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

What's new in this version

Updated REDME.md and linked to the published article.

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


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


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

Made with
1.0.107 Sep, 2020
Technology Example
Works with
InterSystems IRIS
First published
03 Sep, 2020