Racetrack is a framework for deploying, managing, and serving application workloads.
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Racetrack uses the notion of conventions to allow domain experts to produce operationally sound and effective workloads without understanding the underlying infrastructure.
It makes extensive use of plugins. Thus, the type of code which it can accept is broad and covers languages such as Python 3 or Go, and actual applications such as Sphinx, Drupal or even Quake 3.
These "jobs", in Racetrack lingo, can be deployed to different "infrastructure targets". We currently support Kubernetes and Docker. This is also pluggable and can be extended.
Code deployed via Racetrack gets free Swagger pages and Prometheus metrics endpoints.
What distinguishes Racetrack is:
- You only supply your function's logic. No need to write repetitive API code, setting up webservers, creating dockerfiles, kubernetes YAMLs, and so on. Racetrack takes care of that for you.
- Language agnostic. Deploy code written in Python 3, Go, Rust, or anything else encapsulated in a Dockerfile.
- Infrastructure independent. Deploy to either a Kubernetes cluster or a Docker environment in a single transparent step.
Given a Python file like this:
class Meow:
def perform(self, a, b):
"""Add numbers"""
return a + bAnd a YAML file like this:
name: adder
owner_email: meowmeow@example.com
lang: python3:latest
git:
remote: https://www.github.com/path/to-repo.git
python:
entrypoint_path: 'adder.py'
entrypoint_class: 'Meow'You can
racetrack deployAnd the result is a micro-service with an API:
which can be monitored on a dashboard:
or called with a curl command:
Depending on your role, you may be insterested in different documents:
-
Racetrack User:
-
Racetrack Admin:
-
Racetrack Developer:
See the Documentation Pages for more details.
This software is copyright Erhvervsstyrelsen. It is published under the Apache 2.0 License. See Copyright Notices.
This project is a collaboration between The Danish Business Authority and deepsense.ai.