Databases on Kubernetes

Running databases in containers was once a terrible idea. Discover how the Kubernetes Operator pattern has made it a production-ready reality.

#1about 5 minutes

Why running databases in containers is now a reality

Key advancements like Docker performance improvements, production-grade images, and Kubernetes operators have made running stateful applications in containers viable.

#2about 7 minutes

Understanding Kubernetes extensibility with CRDs and controllers

Custom Resource Definitions (CRDs) allow you to define new resource types, and controllers can listen to events related to these resources to automate complex management tasks.

#3about 9 minutes

Deploying a database cluster using a YAML file

A live demo shows how to deploy a multi-node Couchbase cluster by applying a single YAML file, which the operator uses as the single source of truth for configuration.

#4about 8 minutes

Automating database recovery and scaling with an operator

The operator automatically handles node failures by recovering pods and rebalancing data, and scales the cluster up or down based on simple changes to the configuration file.

#5about 6 minutes

Choosing the right storage for databases on Kubernetes

An overview of storage options, including ephemeral, remote persistent, and local persistent storage, with a recommendation to use local storage for databases with built-in replication.

#6about 6 minutes

Simplifying database provisioning with service brokers

Service brokers provide a facade over operators, allowing developers to provision databases by requesting pre-defined plans via a simple API call instead of writing complex YAML.

#7about 4 minutes

Comparing self-managed Kubernetes databases to DBaaS

A comparison of the trade-offs between using a managed Database-as-a-Service (DBaaS) and running your own database on Kubernetes, focusing on flexibility versus ease of use.