Database DevOps with Containers

Stop letting database environments slow your team down. Learn to build an automated pipeline that delivers safe, production-like data inside a container.

#1about 4 minutes

Defining the core principles of a DevOps pipeline

A standard application DevOps pipeline focuses on reliability, consistency, and cost, with source control serving as the single source of truth.

#2about 4 minutes

Understanding the unique challenges of database DevOps

Unlike applications, the production database is the master copy, requiring a pipeline to safely bring production data into non-production environments.

#3about 3 minutes

Preparing production data for development environments

Safely use production data by anonymizing private information, sanitizing secrets, and shrinking its size while preserving its unique characteristics.

#4about 5 minutes

How containers differ from virtual machines

Containers virtualize the operating system for greater efficiency, while virtual machines virtualize the underlying hardware.

#5about 7 minutes

Exploring the Docker ecosystem and image layers

The Docker ecosystem uses a Dockerfile to build a layered, immutable image which is then run as a lightweight, isolated container.

#6about 4 minutes

Using SQL Server containers for dev and test

While production databases may run on VMs or as a service, containers provide an ideal, ephemeral environment for development and testing.

#7about 5 minutes

Building a dev-safe database image with a Dockerfile

A multi-stage Docker build can restore a production backup, run a transformation script, and package only the sanitized data into a clean final image.

#8about 3 minutes

Running and verifying the sanitized database container

After building the image, run the container and connect to it to verify that all data has been correctly anonymized, sanitized, and is ready for development.

#9about 2 minutes