Book Image

Practical Site Reliability Engineering

By : Pethuru Raj Chelliah, Shreyash Naithani, Shailender Singh
Book Image

Practical Site Reliability Engineering

By: Pethuru Raj Chelliah, Shreyash Naithani, Shailender Singh

Overview of this book

Site reliability engineering (SRE) is being touted as the most competent paradigm in establishing and ensuring next-generation high-quality software solutions. This book starts by introducing you to the SRE paradigm and covers the need for highly reliable IT platforms and infrastructures. As you make your way through the next set of chapters, you will learn to develop microservices using Spring Boot and make use of RESTful frameworks. You will also learn about GitHub for deployment, containerization, and Docker containers. Practical Site Reliability Engineering teaches you to set up and sustain containerized cloud environments, and also covers architectural and design patterns and reliability implementation techniques such as reactive programming, and languages such as Ballerina and Rust. In the concluding chapters, you will get well-versed with service mesh solutions such as Istio and Linkerd, and understand service resilience test practices, API gateways, and edge/fog computing. By the end of this book, you will have gained experience on working with SRE concepts and be able to deliver highly reliable apps and services.
Table of Contents (19 chapters)
Title Page
Dedication
About Packt
Contributors
Preface
10
Containers, Kubernetes, and Istio Monitoring
Index

The importance of root-cause analysis 


The cost of service downtime is growing up. There are reliable reports stating that the cost of downtime ranges from $100,000-$72,000 per minute. Identifying the root-cause (mean-time-to-identification (MTTI) generally takes hours. For a complex situation, the process may run into days. The MTTI is lengthy due to various reasons. There are not many tools to speed up the MTTI process. We need competent tools that enrich the value by correlating the data from different IT tools, such as APM, ITSM, SIEM, and ITOM with open API connectors. As microservices and their instances run on containers, IT teams need to manage millions of data points. This transition mandates for highly advanced and automated tools. The pioneering AI algorithms will be commonly used to automate for precisely finding the root-causes.

Root-cause analysis is being touted as an important post-deployment activity for exactly pinpointing bugs and their roots in any software applications...