Denis Wilson Souza Rosa & Steffen Schneider

Databases on Kubernetes: Why you should care

A database pod fails. Instead of panic, the cluster automatically provisions a new node and rebalances data to restore a healthy state—all without human intervention.

Databases on Kubernetes: Why you should care
#1about 3 minutes

The evolution of running databases in containers

The community's perspective shifted from advising against running databases in containers to embracing it due to improvements in Docker and the rise of Kubernetes.

#2about 1 minute

Challenges of a naive database deployment on Kubernetes

A simple deployment of a database like MySQL on Kubernetes creates configuration management problems and requires maintaining multiple container images.

#3about 5 minutes

Using custom resource definitions to manage configuration

Custom Resource Definitions (CRDs) extend the Kubernetes API, allowing you to store application-specific configuration directly within the cluster.

#4about 4 minutes

Understanding stateful application failures in Kubernetes

Standard Kubernetes deployments fail to manage stateful applications like databases because they don't handle node failures, pod affinity, or state recovery automatically.

#5about 5 minutes

The Kubernetes operator pattern for database automation

The operator pattern uses custom controllers to listen for events and encode operational knowledge, automating complex tasks like database recovery and upgrades.

#6about 10 minutes

Live demo of the Couchbase operator in action

The Couchbase operator demonstrates self-healing by automatically replacing a deleted pod, rejoining it to the cluster, and rebalancing data without manual intervention.

#7about 7 minutes

Scaling and upgrading a database with an operator

Operators simplify complex operations like scaling out nodes, performing rolling upgrades, and tuning resource allocation by just modifying a declarative configuration file.

#8about 3 minutes

Comparing managed DBaaS with databases on Kubernetes

While managed DBaaS is simpler for small workloads, running databases on Kubernetes with operators provides greater flexibility, control, and cost-effectiveness at scale.

#9about 4 minutes

Storage and performance considerations on Kubernetes

Using local persistent storage is recommended for performance, and benchmarks show only a minimal 3-4% overhead when running databases in containers versus bare metal.

#10about 1 minute

Key takeaways for running databases on Kubernetes

When running databases on Kubernetes, choose a mature operator, prefer local persistent storage, and account for a small performance overhead compared to bare metal.

Related jobs
Jobs that call for the skills explored in this talk.

Featured Partners

Related Videos

See all videos
Databases on Kubernetes48:45

Databases on Kubernetes

Denis Souza Rosa

Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)43:28

Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)

Gregor Bauer

Mastering Kubernetes – Beginner Edition57:24

Mastering Kubernetes – Beginner Edition

Hannes Norbert Göring

Kubernetes and Microservices with Multi-Model Databases29:30

Kubernetes and Microservices with Multi-Model Databases

Wei Hu

Kubernetes Maestro: Dive Deep into Custom Resources to Unleash Next-Level Orchestration Power!29:21

Kubernetes Maestro: Dive Deep into Custom Resources to Unleash Next-Level Orchestration Power!

Um e Habiba

Database Magic behind 40 Million operations/s24:22

Database Magic behind 40 Million operations/s

Jürgen Pilz

Adjusting Pod Eviction Timings in Kubernetes29:06

Adjusting Pod Eviction Timings in Kubernetes

Andrew Pruski

Developing locally with Kubernetes - a Guide and Best Practices39:20

Developing locally with Kubernetes - a Guide and Best Practices

Dan Erez

From learning to earning

Jobs that call for the skills explored in this talk.

Kubernetes Specialist

CompuSafe Data Systems AG
München, Germany

Linux
VMware
Routing
Kubernetes
Load Balancing