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We aim to support the last 10 releases of the Tailscale client on all provided operating systems and platforms. Some platforms might require additional configuration to connect with headscale.
OS | Supports headscale |
---|---|
Linux | Yes |
OpenBSD | Yes |
FreeBSD | Yes |
Windows | Yes (see docs and /windows on your headscale for more information) |
Android | Yes (see docs for more information) |
macOS | Yes (see docs and /apple on your headscale for more information) |
iOS | Yes (see docs and /apple on your headscale for more information) |
tvOS | Yes (see docs and /apple on your headscale for more information) |
We aim to support the last 10 releases of the Tailscale client on all provided operating systems and platforms. Some platforms might require additional configuration to connect with headscale.
OS | Supports headscale |
---|---|
Linux | Yes |
OpenBSD | Yes |
FreeBSD | Yes |
Windows | Yes (see docs and /windows on your headscale for more information) |
Android | Yes (see docs for more information) |
macOS | Yes (see docs and /apple on your headscale for more information) |
iOS | Yes (see docs and /apple on your headscale for more information) |
tvOS | Yes (see docs and /apple on your headscale for more information) |
Headscale is "Open Source, acknowledged contribution", this means that any contribution will have to be discussed with the maintainers before being added to the project. This model has been chosen to reduce the risk of burnout by limiting the maintenance overhead of reviewing and validating third-party code.
Headscale has a small maintainer team that tries to balance working on the project, fixing bugs and reviewing contributions.
When we work on issues ourselves, we develop first hand knowledge of the code and it makes it possible for us to maintain and own the code as the project develops.
Code contributions are seen as a positive thing. People enjoy and engage with our project, but it also comes with some challenges; we have to understand the code, we have to understand the feature, we might have to become familiar with external libraries or services and we think about security implications. All those steps are required during the reviewing process. After the code has been merged, the feature has to be maintained. Any changes reliant on external services must be updated and expanded accordingly.
The review and day-1 maintenance adds a significant burden on the maintainers. Often we hope that the contributor will help out, but we found that most of the time, they disappear after their new feature was added.
This means that when someone contributes, we are mostly happy about it, but we do have to run it through a series of checks to establish if we actually can maintain this feature.
A general description is provided here and an explicit list is provided in our pull request template.
All new features have to start out with a design document, which should be discussed on the issue tracker (not discord). It should include a use case for the feature, how it can be implemented, who will implement it and a plan for maintaining it.
All features have to be end-to-end tested (integration tests) and have good unit test coverage to ensure that they work as expected. This will also ensure that the feature continues to work as expected over time. If a change cannot be tested, a strong case for why this is not possible needs to be presented.
The contributor should help to maintain the feature over time. In case the feature is not maintained probably, the maintainers reserve themselves the right to remove features they redeem as unmaintainable. This should help to improve the quality of the software and keep it in a maintainable state.
Headscale is open to code contributions for bug fixes without discussion.
If you find mistakes in the documentation, please submit a fix to the documentation.
Headscale is "Open Source, acknowledged contribution", this means that any contribution will have to be discussed with the maintainers before being added to the project. This model has been chosen to reduce the risk of burnout by limiting the maintenance overhead of reviewing and validating third-party code.
Headscale has a small maintainer team that tries to balance working on the project, fixing bugs and reviewing contributions.
When we work on issues ourselves, we develop first hand knowledge of the code and it makes it possible for us to maintain and own the code as the project develops.
Code contributions are seen as a positive thing. People enjoy and engage with our project, but it also comes with some challenges; we have to understand the code, we have to understand the feature, we might have to become familiar with external libraries or services and we think about security implications. All those steps are required during the reviewing process. After the code has been merged, the feature has to be maintained. Any changes reliant on external services must be updated and expanded accordingly.
The review and day-1 maintenance adds a significant burden on the maintainers. Often we hope that the contributor will help out, but we found that most of the time, they disappear after their new feature was added.
This means that when someone contributes, we are mostly happy about it, but we do have to run it through a series of checks to establish if we actually can maintain this feature.
A general description is provided here and an explicit list is provided in our pull request template.
All new features have to start out with a design document, which should be discussed on the issue tracker (not discord). It should include a use case for the feature, how it can be implemented, who will implement it and a plan for maintaining it.
All features have to be end-to-end tested (integration tests) and have good unit test coverage to ensure that they work as expected. This will also ensure that the feature continues to work as expected over time. If a change cannot be tested, a strong case for why this is not possible needs to be presented.
The contributor should help to maintain the feature over time. In case the feature is not maintained probably, the maintainers reserve themselves the right to remove features they redeem as unmaintainable. This should help to improve the quality of the software and keep it in a maintainable state.
Headscale is open to code contributions for bug fixes without discussion.
If you find mistakes in the documentation, please submit a fix to the documentation.
Headscale aims to implement a self-hosted, open source alternative to the Tailscale control server. Headscale's goal is to provide self-hosters and hobbyists with an open-source server they can use for their projects and labs. It implements a narrow scope, a single Tailscale network (tailnet), suitable for a personal use, or a small open-source organisation.
Headscale is "Open Source, acknowledged contribution", this means that any contribution will have to be discussed with the Maintainers before being submitted.
Please see Contributing for more information.
Both maintainers have full-time jobs and families, and we want to avoid burnout. We also want to avoid frustration from contributors when their PRs are not accepted.
We are more than happy to exchange emails, or to have dedicated calls before a PR is submitted.
We don't know. We might be working on it. If you're interested in contributing, please post a feature request about it.
Please be aware that there are a number of reasons why we might not accept specific contributions:
We currently support deploying headscale using our binaries and the DEB packages. Visit our installation guide using official releases for more information.
In addition to that, you may use packages provided by the community or from distributions. Learn more in the installation guide using community packages.
For convenience, we also build container images with headscale. But please be aware that we don't officially support deploying headscale using Docker. On our Discord server we have a "docker-issues" channel where you can ask for Docker-specific help to the community.
It depends. As often stated, Headscale is not enterprise software and our focus is homelabbers and self-hosters. Of course, we do not prevent people from using it in a commercial/professional setting and often get questions about scaling.
Please note that when Headscale is developed, performance is not part of the consideration as the main audience is considered to be users with a moddest amount of devices. We focus on correctness and feature parity with Tailscale SaaS over time.
To understand if you might be able to use Headscale for your usecase, I will describe two scenarios in an effort to explain what is the central bottleneck of Headscale:
An environment with 1000 servers
An environment with 80 laptops/phones (end user devices)
Headscale calculates a map of all nodes that need to talk to each other, creating this "world map" requires a lot of CPU time. When an event that requires changes to this map happens, the whole "world" is recalculated, and a new "world map" is created for every node in the network.
This means that under certain conditions, Headscale can likely handle 100s of devices (maybe more), if there is little to no change happening in the network. For example, in Scenario 1, the process of computing the world map is extremly demanding due to the size of the network, but when the map has been created and the nodes are not changing, the Headscale instance will likely return to a very low resource usage until the next time there is an event requiring the new map.
In the case of Scenario 2, the process of computing the world map is less demanding due to the smaller size of the network, however, the type of nodes will likely change frequently, which would lead to a constant resource usage.
Headscale will start to struggle when the two scenarios overlap, e.g. many nodes with frequent changes will cause the resource usage to remain constantly high. In the worst case scenario, the queue of nodes waiting for their map will grow to a point where Headscale never will be able to catch up, and nodes will never learn about the current state of the world.
We expect that the performance will improve over time as we improve the code base, but it is not a focus. In general, we will never make the tradeoff to make things faster on the cost of less maintainable or readable code. We are a small team and have to optimise for maintainabillity.
We recommend the use of SQLite as database for headscale:
The headscale project itself does not provide a tool to migrate from PostgreSQL to SQLite. Please have a look at the related tools documentation for migration tooling provided by the community.
The choice of database has little to no impact on the performance of the server, see Scaling / How many clients does Headscale support? for understanding how Headscale spends its resources.
We don't know. We don't use reverse proxies with headscale ourselves, so we don't have any experience with them. We have community documentation on how to configure various reverse proxies, and a dedicated "reverse-proxy-issues" channel on our Discord server where you can ask for help to the community.
Running headscale on a machine that is also in the tailnet can cause problems with subnet routers, traffic relay nodes, and MagicDNS. It might work, but it is not supported.
A frequent use case is to allow traffic only from one node to another, but not the other way around. For example, the workstation of an administrator should be able to connect to all nodes but the nodes themselves shouldn't be able to connect back to the administrator's node. Why do all nodes see the administrator's workstation in the output of tailscale status
?
This is essentially how Tailscale works. If traffic is allowed to flow in one direction, then both nodes see each other in their output of tailscale status
. Traffic is still filtered according to the ACL, with the exception of tailscale ping
which is always allowed in either direction.
Headscale aims to implement a self-hosted, open source alternative to the Tailscale control server. Headscale's goal is to provide self-hosters and hobbyists with an open-source server they can use for their projects and labs. It implements a narrow scope, a single Tailscale network (tailnet), suitable for a personal use, or a small open-source organisation.
Headscale is "Open Source, acknowledged contribution", this means that any contribution will have to be discussed with the Maintainers before being submitted.
Please see Contributing for more information.
Both maintainers have full-time jobs and families, and we want to avoid burnout. We also want to avoid frustration from contributors when their PRs are not accepted.
We are more than happy to exchange emails, or to have dedicated calls before a PR is submitted.
We don't know. We might be working on it. If you're interested in contributing, please post a feature request about it.
Please be aware that there are a number of reasons why we might not accept specific contributions:
We currently support deploying headscale using our binaries and the DEB packages. Visit our installation guide using official releases for more information.
In addition to that, you may use packages provided by the community or from distributions. Learn more in the installation guide using community packages.
For convenience, we also build container images with headscale. But please be aware that we don't officially support deploying headscale using Docker. On our Discord server we have a "docker-issues" channel where you can ask for Docker-specific help to the community.
It depends. As often stated, Headscale is not enterprise software and our focus is homelabbers and self-hosters. Of course, we do not prevent people from using it in a commercial/professional setting and often get questions about scaling.
Please note that when Headscale is developed, performance is not part of the consideration as the main audience is considered to be users with a moddest amount of devices. We focus on correctness and feature parity with Tailscale SaaS over time.
To understand if you might be able to use Headscale for your usecase, I will describe two scenarios in an effort to explain what is the central bottleneck of Headscale:
An environment with 1000 servers
An environment with 80 laptops/phones (end user devices)
Headscale calculates a map of all nodes that need to talk to each other, creating this "world map" requires a lot of CPU time. When an event that requires changes to this map happens, the whole "world" is recalculated, and a new "world map" is created for every node in the network.
This means that under certain conditions, Headscale can likely handle 100s of devices (maybe more), if there is little to no change happening in the network. For example, in Scenario 1, the process of computing the world map is extremly demanding due to the size of the network, but when the map has been created and the nodes are not changing, the Headscale instance will likely return to a very low resource usage until the next time there is an event requiring the new map.
In the case of Scenario 2, the process of computing the world map is less demanding due to the smaller size of the network, however, the type of nodes will likely change frequently, which would lead to a constant resource usage.
Headscale will start to struggle when the two scenarios overlap, e.g. many nodes with frequent changes will cause the resource usage to remain constantly high. In the worst case scenario, the queue of nodes waiting for their map will grow to a point where Headscale never will be able to catch up, and nodes will never learn about the current state of the world.
We expect that the performance will improve over time as we improve the code base, but it is not a focus. In general, we will never make the tradeoff to make things faster on the cost of less maintainable or readable code. We are a small team and have to optimise for maintainabillity.
We recommend the use of SQLite as database for headscale:
The headscale project itself does not provide a tool to migrate from PostgreSQL to SQLite. Please have a look at the related tools documentation for migration tooling provided by the community.
The choice of database has little to no impact on the performance of the server, see Scaling / How many clients does Headscale support? for understanding how Headscale spends its resources.
We don't know. We don't use reverse proxies with headscale ourselves, so we don't have any experience with them. We have community documentation on how to configure various reverse proxies, and a dedicated "reverse-proxy-issues" channel on our Discord server where you can ask for help to the community.
Running headscale on a machine that is also in the tailnet can cause problems with subnet routers, traffic relay nodes, and MagicDNS. It might work, but it is not supported.
A frequent use case is to allow traffic only from one node to another, but not the other way around. For example, the workstation of an administrator should be able to connect to all nodes but the nodes themselves shouldn't be able to connect back to the administrator's node. Why do all nodes see the administrator's workstation in the output of tailscale status
?
This is essentially how Tailscale works. If traffic is allowed to flow in one direction, then both nodes see each other in their output of tailscale status
. Traffic is still filtered according to the ACL, with the exception of tailscale ping
which is always allowed in either direction.
Headscale aims to implement a self-hosted, open source alternative to the Tailscale control server. Headscale's goal is to provide self-hosters and hobbyists with an open-source server they can use for their projects and labs. This page provides on overview of Headscale's feature and compatibility with the Tailscale control server:
autogroup:internet
, autogroup:nonroot
Headscale aims to implement a self-hosted, open source alternative to the Tailscale control server. Headscale's goal is to provide self-hosters and hobbyists with an open-source server they can use for their projects and labs. This page provides on overview of Headscale's feature and compatibility with the Tailscale control server:
autogroup:internet
, autogroup:nonroot
Join our Discord server for announcements and community support.
Please report bugs via GitHub issues
Join our Discord server for announcements and community support.
Please report bugs via GitHub issues
All headscale releases are available on the GitHub release page. Those releases are available as binaries for various platforms and architectures, packages for Debian based systems and source code archives. Container images are available on Docker Hub and GitHub Container Registry.
An Atom/RSS feed of headscale releases is available here.
See the "announcements" channel on our Discord server for news about headscale.
All headscale releases are available on the GitHub release page. Those releases are available as binaries for various platforms and architectures, packages for Debian based systems and source code archives. Container images are available on Docker Hub and GitHub Container Registry.
An Atom/RSS feed of headscale releases is available here.
See the "announcements" channel on our Discord server for news about headscale.
If you like to support the development of headscale, please consider a donation via ko-fi.com/headscale. Thank you!
If you like to support the development of headscale, please consider a donation via ko-fi.com/headscale. Thank you!