care. It seems to be a very interesting path, more and more consistent and ready for local markets. Organizations can use private data centers they have already invested in, adding one common viewpoint in Azure and increasing the ability to manage multi-cloud in parallel with on-premises, maintaining a uniform level of security and quality of their services.