Chaos Engineering with Python Python-powered techniques for building resilient systems through chaos engineering

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Free Download Chaos Engineering with Python
by Ubhi, Mandeep;

English | 2025 | ISBN: 9365892074 | 210 pages | True EPUB | 6.98 MB

Chaos Engineering with Python is a comprehensive guide to designing, executing, and automating chaos experiments to build resilient systems. The book blends foundational theory with hands-on practice, ensuring readers gain an understanding of implementing chaos engineering effectively.
It begins by defining resilience and tracing the evolution of chaos engineering from traditional testing methods. A core focus of the book is real-world application, demonstrating structured chaos experiments across various environments. Readers will learn fault injection techniques, how to analyze experiment results, and how to use tools like the Python Chaos Toolkit. The book extensively covers chaos engineering on Kubernetes, a critical skill for modern cloud-native applications, and explores experiments on virtual machines and AWS infrastructure, in addition to providing an overview of the managed chaos services. The book also emphasizes integrating chaos experiments into CI/CD pipelines, enabling automated, continuous resilience testing as part of the development workflow. Beyond tech, it provides guidance on embedding, measuring, and sustaining the cultural shift needed to embrace chaos engineering.
This book is a valuable resource for anyone looking to understand and implement chaos engineering, from beginners to experienced practitioners, providing both the technical know-how and the cultural understanding necessary for building truly resilient systems.
Key Features
● Progressive learning, starting with chaos principles, fault tolerance patterns to practical use cases, and finally to integration with CI/CD.
● Real-world use cases, including Kubernetes and cloud infrastructure, built with a structured and repeatable approach.
● Proven methods to embed chaos engineering culture in the enterprise and highlight its business value to stakeholders.
What you will learn
● Understand chaos engineering principles, resilience, and proactive failure testing.
● Implement chaos experiments using Python, Kubernetes, and cloud environments.
● Integrate chaos testing into CI/CD for continuous resilience validation.
● Apply fault injection techniques across VMs, infrastructure, and cloud systems.
● Leverage Python Chaos Toolkit for automated and structured chaos experiments.
● Foster a chaos engineering culture within DevOps and SRE teams.
Who this book is for
This book is for software engineers, DevOps engineers, SREs, and IT professionals looking to implement chaos engineering. Readers should have basic programming knowledge and familiarity with cloud computing concepts, though a Python refresher is provided.
Table of Contents
1. Resilience and Evolution of Chaos Engineering
2. Rapid Refresher on Python Essentials
3. Implementation Journey of Chaos Experiments
4. Up and Running with Python Chaos Toolkit
5. Chaos Experiments on Virtual Machines
6. Chaos Experiments with Kubernetes
7. Chaos Experiments with Infrastructure
8. Integrating Chaos Experiments into CI/CD Pipelines
9. Embedding Chaos Engineering Culture




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Chaos Engineering
Published 10/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.53 GB | Duration: 2h 42m​

Equip yourself with the knowledge and skills to ensure your AWS systems withstand and recover from failures.

What you'll learn

Chaos Engineering Fundamentals

Building a Basic Fault Injection Simulation (FIS) Experiment

Introduction to Real-Life Application

Chaos Engineering on Compute - EC2

Chaos Engineering on Database - Aurora

Chaos Engineering on Serverless - Fargate

Chaos Engineering on Kubernetes - EKS

Chaos Engineering on Availability Zone

Requirements

No prior experience or knowledge required - this course is beginner-friendly and covers everything you need to know!

Description

In today's fast-paced digital landscape, system resilience is vital for businesses of all sizes. "Chaos Engineering" is a comprehensive and hands-on course designed to equip you with the knowledge and skills needed to ensure your systems withstand and recover from failures. From foundational concepts to advanced applications on various AWS services, including EC2, Aurora, Fargate, and EKS, as well as strategies to ensure availability across multiple Availability Zones.What You'll Learn:Chaos Engineering Fundamentals:Understand core principles and the philosophy behind Chaos Engineering.Learn why identifying and addressing system weaknesses through controlled chaos experiments is vital.Explore essential tools and methodologies for implementing Chaos Engineering.Building a Basic Fault Injection Simulation (FIS) Experiment:Gain a step-by-step understanding of constructing and executing your first Fault Injection Simulation (FIS) experiment.Understand how to design experiments targeting different failure modes in a controlled setting.Learn to interpret experiment results and refine your simulations for better accuracy.Introduction to Real-Life Application:Discover how to apply Chaos Engineering experiments to real-world applications.Learn best practices for monitoring, capturing metrics, and analyzing results to continually improve system resilience.Chaos Engineering on Compute - EC2:Conduct chaos experiments on EC2 instances to evaluate and improve system robustness.Simulate failures, such as instance termination or network latency, and observe impacts.Chaos Engineering on Database - Aurora:Learn to apply Chaos Engineering principles to Amazon Aurora databases.Simulate failures like cluster instability or node outages and develop strategies for seamless recovery.Chaos Engineering on Serverless - Fargate:Conduct chaos experiments on AWS Fargate to test the resilience of your serverless applications.Simulate events like task failures or service downtime to ensure robust serverless architectures.Chaos Engineering on Kubernetes - EKS:Implement Chaos Engineering on Amazon EKS to stress-test Kubernetes clusters.Simulate pod failures, node crashes, and other disruptions to validate recovery mechanisms.Chaos Engineering on Availability Zone:Conduct chaos experiments across different AWS Availability Zones.Test the impact of zone failures and ensure your systems are prepared for multi-availability zone disasters.This course, with its combination of theory, demonstrations, and real-world scenarios, will enable you to build resilient systems capable of withstanding and recovering from unexpected failures efficiently. Join us to master Chaos Engineering and innovate with confidence.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Important Course Resources

Section 2: Chaos Engineering Fundamentals

Lecture 3 Why Chaos Engineering?

Lecture 4 What is Chaos Engineering ?

Lecture 5 What is AWS FIS?

Lecture 6 FIS Experiments in this Course

Lecture 7 Accessing the Quizzes

Lecture 8 Quiz - Chaos Engineering Fundamentals

Section 3: Building a basic FIS experiment

Lecture 9 FIS Permissions

Lecture 10 Demo - Create FIS Permissions

Lecture 11 Experiment 1-Chaos Engineering on ASG

Lecture 12 Built ASG based Architecture

Lecture 13 Demo: ASG based Architecture

Lecture 14 Create FIS Experiment

Lecture 15 Demo - Run FIS Experiment

Lecture 16 Demo - Demo - Learning and Improvements

Lecture 17 Demo - FIS experiment -CloudWatch Dashboard

Lecture 18 Demo - Create FIS Experiment using CF

Lecture 19 Quiz- Building_Basis_FIS_experiment

Section 4: Introduction to Real life Application

Lecture 20 Introduction to our real life application

Lecture 21 Pre-requisite to Deploy Application & Cloud 9 Deprecation

Lecture 22 Demo: Pre-requisite to Deploy Application

Lecture 23 Demo - Setup Architecture and Deploy Application

Lecture 24 How to Plan Your Experiment? Part 1

Lecture 25 How to Plan Your Experiment? Part 2

Lecture 26 Establishing Steady State Metrics Using Cloudwatch RUM/X Ray

Lecture 27 Demo: Cloud Formation Deployment

Lecture 28 Quiz : Introduction to Real Life Application

Section 5: Chaos Engineering on Compute - EC2

Lecture 29 Disk Fill Scenario on EC2

Lecture 30 Demo: FIS Experiment - Disk Fill Scenario on EC2 and before metrics in X Ray

Lecture 31 Demo: FIS Experiment - After Metrics in X Ray and EC2 instances

Lecture 32 Quiz - Chaos Engineering on Compute

Section 6: Chaos Engineering on Database - Aurora

Lecture 33 Reboot Reader Node Scenario on Aurora

Lecture 34 Demo: Pre-requisite for FIS experiment, Create IAM role, and Current State

Lecture 35 Demo: Create and Run FIS experiment and After Metrics and DB state

Lecture 36 Quiz- Chaos Engineering on Database - Aurora

Section 7: Chaos Engineering on Serverless - Fargate

Lecture 37 ECS Fargate Experiment Idea and Hypothesis

Lecture 38 Demo: Fargate Steady State

Lecture 39 Demo: Fargate IAM role creation

Lecture 40 Demo: Run experiment Task I/O stress

Lecture 41 Demo: Fargate After State and Learning and Improvements

Lecture 42 Quiz- Chaos Engineering on Serverless - Fargate

Section 8: Chaos Engineering on Kubernetes- EKS

Lecture 43 EKS Explanation

Lecture 44 Demo: Memory Stress on EKS - Part 1

Lecture 45 Demo: Memory Stress on EKS - Part 2

Lecture 46 Demo: Memory Stress on EKS- Part 3

Lecture 47 Demo: Memory Stress on EKS- Part 4

Lecture 48 Pod Delete on EKS

Lecture 49 Demo: Steady State Pod Delete on EKS

Lecture 50 Demo: Run Experiment Pod Delete on EKS

Lecture 51 Demo: Recheck After Pod Delete on EKS

Lecture 52 Quiz- Chaos Engineering on Kubernetes- EKS

Section 9: Chaos Engineering on Availability Zone

Lecture 53 What is an Availability Zone(AZ)?

Lecture 54 Experiment Overview

Lecture 55 Demo: General Experiment Setup- AZ

Lecture 56 Demo: Prepare Experiment- AZ

Lecture 57 Running the Experiment

Lecture 58 Quiz- Chaos Engineering on Availability Zone

Section 10: Conclusion

Lecture 59 Cleanup Process

Lecture 60 Conclusion

Developers interested in enhancing their systems' resilience.,Site Reliability Engineers (SREs) focused on improving system reliability.,Cloud Engineers managing AWS environments.,Technical Support Engineers specializing in fault-tolerant systems.,Technical Leads overseeing cloud-native application projects.

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