Book Image

DevOps for Databases

By : David Jambor
Book Image

DevOps for Databases

By: David Jambor

Overview of this book

In today's rapidly evolving world of DevOps, traditional silos are a thing of the past. Database administrators are no longer the only experts; site reliability engineers (SREs) and DevOps engineers are database experts as well. This blurring of the lines has led to increased responsibilities, making members of high-performing DevOps teams responsible for end-to-end ownership. This book helps you master DevOps for databases, making it a must-have resource for achieving success in the ever-changing world of DevOps. You’ll begin by exploring real-world examples of DevOps implementation and its significance in modern data-persistent technologies, before progressing into the various types of database technologies and recognizing their strengths, weaknesses, and commonalities. As you advance, the chapters will teach you about design, implementation, testing, and operations using practical examples, as well as common design patterns, combining them with tooling, technology, and strategies for different types of data-persistent technologies. You’ll also learn how to create complex end-to-end implementation, deployment, and cloud infrastructure strategies defined as code. By the end of this book, you’ll be equipped with the knowledge and tools to design, build, and operate complex systems efficiently.
Table of Contents (24 chapters)
1
Part 1: Database DevOps
5
Part 2: Persisting Data in the Cloud
7
Chapter 5: RDBMS with DevOps
10
Part 3: The Right Tool for the Job
14
Part 4: Build and Operate
19
Part 5: The Future of Data

Case studies – self-healing databases in Kubernetes

Self-healing databases in Kubernetes bring together the resilience and scalability of Kubernetes with the reliability and data management capabilities of databases. By combining these technologies, organizations can achieve highly available and fault-tolerant database deployments. In this technical summary, we will explore case studies that showcase the implementation of self-healing databases in Kubernetes environments.

Case study 1 – MySQL Operator

The MySQL Operator is an example of a self-healing mechanism for MySQL databases in Kubernetes. It leverages the Kubernetes operator pattern to automate the management of MySQL deployments. The MySQL Operator monitors the health of MySQL pods and automatically performs recovery actions in case of failures.

When a pod fails, the MySQL Operator detects the failure through liveness probes and initiates the recovery process. It automatically creates a new pod to replace...