Supported OS: Tutor runs on any 64-bit, UNIX-based OS. It was also reported to work on Windows (with WSL 2).
Architecture: support for ARM64 is a work-in-progress. See this issue.
Do not attempt to simply run
apt-get install docker docker-compose on older Ubuntu platforms, such as 16.04 (Xenial), as you will get older versions of these utilities.
Ports 80 and 443 should be open. If other web services run on these ports, check the tutorial on :ref:`how to setup a web proxy <web_proxy>`.
- Minimum configuration: 4 GB RAM, 2 CPU, 8 GB disk space
- Recommended configuration: 8 GB RAM, 4 CPU, 25 GB disk space
On Mac OS, by default, containers are allocated 2 GB of RAM, which is not enough. You should follow these instructions from the official Docker documentation to allocate at least 4-5 GB to the Docker daemon. If the deployment fails because of insufficient memory during database migrations, check the :ref:`relevant section in the troubleshooting guide <migrations_killed>`.
Choose one of the installation methods below. If you install Tutor in different ways, you will end up with multiple
tutor executables, which is going to be very confusing. At any time, you can check the path to your
tutor executable by running
Check the "tutor" package on Pypi: https://pypi.org/project/tutor. You will need Python >= 3.6 with pip and the libyaml development headers. On Ubuntu, these requirements can be installed by running:
sudo apt install python3 python3-pip libyaml-dev
The latest binaries can be downloaded from https://github.com/overhangio/tutor/releases. From the command line:
This is the simplest and recommended installation method for most people who do not have Python 3 on their machine. Note however that you will not be able to use custom plugins with this pre-compiled binary. The only plugins you can use with this approach are those that are already bundled with the binary: see the :ref:`existing plugins <existing_plugins>`.
Installing from source
To inspect the Tutor source code, install Tutor from the Github repository:
git clone https://github.com/overhangio/tutor cd tutor pip install -e .
Configuring DNS records
When running a server in production, it is necessary to define DNS records which will make it possible to access your Open edX platform by name in your browser. The precise procedure to create DNS records vary from one provider to the next and is beyond the scope of these docs. You should create a record of type A with a name equal to your LMS hostname (given by
tutor config printvalue LMS_HOST) and a value that indicates the IP address of your server. Applications other than the LMS, such as the studio, ecommerce, etc. typically reside in subdomains of the LMS. Thus, you should also create a CNAME record to point all subdomains of the LMS to the LMS_HOST.
For instance, the demo Open edX server that runs at https://demo.openedx.overhang.io has the following DNS records:
demo.openedx 1800 IN A 18.104.22.168 *.demo.openedx 1800 IN CNAME demo.openedx.overhang.io.
Zero-click AWS installation
Tutor can be launched on Amazon Web Services very quickly with the official Tutor AMI. Shell access is not required, as all configuration will happen through the Tutor web user interface. For detailed installation instructions, we recommend watching the following video:
.. youtube:: xtXP52qGphA
To upgrade Open edX or benefit from the latest features and bug fixes, you should simply upgrade Tutor. Start by upgrading the "tutor" package and its dependencies:
pip install --upgrade tutor[full]
Then run the
quickstart command again. Depending on your deployment target, run either:
tutor local quickstart # for local installations tutor k8s quickstart # for Kubernetes installation
Upgrading with custom Docker images
If you run :ref:`customised <configuration_customisation>` Docker images, you need to rebuild them prior to running
tutor config save tutor images build all # specify here the images that you need to build tutor local quickstart
Upgrading to a new Open edX release
Major Open edX releases are published twice a year, in June and December, by the Open edX Build/Test/Release working group. When a new Open edX release comes out, Tutor gets a major version bump (see :ref:`versioning`). Such an upgrade typically includes multiple breaking changes. Any upgrade is final, because downgrading is not supported. Thus, when upgrading your platform from one major version to the next, it is strongly recommended to do the following:
Read the changes listed in the CHANGELOG.md file. Breaking changes are identified by a "
Perform a backup. On a local installation, this is typically done with:
tutor local stop sudo rsync -avr "$(tutor config printroot)"/ /tmp/tutor-backup/
If you created custom plugins, make sure that they are compatible with the newer release.
Test the new release in a sandboxed environment.
If you are running edx-platform, or some other repository from a custom branch, then you should rebase (and test) your changes on top of the latest release tag (see :ref:`edx_platform_fork`).
The process for upgrading from one major release to the next works similarly to any other upgrade, with the
quickstart command (see above). The single difference is that if the
quickstart command detects that your tutor environment was generated with an older release, it will perform a few release-specific upgrade steps. These extra upgrade steps will be performed just once. But they will be ignored if you updated your local environment (for instance: with
tutor config save) prior to running
quickstart. This situation typically occurs if you need to re-build some Docker images (see above). In such a case, you should make use of the
upgrade command. For instance, to upgrade a local installation from Lilac to Maple and rebuild some Docker images, run:
tutor config save tutor images build all # list the images that should be rebuilt here tutor local upgrade --from=lilac tutor local quickstart
Tutor is built on top of Click, which is a great library for building command line interface (CLI) tools. As such, Tutor benefits from all Click features, including auto-completion. After installing Tutor, auto-completion can be enabled in bash by running:
_TUTOR_COMPLETE=bash_source tutor >> ~/.bashrc
If you are running zsh, run instead:
_TUTOR_COMPLETE=zsh_source tutor >> ~/.zshrc
After opening a new shell, you can test auto-completion by typing:
It is fairly easy to completely uninstall Tutor and to delete the Open edX platforms that is running locally.
First of all, stop any locally-running platform:
tutor local stop tutor dev stop
Then, delete all data associated to your Open edX platform:
# WARNING: this step is irreversible sudo rm -rf "$(tutor config printroot)"
Finally, uninstall Tutor itself:
# If you installed tutor from source pip uninstall tutor # If you downloaded the tutor binary sudo rm /usr/local/bin/tutor