TL;DR After a chat with some team members we've decided to double the concurrency of the delivery-worker-reporting app to 4 from 2. Looking at the memory usage during the reporting task runs we don't believe this to be a risk. There are some other things to look at, but this could be a quick win in the short term. Longer read: Every night we have 2 "reporting" tasks that run. - create-nightly-billing starts at 00:15 - populates data for ft_billing for the previous days. - 4 days for email - 4 days for sms - 10 days for letters - create-nightly-notification-status starts at 00:30 - populates data for ft_notification - 4 days for email - 4 days for sms - 10 days for letters These tasks are picked up by the `notify-delivery-worker-reporting` app, we run 3 instances with a concurrency = 2. This means that we have 6 worker threads that pick up the 18 tasks created at 00:15 and 00:30. Each celery main thread picks up 10 tasks of the queue, the 2 worker threads start working on a task and acknowledge the task to SQS. Meanwhile the other 8 tasks wait in the internal celery queue and are no acknowledgement is sent to SQS. As each task is complete a worker picks up a new thread, acknowledges the task. If a task is kept in the Celery internal queue for longer than 5 minutes the visibility timeout in SQS will assume the task has not completed and put the task back on the availability queue, therefore creating a duplicate task. At some point all the tasks are completed, some are completed twice.
GOV.UK Notify API
Contains:
- the public-facing REST API for GOV.UK Notify, which teams can integrate with using our clients
- an internal-only REST API built using Flask to manage services, users, templates, etc (this is what the admin app talks to)
- asynchronous workers built using Celery to put things on queues and read them off to be processed, sent to providers, updated, etc
Setting Up
Python version
We run python 3.9 both locally and in production.
pycurl
See https://github.com/alphagov/notifications-manuals/wiki/Getting-started#pycurl
AWS credentials
To run the API you will need appropriate AWS credentials. See the Wiki for more details.
environment.sh
Creating and edit an environment.sh file.
echo "
export NOTIFY_ENVIRONMENT='development'
export MMG_API_KEY='MMG_API_KEY'
export FIRETEXT_API_KEY='FIRETEXT_ACTUAL_KEY'
export NOTIFICATION_QUEUE_PREFIX='YOUR_OWN_PREFIX'
export FLASK_APP=application.py
export FLASK_ENV=development
export WERKZEUG_DEBUG_PIN=off
"> environment.sh
Things to change:
- Replace
YOUR_OWN_PREFIXwithlocal_dev_<first name>. - Run the following in the credentials repo to get the API keys.
notify-pass credentials/providers/api_keys
Postgres
Install Postgres.app.
Currently the API works with PostgreSQL 11. After installation, open the Postgres app, open the sidebar, and update or replace the default server with a compatible version.
Note: you may need to add the following directory to your PATH in order to bootstrap the app.
export PATH=${PATH}:/Applications/Postgres.app/Contents/Versions/11/bin/
Redis
To switch redis on you'll need to install it locally. On a OSX we've used brew for this. To use redis caching you need to switch it on by changing the config for development:
REDIS_ENABLED = True
To run the application
# install dependencies, etc.
make bootstrap
# run the web app
make run-flask
# run the background tasks
make run-celery
# run scheduled tasks (optional)
make run-celery-beat
To test the application
# install dependencies, etc.
make bootstrap
make test
To update application dependencies
To update application dependencies
requirements.txt is generated from the requirements.in in order to pin versions of all nested dependencies. If requirements.in has been changed, run make freeze-requirements to regenerate it.
To run one off tasks
Tasks are run through the flask command - run flask --help for more information. There are two sections we need to
care about: flask db contains alembic migration commands, and flask command contains all of our custom commands. For
example, to purge all dynamically generated functional test data, do the following:
Locally
flask command purge_functional_test_data -u <functional tests user name prefix>
On the server
cf run-task notify-api "flask command purge_functional_test_data -u <functional tests user name prefix>"
All commands and command options have a --help command if you need more information.