Summary. I use Docker to create, manage, and deliver applications across various hardware platforms and environments. I demonstrate how Docker simplifies the deployment of everything from database instances to complex machine learning and AI systems.

What the posts say

Docker provides an easy way to create, manage, and deliver applications.

“Docker Hub is a cloud based repository that allows users to share container images.” — Docker

The entire stack runs locally using Docker Compose and a FastAPI backend.

“Every beat above ran against the full stack live on a Docker Compose setup on the M4 MacBook Air from Part 2 — Postgres/pgvector, the FastAPI backend, and the React frontend, all local, no cloud dependency for any of it:” — Agentic AI for Professionals (Part 3)

I demonstrate how to set up and interact with a Microsoft SQL Server instance using Docker.

“I downloaded and ran the amd64 Docker image from https://hub.docker.com/_/microsoft-mssql-server” — Microsoft SQL Server (Part 1)

I demonstrate how to run a Prompt Flow application inside a Docker container.

“I used Prompt flow for Visual Studio Code to create and run a flow in a Docker container” — Prompt Flow (Part 2)

I used a specific command to build and push a multi-architecture image to Docker Hub.

“I used docker to build an image and to upload the image to dockerhubdocker buildx build --platform linux/amd64,linux/arm64 --rm -t haddley/flow:latest --push .” — Prompt Flow (Part 2)

The haddley/blog image supports multiple Operating System/Architectures.

“Since the haddley/blog image has been published using multiple Operating System/Architectures an image can be pulled from Docker Hub and run on a Raspberry Pi computer.” — Docker