What should you do if you have a problem?
Do not create a Github issue!
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 logscommand. (see Logging below)
Check if your problem already has a solution right here in the Troubleshooting section.
Search for your problem in the open and closed Github issues.
Search for your problem in the community forums.
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.
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.
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
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:
“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
/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
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.