Note
The repository has been supplanted by montagu-deploy and montagu-config.
- Docker Community Edition
- Docker Compose - at least version 0.17.0
- Python 3 and pip (Python 3 is included with Ubunti. For pip, use
apt install python3-pip
) - Vault available on the command line as
vault
, with the address set viaexport VAULT_ADDR=https://support.montagu.dide.ic.ac.uk:8200
- Your machine needs to trust our Docker Registry. See "Configuring docker clients to use the registry"
- Release process
- Upgrading and rebooting servers, disaster recovery: docs
- Troubleshooting - potential issues and their solutions, particularly for getting Montagu running on a local dev environment.
- Install python packages with
pip3 install --user -r src/requirements.txt
- If restoring from backup (or making backups) prepare bb8 with
sudo ./montagu-bb8/bb8/bb8_link_write
./src/deploy.py
./deploy.py v0.1.2
If the version number is omitted the script will prompt you for one (it must match the pattern of vX.Y.Z-RCa
where X
, Y
, Z
and a
are one or more digits.
We also have all our released images on docker hub and the deploy tool can work from there. This requires VPN access only for the vault, so for test deployments can be done off-site more easily.
./deploy.py --docker-hub <version>
The deploy tool will ask you a series of questions interactively, suggesting
defaults along the way. These settings are saved to ./src/montagu-deploy.json
and on the next deploy those questions will not be asked. If new settings are
added to the deploy tool, you will just be asked the new questions on your next
deploy.
If you change your mind, you can directly change the values in the json file, delete the setting in question from the json file (prompting the tool to ask you just that question again next time you deploy) or delete the whole json file and go through the full interactive setup again.
If you use the 'test_data' data set then it comes with a default username ("[email protected]") and password ("password")
When deploying to a testing environment using real data restored from live,
setting the add_test_user
option to true adds the above user with permissions
to all modelling groups and reports.
It will also add a "[email protected]" user who has access only to IC-Garske and Harvard-Sweet modelling groups.
To copy file artefacts from the orderly volume into the static volume where
they can be served by the montagu-static
file server, add a config file to
the ./static
directory in this repository. File artefacts will be copied into place
following the directory structure of the config file, i.e. artefacts listed in a
config file placed in ./static/model-review/2019
will be served from
/www/model-review/2019
. The config file itself must be a csv where each row contains
2 entries, the first being a glob identifying file artefacts within the orderly archive,
the second being the directory to serve matching artefacts from.
So if a file at ./static/model-review/2019/config.csv
contains
row native-diagnostics-burden-report-drafts/20190131-123847-53fe189e/*,IC-Hallett
the result is that all files matching the native-diagnostics-burden-report-drafts/20190131-123847-53fe189e/*
glob
will be served at model-review/2019/IC-Hallett
When deploying to the production server, make sure to first become the
montagu
user by connecting to production as
[email protected]
Database passwords are managed by the vault and laid out as:
/secret/vimc/database/:password_group/users/:username
Currently our two password groups are science
and production
To get a database password for use with postgres
export PGPASSWORD=$(vault read -field=password secret/vimc/database/science/users/readonly)
psql -h support.montagu.dide.ic.ac.uk -U readonly -d montagu
This gets the password for the readonly
user for the science
password group (which is suitable for the database running on support.montagu.dide.ic.ac.uk). To see all users, use:
vault list secret/vimc/science/users
or
vault list secret/vimc/database/production/users
Run
./src/generate_passwords.py add_user <username>
Passwords can be regenerated by running the script
generate_passwords.py regenerate_passwords <group>
which will regenerate passwords for one of the password groups. To create a new password group, use
./src/generate_passwords.py create_password_group [--base=BASE] <name>
which generates a new set of passwords for the same users as the group specified by --base
(defaulting to science).
To update src/versions.py
to the latest master of each sub repo, use
src/update_versions_to_latest_master.py
.
If the deployment setting fake_smtp
is true, a fake SMTP server will be deployed. It provides a web interface at
http://localhost:1080 showing the email requests it has received. It is used by the task queue component to send
notification emails. If fake_smtp
is false the component will be configured to use the Production SMTP server.
Configuration of diagnostic reports to run when burden estimates are completed is defined in
./container_config/real_diagnostic_reports.yml
This involves a lot of repetition as we currently
run the same diagnostic report for each model, so this file can be regenerated by running
./src/generate_real_diagnostic_reports_config.py
- any changes to the required configuration
should be made through this script.
We log to systemd. All logs will have the tag DOCKER_TAG=montagu
which allows for filtering with
journalctl --since=today CONTAINER_TAG=montagu
journalctl --since=today CONTAINER_NAME=montagu_db_1
See ReleaseProcess.md
for details on releasing