Short description

“Covid-19 AI demo in all-Docker” deployment including dockerised Flask, FastAPI, Tensorflow Serving and HA Proxy etc etc.

Full documentation

Full documentation is pulished here at Deploy ML/DL models into a consolidated AI demo service stack

Scope

In scope:

As a jump start, we can simply use docker-compose to deploy the following dockerised components into an AWS Ubuntu server

HAProxy - load balancer
Gunicorn vs. Univorn - web gateway server
Flask vs. FastAPI - application server
Tensorflow-Serving vs. Tensorflow-Serving-gpu - application back-end servers for image etc classifications etc
IRIS IntegratedML - consolidated App+DB AutoML with SQL interface
Python3 in Jupyter Notebook to emulate a client for benchmarking
Docker and docker-compose
AWS Ubuntu 16.04 with a Tesla T4 GPU
Note: Tensorflow Serving with GPU is for demo purpose only - you can simply switch off the gpu related image (in a dockerfile) and the config (in the docker-compose.yml).

Out of scope or on next wish list:

Nginx or Apache etc web servers are omitted in demo for now
RabbitMQ and Redis - queue broker for reliable messaging that can be replace by IRIS or Ensemble.
IAM (Intersystems API Manger) or Kong is on wish list
SAM (Intersystems System Alert & Monitoring)
ICM (Intersystems Cloud Manager) with Kubernetes Operator - always one of my favorites since its birth
FHIR (Intesystems IRIS based FHIR R4 server and FHIR Sandbox for SMART on FHIR apps)
CI/CD devop tools or Github Actions

Deployment Pattern

Logical Deployment Pattern

Environment Topology

Physical Deployment Topology

Volumes Mapping & Directory Structure

Please refer to full documentation on section “Dockerised Components”

Service start-up

Default start-up: docker-compose up -d
Scale-up start-up: docker-compose up --scale fastapi=2 --scale flask=2 -d

Test App

Sample application on AWS. Note: this service is on a temp AWS address and not up 24/07.

Functional Testing and API docs:

Please see section “2. Test demo APIs” within full documentation on section “Dockerised Components”

Benchmark testing

Please see section “3. Benchmark-test demo APIs” within full documentation on section “Dockerised Components”

Full documentation is pulished here

Note

Tensorflow exported models are ommited in the models directory, since they are ~250M (larger than 100M by Github). I will upload these large files seperately.

The models are exported from Jupyter pipelines at here and here

covid-ai-demo-deployment