Skip to main content
Redhat Developers  Logo
  • AI

    Get started with AI

    • Red Hat AI
      Accelerate the development and deployment of enterprise AI solutions.
    • AI learning hub
      Explore learning materials and tools, organized by task.
    • AI interactive demos
      Click through scenarios with Red Hat AI, including training LLMs and more.
    • AI/ML learning paths
      Expand your OpenShift AI knowledge using these learning resources.
    • AI quickstarts
      Focused AI use cases designed for fast deployment on Red Hat AI platforms.
    • No-cost AI training
      Foundational Red Hat AI training.

    Featured resources

    • OpenShift AI learning
    • Open source AI for developers
    • AI product application development
    • Open source-powered AI/ML for hybrid cloud
    • AI and Node.js cheat sheet

    Red Hat AI Factory with NVIDIA

    • Red Hat AI Factory with NVIDIA is a co-engineered, enterprise-grade AI solution for building, deploying, and managing AI at scale across hybrid cloud environments.
    • Explore the solution
  • Learn

    Self-guided

    • Documentation
      Find answers, get step-by-step guidance, and learn how to use Red Hat products.
    • Learning paths
      Explore curated walkthroughs for common development tasks.
    • Guided learning
      Receive custom learning paths powered by our AI assistant.
    • See all learning

    Hands-on

    • Developer Sandbox
      Spin up Red Hat's products and technologies without setup or configuration.
    • Interactive labs
      Learn by doing in these hands-on, browser-based experiences.
    • Interactive demos
      Click through product features in these guided tours.

    Browse by topic

    • AI/ML
    • Automation
    • Java
    • Kubernetes
    • Linux
    • See all topics

    Training & certifications

    • Courses and exams
    • Certifications
    • Skills assessments
    • Red Hat Academy
    • Learning subscription
    • Explore training
  • Build

    Get started

    • Red Hat build of Podman Desktop
      A downloadable, local development hub to experiment with our products and builds.
    • Developer Sandbox
      Spin up Red Hat's products and technologies without setup or configuration.

    Download products

    • Access product downloads to start building and testing right away.
    • Red Hat Enterprise Linux
    • Red Hat AI
    • Red Hat OpenShift
    • Red Hat Ansible Automation Platform
    • See all products

    Featured

    • Red Hat build of OpenJDK
    • Red Hat JBoss Enterprise Application Platform
    • Red Hat OpenShift Dev Spaces
    • Red Hat Developer Toolset

    References

    • E-books
    • Documentation
    • Cheat sheets
    • Architecture center
  • Community

    Get involved

    • Events
    • Live AI events
    • Red Hat Summit
    • Red Hat Accelerators
    • Community discussions

    Follow along

    • Articles & blogs
    • Developer newsletter
    • Videos
    • Github

    Get help

    • Customer service
    • Customer support
    • Regional contacts
    • Find a partner

    Join the Red Hat Developer program

    • Download Red Hat products and project builds, access support documentation, learning content, and more.
    • Explore the benefits

Introducing the Red Hat OpenShift Virtualization incident must-gather

New VM Incident Collection Mode in kubevirt/must-gather Tool

August 14, 2026
Fabian Deutsch Simone Tiraboschi
Related topics:
Virtualization
Related products:
Red Hat OpenShift Virtualization

    Investigating virtual machine (VM) incidents, such as Microsoft Windows kernel panics ("Blue screen of death", or BSOD for short) or I/O hangs, traditionally required running a cluster-wide must-gather combined with sosreport, which could potentially take hours to run. This approach is resource-intensive, slow to collect, and produces a large dataset that's difficult to review efficiently

    To address this, we have introduced a new --vm-incident mode to the kubevirt/must-gather tool.

    Why better incident reporting is needed

    The goal is to provide a collection mechanism specifically for issues that impact one, or a small subset of VMs. When a VM is failing, investigators typically need data from a specific node at a specific time. Instead of gathering cluster-wide data, and --vm-incident allows you to isolate the scope to:

    • The specific VM involved
    • The node where the VM was running at the incident time
    • A defined time window around the incident

    What it does

    When invoked, the tool uses PromQL to automatically identify the node running your VM at the specified incident time. It then sets a collection window of [Incident Time - 24h, Incident Time + 2h] to capture relevant context.

    This mode collects a complete view of the virtualized stack, including:

    • Host data: dmesg, time-scoped system journal and kubelet logs, hardware inventory (dmidecode, lspci, kernel boot parameters), storage diagnostics (mountstats, diskstats, I/O/memory/CPU pressure), networking state (interfaces, bridges, VLANs, firewall rules, NetworkManager logs), NFS deep diagnostics, SR-IOV/VFIO device state, kernel tunables (sysctl), tuned profiles, time synchronization (chrony), and a curated kernel red-flags log that surfaces OOM kills, QEMU crashes, NFS errors, and hung tasks.
    • VM context: VM/VMI definitions, PVC/PV/StorageClass chains, VolumeAttachments, and namespace events
    • Live VM state: If the VM has not restarted since the incident (for example, it is still stuck on a BSOD), the tool captures live hypervisor state: virsh domain XML, block device lists, domain stats, block errors, QEMU logs, the guest serial console (containing kernel panic or BSOD output), and cgroup memory/CPU statistics for the QEMU process. If the VM has already rebooted, this data is automatically skipped since it would only reflect the new instance, not the one that experienced the incident.
    • Pod data: Time-scoped virt-launcher and virt-handler logs (including previous container logs).
    • Metrics: Incident-specific Prometheus metrics exported in OpenMetrics format.

    The archive generated includes an incident-summary.yaml file, which catalogs exactly what was collected and notes any skipped items with reasons, ensuring you know exactly what is in your data package.

    No day without AI

    Beyond human investigation, this structured, time-scoped approach to data collection is also expected to support AI-assisted root cause analysis. By providing a richer, more focused dataset, these archives offer the necessary context for AI models to more effectively correlate events and identify patterns that might be obscured in larger, less relevant data collections.

    From here we go

    You can use the new mode with the standard must-gather command:

    oc adm must-gather --image=quay.io/kubevirt/must-gather \
      -- NS=namespace VM=myvm \
      /usr/bin/gather --vm-incident \
      --incident-time=2026-07-16T10:00:00Z

    Replace the NS, VM, and --incident-time arguments with your specific details. The --incident-time should be provided in ISO-8601 format, representing the UTC time when the issue occurred.

    This feature is designed to reduce the time spent on incident investigation by minimizing noise. Please try it out in your environment and provide feedback or report issues directly in the kubevirt/must-gather repository.

    Related Posts

    • Troubleshoot Red Hat OpenShift Virtualization localnet with the netobserv command

    • How to use Red Hat Satellite to deploy virtual machines in Microsoft Azure

    • Deploy hosted control planes with OpenShift Virtualization: Split hub

    • Deploy hosted control planes with OpenShift Virtualization

    Recent Posts

    • Introducing the Red Hat OpenShift Virtualization incident must-gather

    • How llm-d routes model inference traffic on Amazon EKS

    • Replace LLM infrastructure guesswork with data-driven planning

    • Build a DIY pipeline for a trusted software supply chain

    • How to check if your model is supported by vLLM in Red Hat AI

    Red Hat Developers logo LinkedIn YouTube Twitter Facebook

    Platforms

    • Red Hat AI
    • Red Hat Enterprise Linux
    • Red Hat OpenShift
    • Red Hat Ansible Automation Platform
    • See all products

    Build

    • Developer Sandbox
    • Developer tools
    • Interactive tutorials
    • API catalog

    Quicklinks

    • Learning resources
    • E-books
    • Cheat sheets
    • Blog
    • Events
    • Newsletter

    Communicate

    • About us
    • Contact sales
    • Find a partner
    • Report a website issue
    • Site status dashboard
    • Report a security problem

    RED HAT DEVELOPER

    Build here. Go anywhere.

    We serve the builders. The problem solvers who create careers with code.

    Join us if you’re a developer, software engineer, web designer, front-end designer, UX designer, computer scientist, architect, tester, product manager, project manager or team lead.

    Sign me up

    Red Hat legal and privacy links

    • About Red Hat
    • Jobs
    • Events
    • Locations
    • Contact Red Hat
    • Red Hat Blog
    • Inclusion at Red Hat
    • Cool Stuff Store
    • Red Hat Summit
    © 2026 Red Hat

    Red Hat legal and privacy links

    • Privacy statement
    • Terms of use
    • All policies and guidelines
    • Digital accessibility
    Ask AI