Agentic cloud ops with the new Azure Copilot

Microsoft unveiled its awkwardly named Copilot in Azure back in 2024. That was followed by the Azure Model Context Protocol Server, called from the GitHub Copilot agent in Visual Studio Code. Now, Microsoft is putting the band back together, with a new Azure Copilot that builds on both earlier projects to deliver a set of useful tools for all parts of the cloud application life cycle: for infrastructure as a service and platform as a service.

Announced at Ignite 2025, the new Azure Copilot is a collection of specialized agents that can help you with a wide selection of different cloud management tasks, either on their own or working together. The original Copilot in Azure was an assistive chatbot, useful but unable to execute actions. You had to copy and paste responses into the Azure CLI or follow instructions in the portal.

Introducing agentic cloud ops

The revamped Azure Copilot is much more sophisticated, providing an orchestration layer for its component agents, an approach that Microsoft is calling “agentic cloud ops.” There’s a certain logic to this, considering how complex the Azure management surface has become. Under the portal or through the CLI, you interact with dozens of different services daily, often more.

Azure is complex and ever-changing. New services launch almost daily, and APIs update and change on a rapid cadence. Under the hood, tools and technologies like the TypeSpec language allow Microsoft to automate the process of documenting and publishing Azure’s APIs, delivering them as OpenAPI format documents. By standardizing the structure of its APIs, Microsoft has made it relatively simple for the latest generation of generative AI tools to parse and use them, generating the requisite calls and fielding responses, providing a natural language interface to the heart of Azure.

One key feature of the new Azure Copilot is that it works wherever you work, so you can access it in the portal, with a new agent dashboard, in a chat interface, or via the Azure CLI. This approach fits well with Microsoft’s long history of delivering tools that surface where they’re needed, making them part of your workflow instead of you having to be part of theirs.

Six new agents make up the Azure Copilot stack: Migration Agent, Deployment Agent, Observability Agent, Optimization Agent, Resiliency Agent, and Troubleshooting Agent. The intent is to support key pieces of the Azure operations platform, leaving the Azure MCP server in Visual Studio Code to support cloud development. The agents themselves have access to Azure tools and APIs, as well as knowledge bases like Learn. They can also use your deployed resources in the Azure Resource Manager and the associated Azure Resource Graph.

Let’s take a look at the new Azure Copilot agents and their capabilities.

Migration Agent

The Migration Agent is intended to help bring on-premises applications into the cloud and is based on the existing Azure Migrate tools and processes. It includes agentless discovery tools to map your existing infrastructure, with support for offline operations. As well as mapping your infrastructure, the tool is application-aware and can help update and modernize systems, building the necessary infrastructure as code scripts in either Bicep or Terraform. These can be evaluated and tested before being run to ensure that the agent is building the correct infrastructure for you.

At the same time, the tool isn’t focused on a big-bang approach; you can work with it to define how to move applications instead of simply creating a network and deploying VMs. It provides security reports and risk analysis and provides advice and guidance on application modernization. This takes advantage of the tools in GitHub Copilot to update both.NET and Java code, fitting in with an application-focused migration. Along with new GitHub Copilot tools for migrating on-premises Oracle databases to cloud Azure databases, you can use this process to change platform elements.

Deployment Agent

Like other hyperscale cloud platforms, Azure has a set of best practices for deploying infrastructure and applications. The Azure Well-Architected Framework forms the basis of the Azure Copilot Deployment Agent and builds deployment plans from your goals, constructing the right infrastructure as code to build out a virtual infrastructure. The resulting Terraform plans can be added to GitHub and used in actions as part of a CI/CD pipeline.

One key point shows links to the spec-driven development model used in GitHub’s Spec Kit. You’re encouraged to write long prompts to describe the application or service you want to build. This isn’t like searching documentation; it’s providing a complete description of the application, the Azure services you want to use, and how you want them to function. Like SpecKit, the process of building out your infrastructure is interactive, with the agent requesting more information as needed.

There are links to other Azure services, so when the Deployment Agent generates a set of Terraform scripts, it offers additional analysis from the Azure pricing calculator so you can get a feel for how expensive it will be to deliver and run your infrastructure.

Observability Agent

Much of what is in the Azure Copilot extends existing tools, which makes sense and reduces the risks associated with generative AI. This approach allows the Observability Agent to build on Azure Monitor, using its investigation tools to help explore issues in your applications and infrastructure. A new Investigate button has been added to Azure Monitor alerts and produces a set of agent-generated probable causes for the underlying issue, mixing anomaly detection machine learning tools with generative AI natural language interfaces. The ML engine handles fault finding, and the agent’s generative AI component summarizes results and produces next steps.

The agent can access signals from across Azure’s services, allowing it to analyze logs from Azure Kubernetes Service and use context to link possibly related alerts. With modern cloud-native applications built on top of distributed systems, this last feature is surprisingly important as it can help connect what might at first glance be unrelated events that lead to failure.

Optimization Agent

Running on top of Azure is as much about managing costs as running applications and virtual infrastructures. The Azure Copilot Optimization Agent is targeted at finops practitioners, giving them tools to choose between actions that are ranked by how much they cost, their environmental impact, and how easy they are to implement. Options can include changing the underlying VM SKUs. The agent generates the scripts to move workloads to more efficient, lower cost virtual infrastructure.

The aim is to prevent finops teams from being surprised by costs, keeping bills aligned to usage and avoiding inefficient hardware choices. You’re less likely to need this tool if you’re using other Azure Copilot tools to deploy applications, but if you’re running existing implementations—especially lift-and-shift ones from on-premises data centers—it should help you get your Azure infrastructure under control.

Resiliency Agent

Azure offers a wide selection of features to make your infrastructure more resilient, but the complexity of many virtual infrastructures means that in many cases, you don’t often have all the relevant options enabled. The Resiliency Agent checks your resources to ensure that they are in more than one availability zone so data center outages don’t affect your operations. The agent can help build your failover and recovery plans, and even test processes by simulating failures. Here the agent uses information in the Azure Resource Graph to build reports and run necessary automations in case of infrastructure failures.

Troubleshooting Agent

The Troubleshooting Agent in Azure Copilot is designed to run diagnostics on your infrastructure and then provide a fix, either as a series of steps for you to walk through or, in some cases, a one-click automation. It’s available for all Azure services, but works best with AKS, Cosmos DB, and Azure-hosted VMs.

Not all failures get a one-click fix. In some cases, the best the agent can do is document the issue and generate a support ticket. However, that’s still useful as the agent has access to your logs and resources and can help diagnose issues and suggest fixes based on Microsoft’s internal data.

Finding a role for AI operations

The role of the new Azure Copilot is to orchestrate these agents, parsing your requests and then calling agent functions as needed. The result is an interesting combination of features that address common pain points across Azure operations. Initially, you’ll likely get the most use out of the Troubleshooting Agent, and your finops team (and your bottom line) will benefit from the Optimization Agent.

With a handful of agents in this first preview, Microsoft is clearly easing its Azure users into accepting AI-assisted operations. That’s a sensible move, as users need to trust Copilot, much like any human colleague, and Copilot needs to prove itself in action. Keeping Azure Copilot to a limited set of operations scenarios will allow Microsoft to see how it performs and help tune it before a wider release.