Previously, configuration management was very confusing because we kept mixing
"base" and "defaults" configuration:
- It was difficult to make the difference between core settings that were
necessary (e.g: passwords) as opposed to others that could simply be
defaulted to.
- The order of settings in config.yml mattered: config entries that depended on
other needed to be defined later. As a consequence, Tutor was not compatible
with Python 3.5, where dict entries are not sorted.
Python 3.5 has reached end of life in September 3.5. Anyway, Tutor was not
compatible because some dev dependencies, such as astroid 2.8.3, are no longer
available in 3.5.
This means that we can now start using many python 3.6 niceties, such as
f-strings \o/
Added OPENEDX_EXTRA_PIP_REQUIREMENTS setting, which allows to specify
extra pip packages that should be installed.
Moved "openedx-scorm-xblock" package from Dockerfile to the new setting
in the config.yml.
Through the commonLabels directive in kustomization.yml, all resources
get a label named "app.kubernetes.io/version", which is being set to
the Tutor version at the time of initial deployment.
When the user then subsequently progresses to a new Tutor version,
Kubernetes attempts to update this label — but for Deployment,
ReplicaSet, and DaemonSet resources, this is no longer allowed as of
https://github.com/kubernetes/kubernetes/issues/50808. This causes
"tutor k8s start" (at the "kubectl apply --kustomize" step) to break
with errors such as:
Deployment.apps "redis" is invalid: spec.selector: Invalid value: v1.LabelSelector{MatchLabels:map[string]string{"app.kubernetes.io/instance":"openedx-JIONBLbtByCGUYgHgr4tDWu1", "app.kubernetes.io/managed-by":"tutor", "app.kubernetes.io/name":"redis", "app.kubernetes.io/part-of":"openedx", "app.kubernetes.io/version":"12.1.7"}, MatchExpressions:[]v1.LabelSelectorRequirement(nil)}: field is immutable
Simply removing the app.kubernetes.io/version label from
kustomization.yml will permanently fix this issue for newly created
Kubernetes deployments, which will "survive" any future Tutor version
changes thereafter.
However, *existing* production Open edX deployments will need to throw
the affected Deployments away, and re-create them.
Also, add the Tutor version as a resource annotation instead, using
the commonAnnotations directive.
See also:
https://github.com/kubernetes/client-go/issues/508https://kubectl.docs.kubernetes.io/references/kustomize/kustomization/commonlabels/https://kubectl.docs.kubernetes.io/references/kustomize/kustomization/commonannotations/
Fixes #531.
When running "tutor k8s" we can disable the forum deployment and
service by setting RUN_FORUM to false, but the corresponding job is
added to jobs.yml unconditionally.
Add a conditional to tutor/templates/k8s/jobs.yml so that the forum
job definition is only included when RUN_FORUM is true.
Fixes #525.
When nginx was removed in favour of caddy, we decided that plugin
implementations of the "caddyfile" patch should make use of the "port" local
variable. However, local variables are not available from inside plugin
patches, which are rendered outside of the context of the parent templates.
For a more extensive description of the problem, see:
https://github.com/overhangio/tutor-mfe/pull/23#issuecomment-964016190
We still want to make it easy for developers to decide what should the port be
for caddy hosts. To do so, we make use of environment variables that are passed
at runtime to the caddy container.
Thus, a regular plugin patch should look like this:
{{ PLUGIN_HOST }}{$default_site_port} {
import proxy "myplugin:8000"
}
Forum is an optional feature, and as such it deserves its own plugin. Starting
from Maple, users will be able to install the forum from
https://github.com/overhangio/tutor-forum/
Close #450.
In some cases, plugins declare an entry point but cannot be loaded.
This is the case when they depend on a version of tutor that is not the
one that is currently installed. This use case is very frequent when
working on multiple versions at the same time (i.e: right now, while we
are working on the Maple release). In such cases, it's best just to
ignore the plugin entirely rather than having to re-install all plugins
in the virtualenv.
In the past, tutor was installed with "pip install tutor-openedx". For
some time (since v12.0.2), "tutor" was installed as a dependency of
"tutor-openedx". Now is the time to get rid of that old package.
The standard way of installing tutor is now with "pip install tutor".
- [Improvement] Upgrade all services to open-release/lilac.3.
- [Feature] Make it possible to override job configuration in
development: if they exist, `dev/docker-compose.jobs.yml` and
`dev/docker-compose.jobs.override.yml` will be loaded when running jobs.
- [Improvement] Faster `tutor local start` by building only necessary
images.
Previously, job declarations were always loaded from local/docker-compose.yml
and local/docker-compose.jobs.yml. This meant that it was not possible to
override job declarations in dev mode. It is now the case, with
dev/docker-compose.jobs.yml and dev/docker-compose.jobs.override.yml. Neither
of these files exist yet... But who knows? we might need this feature one day.
In any case the code is much cleaner now.
Before, custom `docker_compose_func` arguments had to be passed to job runners.
This was not very elegant. Also, it prevented us from loading custom job files
in development.
Here, we adopt a better object-oriented approach, where context classes are
ordered hierarchically.
This paves the way for loading `dev/docker-compose.jobs.yml` files in `tutor
dev init` commands -- which will be necessary to fix permissions in dev/local
mode.
Previously, we were building all images every time we ran a "local start"
command. This was causing unnecessary rebuild. Here, instead, we make use of
the `docker-compose up --build`. This means that only the required images will
be rebuilt.
Limits the memory chek to the 'local quickstart' command, makes error
handling more accurate and adds warning messages for some conditions.
Also adds a mention of this in troubleshooting.rst.
Adds a check in the 'local' command group that requires at least
4 GB of RAM to be allocated to Docker when running any of the
local subcommands on macOS. This addresses a common issue where
Docker's default setting (2 GB) causes startup to crash with
misleading error messages.
