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The Linux DevOps Handbook

The Linux DevOps Handbook

By : Damian Wojsław, Grzegorz Adamowicz
4.7 (7)
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The Linux DevOps Handbook

The Linux DevOps Handbook

4.7 (7)
By: Damian Wojsław, Grzegorz Adamowicz

Overview of this book

The Linux DevOps Handbook is a comprehensive resource that caters to both novice and experienced professionals, ensuring a strong foundation in Linux. This book will help you understand how Linux serves as a cornerstone of DevOps, offering the flexibility, stability, and scalability essential for modern software development and operations. You’ll begin by covering Linux distributions, intermediate Linux concepts, and shell scripting to get to grips with automating tasks and streamlining workflows. You’ll then progress to mastering essential day-to-day tools for DevOps tasks. As you learn networking in Linux, you’ll be equipped with connection establishment and troubleshooting skills. You’ll also learn how to use Git for collaboration and efficient code management. The book guides you through Docker concepts for optimizing your DevOps workflows and moves on to advanced DevOps practices, such as monitoring, tracing, and distributed logging. You’ll work with Terraform and GitHub to implement continuous integration (CI)/continuous deployment (CD) pipelines and employ Atlantis for automated software delivery. Additionally, you’ll identify common DevOps pitfalls and strategies to avoid them. By the end of this book, you’ll have built a solid foundation in Linux fundamentals, practical tools, and advanced practices, all contributing to your enhanced Linux skills and successful DevOps implementation.
Table of Contents (20 chapters)
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1
Part 1: Linux Basics
6
Part 2: Your Day-to-Day DevOps Tools
12
Part 3: DevOps Cloud Toolkit

Differences between monitoring, tracing, and logging

You will hear these terms being used interchangeably depending on the context and person you’re talking to, but there’s a subtle and very important difference between them.

Monitoring refers to instrumenting your servers and applications and gathering data about them for processing, identifying problems, and, in the end, bringing results in front of interested parties. This also includes alerting.

Tracing, on the other hand, is more specific, as we already mentioned. Trace data can tell you a lot about how your system is performing. With tracing, you can observe statistics that are very useful to developers (such as how long a function ran and whether the SQL query is fast or bottleneck), DevOps engineers (how long we were waiting for a database or network), or even the business (what was the experience of the user with our application?). So, you can see that when it’s used right, it can be a very powerful...

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