Kowalski is an API-driven multi-survey data archive and alert broker. Its main focus is the Zwicky Transient Facility.
A schematic overview of the functional aspects of Kowalski
and how they interact is shown below:
- A non-relational (NoSQL) database
MongoDB
powers the data archive, the alert stream sink, and the alert handling service. - An API layer provides an interface for the interaction with the backend:
it is built using a
python
asynchronous web framework,aiohttp
, and the standardpython
async event loop serves as a simple, fast, and robust job queue. Multiple instances of the API service are maintained using theGunicorn
WSGI HTTP Server. - A programmatic
python
client is also available to interact with Kowalski's API. - Incoming and outgoing traffic can be routed through
traefik
, which acts as a simple and performant reverse proxy/load balancer. - An alert brokering layer listens to
Kafka
alert streams and uses adask.distributed
cluster for distributed alert packet processing, which includes data preprocessing, execution of machine learning models, catalog cross-matching, and ingestion intoMongoDB
. It also executes user-defined filters based on the augmented alert data and posts the filtering results to aSkyPortal
instance. - Kowalski is containerized using
Docker
software and orchestrated withdocker-compose
allowing for simple and efficient deployment in the cloud and/or on-premise.
Kowalski
is an API-first system. The full OpenAPI specs can be found here. Most users will only need the queries section of the specs.
The easiest way to interact with a Kowalski
instance is by using a python client penquins
.
Clone the repo and cd to the cloned directory:
git clone https://github.com/dmitryduev/kowalski.git
cd kowalski
Use the kowalski.py
utility to manage Kowalski
.
Make sure the requirements to run the kowalski.py
utility are met, e.g.:
pip install -r requirements.txt
Start up Kowalski
using the default config/secrets (copying them over):
./kowalski.py up
You should cp config.defaults.yaml config.yaml
instead of using the default config in a production setting.
Make sure to choose strong passwords!
config.yaml
contains the API and ingester configs, the supevisord
config for the API and ingester containers,
together with all the secrets, so be careful when committing code / pushing docker images.
./kowalski.py up
Kowalski
uses docker-compose
under the hood and requires a docker-compose.yaml
file.
There are several available deployment scenarios:
- Bare-bones
- Bare-bones + broker for
SkyPortal
/Fritz
- Behind
traefik
Use docker-compose.defaults.yaml
as a template for docker-compose.yaml
.
Note that the environment variables for the mongo
service must match
admin_*
under kowalski.database
in config.yaml
.
Use docker-compose.fritz.defaults.yaml
as a template for docker-compose.yaml
.
If you want the alert ingester to post (filtered) alerts to SkyPortal
, make sure
{"misc": {"broker": true}}
in config.yaml
.
Use docker-compose.traefik.defaults.yaml
as a template for docker-compose.yaml
.
If you have a publicly accessible host allowing connections on port 443
and a DNS record with the domain
you want to expose pointing to this host, you can deploy kowalski
behind traefik
,
which will act as the edge router -- it can do many things including load-balancing and
getting a TLS certificate from letsencrypt
.
In docker-compose.yaml
:
- Replace
kowalski@caltech.edu
with your email. - Replace
private.caltech.edu
with your domain.
./kowalski.py test
./kowalski.py down
OpenAPI specs are to be found under /docs/api
once Kowalski
is up and running.
Contributions to Kowalski are made through GitHub Pull Requests, a set of proposed commits (or patches).
To prepare, you should:
-
Create your own fork the kowalski repository by clicking the "fork" button.
-
Clone (download) your copy of the repository, and set up a remote called
upstream
that points to the main Kowalski repository.git clone git@github.com:<yourname>/kowalski git remote add upstream git@github.com:dmitryduev/kowalski
Then, for each feature you wish to contribute, create a pull request:
-
Download the latest version of Kowalski, and create a new branch for your work.
Here, let's say we want to contribute some documentation fixes; we'll call our branch
rewrite-contributor-guide
.git checkout master git pull upstream master git checkout -b rewrite-contributor-guide
-
Make modifications to Kowalski and commit your changes using
git add
andgit commit
. Each commit message should consist of a summary line and a longer description, e.g.:Rewrite the contributor guide While reading through the contributor guide, I noticed several places in which instructions were out of order. I therefore reorganized all sections to follow logically, and fixed several grammar mistakes along the way.
-
When ready, push your branch to GitHub:
git push origin rewrite-contributor-guide
Once the branch is uploaded, GitHub should print a URL for turning your branch into a pull request. Open that URL in your browser, write an informative title and description for your pull request, and submit it. There, you can also request a review from a team member and link your PR with an existing issue.
-
The team will now review your contribution, and suggest changes. To simplify review, please limit pull requests to one logical set of changes. To incorporate changes recommended by the reviewers, commit edits to your branch, and push to the branch again (there is no need to re-create the pull request, it will automatically track modifications to your branch).
-
Sometimes, while you were working on your feature, the
master
branch is updated with new commits, potentially resulting in conflicts with your feature branch. To fix this, please merge in the latestupstream/master
branch:git merge rewrite-contributor-guide upstream/master
Developers may merge master
into their branch as many times as they want to.
- Once the pull request has been reviewed and approved by at least two team members, it will be merged into Kowalski.
Install our pre-commit hook as follows:
pip install pre-commit
pre-commit install
This will check your changes before each commit to ensure that they
conform with our code style standards. We use black
to reformat Python
code and flake8
to verify that code complies with PEP8.