Databases and Docker: A survival guide

Containers are great ephemeral vessels for your applications. But what about the data that drives your business? It must survive containers coming and going, maintain its availability and reliability, and grow when you need it. Alvin Richards does some live coding to show key strategies to help you survive the transition to production.

Containers are great ephemeral vessels for your applications. But what about the data that drives your business? It must survive containers coming and going, maintain its availability and reliability, and grow when you need it. Alvin Richards does some live coding, illustrating the power of Docker Machine, Engine, Swarm, and Compose, demonstrating how to combine them with multihost networking to build a reliable, scalable, and production-ready tier for the data needs of your organization, and outlining key strategies to help you survive the transition to production. Alvin starts with a quick overview of Docker, relational databases, and the key criteria to evaluate strategies as you move your application and database technology from development to production. Using a simple Python and Flask app, Alvin demonstrates how you can simply build, deploy, and test an application and satisfy your key considerations, including how to find and connect to the database from your application code and how to orchestrate a multicontainer application. Alvin then explains how to inject the behaviors and patterns needed for a production deployment, such as adding a load balancer in front of the web nodes and scaling the web nodes without any downtime or having to do manual reconfiguration. Alvin concludes by tackling scaling the database layer, showing how to automatically configure the database cluster on the fly, implement automatic discovery of the cluster, scale the cluster size, and inject affinity and other constraints to reflect the required production topology. The GitHub repo will be provided to allow you to reproduce these demonstrations later.