{"id":25059,"date":"2026-08-13T09:00:00","date_gmt":"2026-08-13T16:00:00","guid":{"rendered":"https:\/\/research.codeghost.online\/insidetrack\/blog\/?p=25059"},"modified":"2026-08-12T17:19:57","modified_gmt":"2026-08-13T00:19:57","slug":"resolving-repetitive-support-tickets-at-microsoft-with-ai-automation","status":"publish","type":"post","link":"https:\/\/research.codeghost.online\/insidetrack\/blog\/resolving-repetitive-support-tickets-at-microsoft-with-ai-automation\/","title":{"rendered":"Resolving repetitive support tickets at Microsoft with AI automation"},"content":{"rendered":"\n

Across Microsoft, our product teams rely on lab environments to develop, test, validate, and troubleshoot products before they reach customers. These labs are typically made up of virtual machines (VMs) that can be quickly deployed and scaled as needed.<\/p>\n\n\n\n

At Microsoft Digital, the company\u2019s IT organization, we now offer Managed Cloud Labs (formerly known as MyWorkspace), a self-service, Azure-based platform that enables our employees to create and manage the lab environments they need. With more than 150,000 VMs hosted in Managed Cloud Labs across the organization, keeping those environments healthy is essential to maintaining engineering productivity.<\/p>\n\n\n\n

When a VM becomes unavailable, however, diagnosing the issue can require significant manual effort. Today, an engineer may begin troubleshooting by attempting to access the VM, reviewing logs, and running diagnostic commands to identify the root cause. While this process can sometimes resolve the problem, it requires the engineer to remain actively involved throughout the investigation, validating findings and testing potential fixes.<\/p>\n\n\n\n

At the scale of Managed Cloud Labs, even routine VM issues can add up to a significant productivity cost. That’s why our team went looking for a way to automate troubleshooting. The answer was AI.<\/p>\n\n\n\n

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\u201cThe Troubleshooting Agent is the first integration of Azure Serial Console and AI that streamlines VM troubleshooting. It significantly reduces the toll on support engineers and speeds up problem resolution.\u201d<\/p>\nDominika Bobik, technical lead, Azure Serial Console<\/cite><\/blockquote>\n\n\n\n

We and our partners on the product group side engineered a solution for Managed Cloud Labs VMs using Azure Serial Console and agentic AI. This approach\u2014which includes an Info Agent and a Troubleshooting Agent\u2014has been a great success, allowing engineers to identify what\u2019s broken and repair the issue in minutes instead of hours.<\/p>\n\n\n\n

\u201cThe Troubleshooting Agent is the first integration of Azure Serial Console and AI that streamlines VM troubleshooting,\u201d says Dominika Bobik, a technical lead in the Azure Serial Console product group. \u201cIt significantly reduces the toll on support engineers and speeds up problem resolution.\u201d<\/p>\n\n\n\n

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Learn more<\/strong><\/strong><\/p>\n\n\n\n

Read more of our stories about Managed Cloud Labs.<\/a><\/p>\n<\/div>\n<\/div>\n\n\n\n

A new path for VM support issues<\/h2>\n\n\n\n

When we analyzed our support incidents, two recurring challenges emerged: Users needed faster answers to everyday how-to questions, and they needed a quicker path to resolution when remote access to their virtual machines via Remote Desktop Protocol (RDP) failed.<\/p>\n\n\n\n

For how-to questions, the issue usually wasn\u2019t the platform. Our employees were often blocked because they needed assistance with straightforward tasks: How to change a password, update a lab quota, or deploy a custom workspace.<\/p>\n\n\n\n

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\u201cWe had a lot of repetitive how-to questions, where the answers could be found in our user guide. An AI agent made more sense because as the product changes, we update the user guide\u2014our one source of truth\u2014and the Info Agent always provides the latest instructions.\u201d<\/p>\nThien-Y Le, senior product manager, Microsoft Digital<\/cite><\/blockquote>\n\n\n\n

Connectivity issues are more disruptive. When our employees can\u2019t use RDP to connect to a virtual machine, diagnosing the problem means checking across networks, OS configuration, and Azure infrastructure to determine which layer has failed. This typically results in a work stoppage, unless they can quicky recreate the lab.<\/p>\n\n\n\n

In some cases, rebuilding a lab may take only a few minutes. However, many of our customers rely on highly customized virtual machines that have been fine-tuned over years to fit their environments. These labs are essential for investigations, troubleshooting, and development work, and rebuilding them can take much longer. Being unable to remotely access a provisioned lab can also become a critical blocker for active customer case work. These kinds of labs require immediate attention.<\/p>\n\n\n\n

Those experiences shaped our Managed Cloud Labs Agent Experience solution, which pairs an Info Agent for user education and a Troubleshooting Agent for connectivity issues. The Info Agent answers how-to questions conversationally, using retrieval-augmented generation (RAG) to draw from internal documentation as well as the user guide.<\/p>\n\n\n\n

\u201cWe had a lot of repetitive how-to questions, where the answers could be found in our user guide,\u201d says Thien-Y Le, a senior product manager in Microsoft Digital. \u201cAn AI agent made more sense because as the product changes, we update the user guide\u2014our one source of truth\u2014and the Info Agent always provides the latest instructions.\u201d<\/p>\n\n\n\n

Automating the troubleshooting process<\/h2>\n\n\n\n

The Troubleshooting Agent changes the support model. When one of our engineers selects a virtual and reports an RDP problem, the agent investigates the VM, diagnoses the cause, and attempts a repair. Throughout the session, it gives the user a running summary of what it\u2019s detecting and the actions it\u2019s taking, making the automated work visible to the user but also \u201chands-free.\u201d<\/p>\n\n\n\n

When RDP or run commands are broken, our support engineers would typically turn to Azure Serial Console as an expedient path to the VM when all else fails. The Troubleshooting Agent automatically takes that same serial console path, but adding an AI agent to the process required retooling to automate the human action.<\/p>\n\n\n\n

Our team built an orchestrated crew of AI agents behind that user experience. We used Microsoft Foundry to host our models and Microsoft Agent Framework to manage the overall troubleshooting workflow and orchestrate the different agents. To help with evaluations, we utilized the Azure AI Evaluation software development kit.<\/p>\n\n\n\n

A session begins with programmatic checks, then moves on to a read-only diagnostic orchestrator agent that decides what information to gather and tools to use. It can query Azure resource health, call Managed Cloud Labs APIs, and route work to a specialized Windows RDP diagnostic agent that drives the serial console.<\/p>\n\n\n\n

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\u201cWe deliberately break test VMs in dozens of ways and expect the Troubleshooting Agent to repair them, then run evals to make sure the fixes are safe and consistent.\u201d<\/p>\nJoshua Deans, senior software engineer, Microsoft Digital<\/cite><\/blockquote>\n\n\n\n

The process reads early signals. For example, if Azure resource health points to a clear problem, the orchestrator stops there instead of running more complex diagnostics. When the system identifies an issue it can safely address, an auto-repair orchestrator restarts the VM, resets a password and network interface, or sends serial console commands to correct a configuration problem. It then validates whether the fix has succeeded before closing the loop.<\/p>\n\n\n\n

When the agent can’t safely resolve something, because the fix carries risk or the issue falls outside its known scenarios, it provides the full diagnostic context to the user. This context can then be given to a human support engineer, who can pick up the thread from there instead of starting over.<\/p>\n\n\n\n

Making that reliable across the many Windows operating systems that Managed Cloud Labs supports took a lot of testing and careful tuning under close collaboration with the Azure Serial Console product group.<\/p>\n\n\n\n

\u201cWe deliberately break test VMs in dozens of ways and expect the Troubleshooting Agent to repair them, then run evals to make sure the fixes are safe and consistent,\u201d says Joshua Deans, a senior software engineer in Microsoft Digital.<\/p>\n\n\n\n

Decreasing wait times<\/h2>\n\n\n\n

Our Troubleshooting Agent targets the 20% of ticket volume that comes from the common issues our support team typically resolves without escalation. The Info Agent addresses another 30% to 40%. Together, the team aims to take on about half of all ticket volume.<\/p>\n\n\n\n

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\u201cWith the Troubleshooting Agent, the same class of issue that once took more than 90 minutes to resolve is identified in less than 10 minutes. The agent provides immediate self-remediation to reduce downtime and has become an essential part of my workflow.\u201d<\/p>\nHrishi Deshpande, senior tech support engineer, Microsoft Exchange<\/cite><\/blockquote>\n\n\n\n

In the first month of using the Troubleshooting Agent, we were able to:<\/p>\n\n\n\n