tart.run

Tart is a virtualization toolset for building, running, and managing macOS and Linux virtual machines on Apple Silicon. It is aimed at developers and teams who need fast, locally native VMs and who want those VMs to plug into existing automation, CI, and remote storage workflows. If you are running Intel-based Macs, non-Apple hardware, or need to manage large fleets of VMs across many hosts, Tart's core positioning does not fit those cases as directly.

What Tart actually does

At its core, Tart gives you a command-line-driven way to create and operate VMs on Apple Silicon. The project describes itself around four capabilities:

• Building, running, and managing VMs — both macOS and Linux guests on Apple Silicon hosts.
• Native performance — VMs run with hardware-level virtualization rather than emulation, so the guest architecture matches the host.
• Remote storage for VMs — VM images can live in remote storage rather than only on the local disk.
• Integrations with existing automations — the project lists GitHub, GitLab, and other CI systems among its integrations.

That combination matters because it treats VMs less as one-off local sandboxes and more as artifacts you can store, distribute, and run inside pipelines.

Who it is for

Tart fits best when your work looks like one of these:

It fits less well if your hosts are Intel Macs or Linux servers, since the toolset is explicitly scoped to Apple Silicon.

How the pieces relate

The documentation separates Tart into a few layers, which is useful for understanding what you would actually adopt:

The core toolset

This is the part that builds, runs, and manages individual VMs. You would start here to confirm the workflow suits you before adding anything else.

Integrations

Tart lists self-hosted CI, GitHub Actions, GitLab Runner, Buildkite, and Packer. These are the hooks that let a VM image become part of an automated build or test step rather than a manual task.

Orchestration with Orchard

Orchard is the scaling layer, with its own quick start, architecture and security notes, controller and worker deployment, CLI, cluster management, and API integration. If your need is "run many VMs across machines," this is the section that matters, not the core toolset alone.

What to check before committing

A few practical questions decide whether Tart is the right choice:

1. Are your hosts Apple Silicon? The toolset is scoped to Apple Silicon, so this is the first filter.
2. Do you need macOS guests specifically? That is where native Apple Silicon virtualization is hardest to replace.
3. Will VMs be shared or automated? If yes, the remote storage and CI integration features are the reason to pick Tart over a simpler local VM tool.
4. Do you need multi-host scale? If so, plan for Orchard as a separate adoption step with its own architecture and security considerations.

Getting oriented

The project's own entry points are the GitHub repository, a Quick Start guide, and separate Integrations and Orchestration sections. A sensible path is to read the Quick Start, run a single VM to confirm the native-performance workflow, then look at Integrations if you intend to wire VMs into CI, and only then evaluate Orchard if you need to run at scale.

Tart runs on Apple Silicon Macs and is used to build, run, and manage macOS and Linux virtual machines. The site describes it as a virtualization toolset for Apple Silicon with native performance, which points to host-level virtualization on the Mac rather than emulation. The available material does not mention Intel Macs or non-Apple hosts, so treat Apple Silicon as the supported platform and do not assume Tart will run on other hardware.

Host requirements

What this means in practice

If you are planning a setup, the first check is the machine itself: it needs to be an Apple Silicon Mac. From there, Tart is aimed at creating and managing macOS and Linux VMs, so both guest types are within scope. The "native performance" wording is the signal that this is virtualization on the host, not a translation layer, which matters when you are deciding whether Tart fits a workflow that depends on near-native speed.

For example, if your task is to run a Linux build environment alongside a macOS test VM on the same Apple Silicon machine, Tart's stated scope covers both guest types. If your task depends on an Intel-based Mac or a Linux host, the source gives no basis for that configuration, so verify before committing.

Where Tart fits beyond the local machine

The same toolset extends past a single Mac: the site lists remote storage for virtual machines, integrations with GitHub, GitLab, Buildkite, and Packer, and Orchard for running at scale with orchestration, including deploying controllers and workers and managing a cluster through the Orchard CLI and API. Those are relevant once your hardware question is settled and you are deciding how many hosts and how much automation you need.

Open points to confirm

The source does not state minimum macOS versions, RAM, or disk requirements for the host, nor does it describe pricing or licensing terms beyond a Support & Licensing section. Check those pages directly if your decision depends on a specific Mac model or budget.

Orchard is the orchestration component of Tart Virtualization, used to run macOS and Linux virtual machines at scale rather than one at a time on a single host. It is the right fit when you have outgrown local tart run workflows and need a cluster of machines to schedule VM workloads across. If you only build and run VMs on one Apple Silicon Mac, you do not need Orchard.

Where Orchard sits in the toolset

Tart itself is described as a virtualization toolset to build, run and manage macOS and Linux virtual machines on Apple Silicon, with native performance and remote storage for VMs. Orchard extends that from a single machine to a cluster. The site groups it under "Orchestration" with its own documentation set, separate from the core Tart and Integrations sections.

What Orchard covers

Based on the published documentation structure, Orchard includes:

• Quick Start — the entry path for getting an Orchard deployment running.
• Architecture and Security — how the cluster is put together and what security properties it assumes.
• Deploying Controller — standing up the controller component.
• Deploying Workers — adding worker machines that actually run VM workloads.
• Using Orchard CLI — a command-line interface for managing the cluster.
• Managing the Cluster — day-to-day cluster operations.
• Integrating with the API — programmatic access so Orchard can be driven by your own tooling.
• FAQ — a dedicated troubleshooting and common-questions page.

The controller/worker split is the key mechanism: the controller coordinates, and workers supply the compute that hosts VMs. That is what allows VM capacity to grow beyond a single Mac.

How it relates to CI and automation

Tart's integration surface already lists GitHub Actions, GitLab Runner, Buildkite and Packer. Orchard is the layer that makes those integrations viable when the number of concurrent VM jobs exceeds what one machine can host — the controller and workers provide the pool, and the API plus CLI provide the control points for automation. If your CI pipeline currently queues because a single Mac can only run so many simulators or builds at once, Orchard is the part of the product aimed at that problem.

When to choose Orchard, and when not to

Practical starting point

Read the Orchestration Quick Start first, then Architecture and Security before deploying anything, since the controller/worker model determines your network and machine layout. Use the CLI for interactive cluster management and the API for wiring Orchard into existing automation. Keep the FAQ open during initial deployment; it is the documented place for issues that come up.

One caution: the available site material does not state pricing, licensing terms for Orchard specifically, or hardware minimums beyond the Apple Silicon requirement for Tart. Check the Support & Licensing and Legal sections of the site before committing to a deployment plan.

Tart Virtualization's documentation is organized into six main sections on tart.run: Quick Start, Integrations, Orchestration, Support & Licensing, Legal, and Blog. Which one you need depends on whether you're setting up the core toolset, connecting it to CI systems, running VMs at scale with Orchard, or checking terms and updates. The site describes Tart as "a virtualization toolset to build, run and manage macOS and Linux virtual machines on Apple Silicon," so the docs assume Apple Silicon hardware throughout.

Start here: Quick Start for the core toolset

If you're new to Tart, the Quick Start section is the entry point for building, running, and managing macOS and Linux VMs locally. The site highlights three things this core toolset delivers:

• Native performance on Apple Silicon
• Remote storage for Virtual Machines
• Seamless integration with your existing automations

Use this section when your goal is to get a first VM running or to understand the basic build/run/manage workflow before adding automation or orchestration.

Integrations: CI and automation tools

The Integrations section covers connecting Tart to existing pipelines. The site lists these integrations:

Go here if your question is about wiring Tart into a specific CI system rather than running VMs by hand.

Orchestration: running at scale with Orchard

The Orchestration section is dedicated to Orchard, the component for running Tart "at scale." Its subpages are:

• Quick Start — getting Orchard running
• Architecture and Security — how the system is structured and secured
• Deploying Controller and Deploying Workers — the two deployment roles
• Using Orchard CLI — command-line management
• Managing the Cluster — ongoing cluster operations
• Integrating with the API — programmatic access

Choose this section when a single machine is no longer enough and you need a controller/worker cluster. If you only need to know what Orchard is at a conceptual level, the Architecture and Security page is the most direct read.

Support, licensing, and legal

The Support & Licensing section is where to look for commercial support and licensing terms. The Legal section holds the Terms of Service and Privacy pages. Check these before deploying in a commercial or regulated context, since licensing conditions may affect how you roll Tart out.

Blog and archive for updates

The Blog section, with a Blog Archive spanning 2023, 2024, and 2025, is where announcements are published. Posts are categorized (for example, "announcement" and "orchard"), so you can filter for release news or Orchard-specific changes. Check here when you want to know what's changed recently rather than how something works.

Choosing the right section

• First-time setup on a single Mac → Quick Start
• Connecting to GitHub Actions, GitLab, Buildkite, Packer, or self-hosted CI → Integrations
• Running many VMs across machines → Orchestration (start with Architecture and Security, then Deploying Controller/Workers)
• Licensing or commercial support questions → Support & Licensing
• Terms, privacy, or recent announcements → Legal or Blog

The site's top navigation also links directly to GitHub and Home, so source code and the landing page are one click away if the docs don't cover your case.

Tart Virtualization integrates with CI and automation tools by running macOS and Linux virtual machines on Apple Silicon as part of your existing pipelines. The site names GitHub Actions, GitLab Runner, Buildkite, and Packer as supported integrations, and describes "seamless integration with your existing automations." If your build or test workflow depends on macOS or Linux VMs and you run on Apple Silicon hardware, Tart is designed to slot into that pipeline rather than replace it.

What the integrations cover

The site groups its integration support into a few areas:

The common thread is that Tart VMs are provisioned as part of a pipeline step, so the same automation that builds and tests your code can also spin up the macOS or Linux environment it needs.

How the pieces fit together

Tart is described as a "virtualization toolset to build, run and manage macOS and Linux virtual machines on Apple Silicon," with "native performance" and "remote storage for Virtual Machines." In a CI context, that means:

• Build and run — VMs are created and started by the pipeline, not by hand.
• Manage — remote storage lets VM images live outside the individual machine, which matters when many pipeline runs need the same base image.
• Scale — the site points to Orchard for running "at scale," with a controller/worker architecture, a CLI for managing the cluster, and an API for integration.

A concrete example

Suppose a team maintains an iOS app and wants every pull request to run UI tests on a clean macOS VM. With Tart, the CI job would pull the VM image from remote storage, boot it on an Apple Silicon runner, run the tests, and tear the VM down — all as pipeline steps. The same pattern applies to a Linux VM for a build step, or to Packer building a fresh image that later pipeline runs consume.

What to check before adopting it

• Hardware: Tart targets Apple Silicon, so your CI runners need to be Apple Silicon machines (including self-hosted ones).
• Existing automation: The value comes from fitting Tart into pipelines you already run; the named integrations are the places to start.
• Scale needs: If you're running many VMs across machines, look at Orchard's controller/worker model and API rather than single-machine use.

The site does not publish pricing details in the material reviewed here, so confirm licensing and support terms directly before planning a rollout.