With Azure Arc-enabled Machine Learning, you can bring AML open architecture into the existing external resources – such as, on-premise machines or 3rd party platforms (EKS, GKE, etc).
Data science team can operate ML jobs on any platforms anywhere, with Azure Machine Learning consistent manners.
Who is Azure Machine Learning for?
Machine Learning is for individuals and teams implementing MLOps within their organisation to bring ML models into production in a secure and auditable production environment.
Data scientists and ML engineers can use tools to accelerate and automate their day-to-day workflows. Application developers can use tools for integrating models into applications or services. Platform developers can use a robust set of tools, backed by durable Azure Resource Manager APIs, for building advanced ML tooling.
Enterprises working in the Microsoft Azure cloud can use familiar security and role-based access control for infrastructure. You can set up a project to deny access to protected data and select operations.
With Arc-enabled app services, you can bring Azure’s cloud-native tools and services to your existing infrastructure, enabling consistent development, operations, and security wherever your applications reside.
Modernise Your Application Management
Arc-enabled app services allow you to run Azure App Service, Azure Functions, and Azure Logic Apps in any environment, providing a unified platform for building, deploying, and scaling web apps, APIs, and automation workflows. For businesses aiming to modernise their application landscape, this means more flexibility, reduced complexity, and enhanced productivity.
Achieve Consistency Across Your Ecosystem
With Arc-enabled app services, your IT teams can maintain a consistent approach to application management and development, whether your resources are on-premises, in the cloud, or at the edge. This ensures that your applications meet compliance, security, and performance requirements, no matter where they are deployed.
Azure Arc makes it possible to run Azure data services on-premises, at the edge, and in public clouds using Kubernetes and the infrastructure of your choice.
Currently, the following Azure Arc-enabled data services are available:
Always current
Azure Arc-enabled data services such as SQL Managed Instance enabled by Azure Arc and Azure Arc-enabled PostgreSQL server receive updates on a frequent basis including servicing patches and new features similar to the experience in Azure. Updates from the Microsoft Container Registry are provided to you and deployment cadences are set by you in accordance with your policies. This way, on-premises databases can stay up to date while ensuring you maintain control. Because Azure Arc-enabled data services are a subscription service, you will no longer face end-of-support situations for your databases.
Elastic scale
Cloud-like elasticity on-premises enables you to scale databases up or down dynamically in much the same way as they do in Azure, based on the available capacity of your infrastructure. This capability can satisfy burst scenarios that have volatile needs, including scenarios that require ingesting and querying data in real time, at any scale, with sub-second response time.
Self-service provisioning
Azure Arc also provides other cloud benefits such as fast deployment and automation at scale. Thanks to Kubernetes-based orchestration, you can deploy a database in seconds using either GUI or CLI tools.
Unified management
Using familiar tools such as the Azure portal, Azure Data Studio, and the Azure CLI with the arc data extension, you can now gain a unified view of all your data assets deployed with Azure Arc. You are able to not only view and manage a variety of relational databases across your environment and Azure, but also get logs and telemetry from Kubernetes APIs to analyse the underlying infrastructure capacity and health. Besides having localised log analytics and performance monitoring, you can now leverage Azure Monitor for comprehensive operational insights across your entire estate.
Innovate at the Edge with Azure Edge and IoT
In today’s interconnected world, data is generated everywhere—at remote sites, on manufacturing floors, and within IoT devices. Azure Edge enables your business to process this data where it is created, reducing latency and delivering real-time insights. Whether you’re managing smart factories, enhancing supply chain visibility, or enabling remote work, Azure Edge ensures that your operations are efficient, scalable, and secure.
Simplify and Scale Your IoT Operations
With Azure IoT, you can easily connect, monitor, and manage IoT assets at scale. This is crucial for businesses investing in smart devices and sensors to automate and optimise operations. Azure IoT provides robust security, seamless integration with existing systems, and the flexibility to grow as your IoT deployments expand.
Azure IoT Operations Preview – enabled by Azure Arc is a unified data plane for the edge. Azure IoT Operations is a set of modular, scalable, and highly available data services that run on Azure Arc-enabled edge Kubernetes clusters. It enables data capture from various different systems and integrates with data modeling applications such as Microsoft Fabric to help organisations deploy the industrial metaverse.Â
Azure Arc-enabled Kubernetes allows you to attach Kubernetes clusters running anywhere so that you can manage and configure them in Azure. By managing all of your Kubernetes resources in a single control plane, you can enable a more consistent development and operation experience to run cloud-native apps anywhere and on any Kubernetes platform.
When the Azure Arc agents are deployed to the cluster, an outbound connection to Azure is initiated, using industry-standard SSL to secure data in transit.
Once clusters are connected to Azure, they’re represented as their own resources in Azure Resource Manager, and they can be organized using resource groups and tagging.
Azure Arc-enabled Kubernetes is updated on an ongoing basis. To stay up to date with the most recent developments, this article provides you with information about recent releases of the Azure Arc-enabled Kubernetes agents.
When any of the Arc-enabled Kubernetes agents are updated, all of the agents in the azure-arc namespace are incremented with a new version number, so that the version numbers are consistent across agents. When a new version is released, all of the agents are upgraded together to the newest version (whether or not there are functionality changes in a given agent), unless you have disabled automatic upgrades for the cluster.
Azure Arc-enabled VMware vSphere is an Azure Arc service that helps you simplify management of hybrid IT estate distributed across VMware vSphere and Azure. It does so by extending the Azure control plane to VMware vSphere infrastructure and enabling the use of Azure security, governance, and management capabilities consistently across VMware vSphere and Azure.
Arc-enabled VMware vSphere allows you to:
SQL Server enabled by Azure Arc extends Azure services to SQL Server instances hosted outside of Azure: in your data center, in edge site locations like retail stores, or any public cloud or hosting provider.
Azure Arc enables you to manage all of your SQL Server instances from a single point of control: Azure. As you connect your SQL Server instances to Azure, you get a single place to view the detailed inventory of your SQL Server instances and databases.
Microsoft Azure
VMware vSphere
If you are working with an on-premises VMware vSphere infrastructure, you can deploy new Windows Server virtual machine installed with SQL Server in an automated fashion using Terraform and onboard it as Azure Arc-enabled SQL Server.
Amazon Web Services
If you are working in a multi-cloud environment, you can deploy new a AWS EC2 instance installed with SQL Server in an automated fashion using Terraform and onboard it as Azure Arc-enabled SQL Server.
Google Cloud Platform
If you are working in a multi-cloud environment, you can deploy new a GCP instance installed with SQL Server in an automated fashion using Terraform and onboard it as Azure Arc-enabled SQL Server.
Unified Operations Use Cases
Once you have server resources projected into Azure with Azure Arc, you can start to use native Azure tooling to manage the servers as native Azure resources.
Azure Arc-enabled servers lets you manage Windows and Linux physical servers and virtual machines hosted outside of Azure, on your corporate network, or other cloud provider. For the purposes of Azure Arc, these machines hosted outside of Azure are considered hybrid machines. The management of hybrid machines in Azure Arc is designed to be consistent with how you manage native Azure virtual machines, using standard Azure constructs such as Azure Policy and applying tags
Microsoft Azure
VMware vSphere
If you are working with an on-premises VMware vSphere infrastructure, you can deploy new Windows or Linux virtual machines in an automated fashion using Terraform and onboard it as Azure Arc-enabled servers.
Amazon Web Services
If you are working in a multi-cloud environment, you can deploy new AWS EC2 instances in an automated fashion using Terraform and onboard it as Azure Arc-enabled servers.
Google Cloud Platform
If you are working in a multi-cloud environment, you can deploy new GCP instances in an automated fashion using Terraform and onboard it as Azure Arc-enabled servers.
HashiCorp Vagrant
If you don’t have any existing servers available, the scenarios in this section will guide you on using HashiCorp Vagrant to host a new server locally in order to simulate an “on-premises” server and onboard it as an Azure Arc-enabled server.
Unified Operations Use Cases
Once you have server resources projected into Azure with Azure Arc, you can start to use native Azure tooling to manage the servers as native Azure resources. The following scenarios show examples of using Azure management tools such as resource tags, Azure Policy, Log Analytics, and more with Azure Arc-enabled servers.
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