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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteCircleCI Machine Runner Orchestrator is for teams that need each self-hosted CI task to run inside a complete virtual machine and already operate Kubernetes with KubeVirt. It watches CircleCI demand, changes a KubeVirt VirtualMachinePool replica count, starts runner VMs when work appears, and removes them after jobs finish. That gives you VM-level operating-system behavior and isolation without keeping a permanently sized fleet, but it also makes your team responsible for Kubernetes, KubeVirt, KVM capacity, tokens, networking, permissions, and cleanup.
If your jobs mainly need custom Docker images in short-lived containers, Container Runner is usually the more natural model. If you already have specific physical or virtual machines and want the runner tied to those hosts, conventional machine runner is simpler. The orchestrator is the middle choice: demand-driven full VMs managed through a Kubernetes virtualization stack.
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What the orchestrator actually does
CircleCI describes Machine Runner Orchestrator as a Kubernetes controller that automatically scales CircleCI runner VMs using KubeVirt. It is not a new CircleCI executor or a replacement job syntax. It is an orchestration layer around self-hosted machine-runner VMs.
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A minReplicas value lets you keep a warm pool. A value of zero allows the pool to scale down completely when no task is pending, which saves idle capacity but means the next task must wait for VM startup. The currently listed orchestrator release is version 1.0.0.
What it does not change
Your CircleCI workflow still uses the machine executor and a self-hosted resource class. The runner is selected by the resource-class name, not by a CircleCI-hosted machine image alias. A job should set machine: true and target the class in the form <namespace>/<name>.
jobs:
build:
machine: true
resource_class: your-namespace/your-machine-class
steps:
- checkout
- run: ./ci/build.shThe namespace and class must exactly match the objects and token mapping configured for the orchestrator. A spelling mismatch sends the job to no eligible runner, even when VMs are healthy.
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- A workflow creates demand. CircleCI places a task in the queue for the self-hosted resource class selected by the job.
- The controller polls CircleCI. It uses task demand and current runner state to decide how many VMs are needed.
- The pool changes size. The controller updates the KubeVirt
VirtualMachinePoolreplica count within your configured bounds. - KubeVirt starts a guest. The VM boots on a Kubernetes node that can provide hardware-accelerated virtualization.
- The runner registers and claims work. The task executes in the VM rather than in a Kubernetes pod or on a permanently assigned host.
- The VM is removed after completion. Ephemeral teardown limits leftover state, although caches, disks, and external services still require an explicit policy.
This design separates scheduling from the VM image and host fleet. Kubernetes supplies placement and lifecycle management; KubeVirt supplies the virtual machines; CircleCI supplies task coordination and runner registration.
When a full VM is the right execution boundary
Operating-system-level behavior
Use the orchestrator when tests depend on kernel behavior, system services, boot-time configuration, device access, or other characteristics that are awkward to reproduce in a container. A full guest operating system can more closely match the environment shipped to customers or deployed on production-like hosts.
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Privileged or machine-specific tooling
Some build and test systems need privileged operations, custom virtualization tools, low-level networking, or software that expects a conventional machine rather than a container process. A VM provides a clearer boundary for those operations than sharing a container host.
Isolation between jobs
Each task gets a newly provisioned guest when the pool is configured for ephemeral operation. That can reduce cross-job contamination compared with a long-lived runner where files, services, package installs, and credentials may survive from one build to the next.
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Private or restricted infrastructure
Self-hosted execution is useful when jobs must reach private networks, use controlled static addresses, assume organization-specific cloud permissions such as AWS IAM roles, run operating-system monitoring, or use CPU architectures and infrastructure unavailable as CircleCI-hosted resource classes. Those are general self-hosted-runner motivations; validate the orchestrator’s networking and security design for your own environment.
When it is a poor fit
You do not operate Kubernetes and KubeVirt
The Helm chart does not install KubeVirt for you. You need an existing Kubernetes cluster, a separately installed and working KubeVirt deployment, and administrators who can troubleshoot both layers. If that operational capability is absent, a static machine runner may be less complex.
Your jobs are fundamentally container builds
Container Runner schedules container jobs in ephemeral Kubernetes pods and supports custom Docker images and Convenience Images. Machine Runner Orchestrator does not turn a machine job into a container job, and conventional machine runner is not compatible with Convenience Images or custom Docker images. Choose the container model when the image itself is the important environment boundary.
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You need predictable startup with no VM warm-up
With minReplicas: 0, no VM may exist while the queue is empty. Boot time, image preparation, node scheduling, and runner registration add latency to the first task. Keeping one or more replicas warm reduces that delay but consumes capacity while idle.
You cannot provide KVM-capable nodes
Every node that hosts runner VMs must expose /dev/kvm. Without hardware virtualization on bare metal or correctly configured nested virtualization on a cloud VM, guests remain pending or fail to start.
Execution-model comparison
| Option | Where the task runs | Best fit | Main trade-off |
|---|---|---|---|
| Machine Runner Orchestrator | A KubeVirt VM provisioned on demand in Kubernetes | Full VM behavior, stronger isolation, privileged access, and demand-based capacity are required | Requires Kubernetes, KubeVirt, KVM-capable nodes, VM image management, and capacity planning |
| Conventional machine runner | The VM or physical machine where the runner binary is installed | You have a specific host environment and do not need Kubernetes-based VM scaling | Each runner remains tied to its host; dependency drift, cleanup, and idle capacity are your responsibility |
| Container Runner | An ephemeral container in a Kubernetes pod | Jobs are designed around custom Docker images and container isolation | It is not a full-VM boundary and still requires Kubernetes operations |
Make the choice across six axes: required isolation, operating-system behavior, image and container support, existing Kubernetes/KubeVirt expertise, acceptable startup latency, and available host capacity. A full VM is not automatically more secure or faster; it changes which boundaries and operational duties you must manage.
Prerequisites before installation
- Kubernetes: a functioning cluster with scheduling capacity for the expected VM count.
- KubeVirt: installed separately and compatible with the orchestrator. CircleCI lists testing with KubeVirt v1.8.
- Virtualization: each eligible VM host must expose
/dev/kvm, using bare-metal hardware acceleration or supported nested virtualization. - Tooling: configured
kubectland Helm version 3 or newer. - CircleCI objects: an organization administrator must create the namespace and each self-hosted resource class.
- Tokens: a resource-class token is required for every class the chart provisions. CircleCI displays a newly created token only once, so store it in a secure secret-management system immediately.
- Network egress: permit outbound HTTPS to https://runner.circleci.com and https://circleci-binary-releases.s3.amazonaws.com. Checkout and persistence features may also need access to your version-control provider or CircleCI task-storage endpoint.
Inbound connectivity is not required by a self-hosted runner according to CircleCI’s FAQ. Treat outbound allow-listing as part of the design rather than discovering it after registration fails.
VM image and sizing decisions
The documented default VM specification is 2 GiB of memory and one CPU. The default uses a CircleCI-maintained Ubuntu 24.04 containerDisk with Docker and common CI tooling. Those values are starting points, not workload guarantees. Compilation, browser testing, large dependency graphs, databases, or parallel test processes may need substantially more memory, CPU, disk, or specialized images.
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Size the guest from measured peak requirements, then verify that the Kubernetes nodes can host several guests without memory pressure or CPU overcommit that harms job reliability. Set upper and lower replica bounds to protect cluster capacity. A high maximum can absorb bursts but can also consume all schedulable resources; a low maximum protects the cluster but leaves tasks queued during spikes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Deployment outline
The exact chart values and token fields are version-specific, so use the 1.0.0 orchestrator guide while applying this sequence:
- Create the CircleCI namespace and resource class. Record the fully qualified class name and copy each token into secure storage when it is shown.
- Create a Kubernetes namespace dedicated to the orchestrator and runner resources, following your cluster’s naming and access policy.
- Prepare Helm values. Map every CircleCI resource class to its token, set replica minimums and maximums, and define the VM specification appropriate for the workload.
- Install chart version 1.0.0 with Helm 3 or newer. The public image and chart do not require registry credentials or an invitation, according to CircleCI.
- Inspect the deployment. Confirm the controller pods are running, the KubeVirt
VirtualMachinePoolexists, and logs show successful polling and authentication. - Check VM readiness. Verify that a test task causes a guest to appear, register, claim work, and terminate after completion.
- Configure the CircleCI job. Use
machine: trueand the exact self-hostedresource_class; do not add a CircleCI-hostedmachine.imagealias.
Do not treat installation as complete until you have observed the complete lifecycle. A running controller alone does not prove that KubeVirt can schedule, boot, register, and clean up a runner VM.
CircleCI Server considerations
For CircleCI Server, the default API address in the guide points to CircleCI Cloud at https://runner.circleci.com. Set provisioner.circleciAPIAddr to the Server hostname instead, and supply the API-token settings required by that Server installation. Without the Server address, newly created VMs attempt to register with the wrong instance and cannot accept work.
Cloud 1.0.0 can poll task counts with resource-class tokens, while the personal API token is optional for legacy /tasks endpoints. Server deployments may differ, so verify the current version-specific token behavior before removing or reusing credentials.
Security and operations checklist
Identity and privilege
Choose the operating-system user under which machine-runner jobs execute and limit that user’s permissions to what builds actually need. Access to a Docker daemon is equivalent to root access on the machine. Do not grant unrestricted Docker access merely to make a build pass; isolate privileged workflows and protect credentials mounted into the guest.
State and reproducibility
Prefer disposable state so a task starts from a known image and cannot inherit secrets or modified tools from an earlier task. Persistent caches can shorten builds, but they can also reduce reproducibility, fill disks, and increase billable usage. Define what is cached, where it is stored, who can read it, and how it is invalidated.
Capacity and scheduling
- Label or otherwise constrain nodes so only KVM-capable hosts receive runner VMs.
- Monitor KubeVirt readiness, VM pending time, node memory, CPU allocation, and disk pressure.
- Set
minReplicasfrom an explicit latency target rather than copying a default. - Set maximum replicas below the point where CI could starve application workloads or system components.
Optional SSH reruns
SSH rerun support is disabled by default. Enabling it requires a Gateway API implementation that supports TCPRoute; follow the guide for the exact version and exposure model before opening that path.
Troubleshooting by symptom
| Symptom | Likely checks |
|---|---|
| No VM appears when a task is queued | Confirm the job’s resource-class spelling, token-to-class mapping, controller authentication, polling logs, and replica maximum. |
| VMs remain pending | Check node capacity, scheduling labels, KubeVirt readiness, and whether eligible nodes expose /dev/kvm. |
| VM boots but never claims work | Verify the CircleCI API address, outbound HTTPS, resource-class token, runner registration logs, and—on Server—the configured hostname. |
| First jobs are slow after idle periods | Raise minReplicas if the added idle capacity is acceptable, or document the cold-start delay for users. |
| Builds interfere with one another | Inspect whether guests are truly recreated, whether caches or external volumes persist, and whether the execution user can modify shared services. |
| Jobs fail after image changes | Compare the VM’s CPU, memory, disk, operating-system packages, Docker availability, and required privileged tooling with the workload’s actual needs. |
How to decide
Choose Machine Runner Orchestrator when the answer to both questions is yes: “Does this workload need a complete VM or machine-level boundary?” and “Can our team run KubeVirt on KVM-capable Kubernetes nodes?” Then validate warm-pool latency, guest sizing, network egress, token handling, and cleanup before moving production workflows.
Choose conventional machine runner when a stable, known host is more valuable than automatic VM lifecycle management. Choose Container Runner when a custom Docker image and ephemeral pod are the natural abstraction. The orchestrator is valuable precisely when neither of those models supplies the operating-system behavior, isolation, or private infrastructure access your jobs require.
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