Deploying a Distributed AI Stack to Kubernetes on CentOS

Install and manage a Kubernetes cluster (version 1.13.4) with helm on a single CentOS 7 vm or in multi-host mode that runs the cluster on 3 CentOS 7 vms. Once running, you can deploy a distributed, scalable python stack capable of delivering a resilient REST service with JWT for authentication and Swagger for development. This service uses a decoupled REST API with two distinct worker backends for routing simple database read and write tasks vs long-running tasks that can use a Redis cache and do not need a persistent database connection. This is handy for not only simple CRUD applications and use cases, but also serving a secure multi-tenant environment where multiple users manage long-running tasks like training deep neural networks that are capable of making near-realtime predictions.

This guide was built for deploying the AntiNex stack of docker containers and the Stock Analysis Engine on a Kubernetes single host or multi-host cluster.

AntiNex Stack Status

Here are the AntiNex repositories, documentation and build reports:

Component Build Docs Link Docs Build
REST API Travis Tests Docs Read the Docs REST API Tests
Core Worker Travis AntiNex Core Tests Docs Read the Docs AntiNex Core Tests
Network Pipeline Travis AntiNex Network Pipeline Tests Docs Read the Docs AntiNex Network Pipeline Tests
AI Utils Travis AntiNex AI Utils Tests Docs Read the Docs AntiNex AI Utils Tests
Client Travis AntiNex Client Tests Docs Read the Docs AntiNex Client Tests