Troubleshooting

What should you do if you have a problem?

Warning

Do not create a Github issue!

  1. Read the error logs that appear in the console. When running a single server platform as daemon, you can view the logs with the tutor local logs command. (see Logging below)

  2. Check if your problem already has a solution right here in the Troubleshooting section.

  3. Search for your problem in the open and closed Github issues.

  4. Search for your problem in the community forums.

  5. If, despite all your efforts, you can’t solve the problem by yourself, you should discuss it in the community forums. Please give as much details about your problem as possible! As a rule of thumb, people will not dedicate more time to solving your problem than you took to write your question.

  6. If you are absolutely positive that you are facing a technical issue with Tutor, and not with Open edX, not with your server, not your custom configuration, then, and only then, should you open an issue on Github. You must follow the instructions from the issue template!!! If you do not follow this procedure, your Github issues will be mercilessly closed 🤯.

Do you need professional assistance with your tutor-managed Open edX platform? Overhang.IO offers online support as part of its Long Term Support (LTS) offering.

Logging

Note

Logs are of paramount importance for debugging Tutor. When asking for help on the Tutor forums, you should always include the unedited logs of your app. You can get those with:

tutor local logs --tail=100 -f

To view the logs from all containers use the tutor local logs command, which was modeled on the standard docker-compose logs command:

tutor local logs --follow

To view the logs from just one container, for instance the web server:

tutor local logs --follow nginx

The last commands produce the logs since the creation of the containers, which can be a lot. Similar to a tail -f, you can run:

tutor local logs --tail=0 -f

If you’d rather use a graphical user interface for viewing logs, you are encouraged to try out Portainer.

“Cannot start service nginx: driver failed programming external connectivity”

The containerized Nginx needs to listen to ports 80 and 443 on the host. If there is already a webserver, such as Apache or Nginx, running on the host, the nginx container will not be able to start. To solve this issue, check the section on how to setup a web proxy.

“Couldn’t connect to docker daemon”

This is not an error with Tutor, but with your Docker installation. This is frequently caused by a permission issue. Before running Tutor, you should be able to run:

docker run --rm hello-world

If the above command does not work, you should fix your Docker installation. Some people will suggest to run Docker as root, or with sudo; do not do this. Instead, what you should probably do is to add your user to the “docker” group. For more information, check out the official Docker installation instructions.

“Running migrations… Killed!” / “Command failed with status 137: docker-compose”

Open edX requires at least 4 GB RAM, in particular to run the SQL migrations. If the tutor local quickstart command dies after displaying “Running migrations”, you most probably need to buy more memory or add swap to your machine. On Docker for Mac OS, by default, containers are allocated at most 2 GB of RAM. You should follow these instructions from the official Docker documentation to allocate at least 4-5 Gb to the Docker daemon.

If migrations were killed halfway, there is a good chance that the MySQL database is in a state that is hard to recover from. The easiest way to recover is simply to delete all the MySQL data and restart the quickstart process. After you have allocated more memory to the Docker daemon, run:

tutor local stop
sudo rm -rf "$(tutor config printroot)/data/mysql"
tutor local quickstart

Warning

THIS WILL ERASE ALL YOUR DATA! Do not run this on a production instance. This solution is only viable for new Open edX installations.

Help! The Docker containers are eating all my RAM/CPU/CHEESE

You can identify which containers are consuming most resources by running:

docker stats

“Build failed running pavelib.servers.lms: Subprocess return code: 1”

python manage.py lms print_setting STATIC_ROOT 2>/dev/null
...
Build failed running pavelib.servers.lms: Subprocess return code: 1`"

This might occur when you run a paver command. /dev/null eats the actual error, so you will have to run the command manually. Run tutor dev shell lms (or tutor dev shell cms) to open a bash session and then:

python manage.py lms print_setting STATIC_ROOT

The error produced should help you better understand what is happening.

“ValueError: Unable to configure handler ‘local’”

ValueError: Unable to configure handler 'local': [Errno 2] No such file or directory

This will occur if you try to run a development environment without patching the LOGGING configuration, as indicated in the development_ section. Maybe you correctly patched the development settings, but they are not taken into account? For instance, you might have correctly defined the TUTOR_EDX_PLATFORM_SETTINGS environment variable, but paver uses the devstack settings (which does not patch the LOGGING variable). This is because calling paver lms --settings=development or paver cms --settings=development ignores the --settings argument. Yes, it might be considered an edx-platform bug… Instead, you should run the update_assets and runserver commands, as explained above.

The chosen default language does not display properly

By default, Open edX comes with a limited set <https://github.com/edx/edx-platform/blob/master/conf/locale/config.yaml> of translation/localization files. To complement these languages, we add locales from the openedx-i18n project. But not all supported locales are downloaded. In some cases, the chosen default language will not display properly because if was not packaged in either edx-platform or openedx-i18n. If you feel like your language should be packaged, please open an issue on the openedx-i18n project.

When I make changes to a course in the CMS, they are not taken into account by the LMS

This issue should only happen in development mode. Long story short, it can be solved by creating a Waffle switch with the following command:

tutor dev run lms ./manage.py lms waffle_switch block_structure.invalidate_cache_on_publish on --create

If you’d like to learn more, please take a look at this Github issue.