> ## Documentation Index > Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt > Use this file to discover all available pages before exploring further. # Course Introduction > This lesson introduces chaos engineering using AWS Fault Injection Simulator to design and analyze fault-injection experiments for system resilience. Welcome to this lesson on chaos engineering with AWS Fault Injection Simulator (FIS). I’m **Nasia Ullas**, and I’ll guide you through designing, executing, and analyzing fault-injection experiments to strengthen your system resilience. As modern architectures grow in complexity, unexpected failures can lead to significant downtime costs: * 44% of organizations report that **1 hour of downtime** costs between **\$1 million and \$5 million**. * In 2021, Facebook incurred **\$80 million+** in losses from **seven hours** of downtime. * A recent “blue screen of death” outage impacted airlines, banks, healthcare providers, and countless other businesses worldwide. ![The image shows a Windows blue screen error message indicating that the PC ran into a problem and needs to restart, with a progress indicator at 5% complete.](https://kodekloud.com/kk-media/image/upload/v1752871956/notes-assets/images/Chaos-Engineering-Course-Introduction/windows-blue-screen-error-restart.jpg) Chaos engineering is the practice of intentionally injecting faults into a system to uncover weaknesses and validate its ability to withstand real-world disruptions. In this course, we’ll leverage [AWS Fault Injection Simulator (FIS)](https://aws.amazon.com/fis/) to conduct controlled experiments in your AWS environment. *** ## Course Outline We’ll cover seven high-level modules, each focusing on different AWS services and fault types: * **Module 1: Basic FIS Experiments**\ Configure IAM, create experiment templates, execute tests, and monitor results with dashboards. * **Module 2: Sample Application & Steady-State Metrics**\ Deploy a reference application and define baseline performance metrics. * **Module 3: Disk Fill Scenario on EC2**\ Simulate disk saturation on EC2 instances and analyze its impact on application behavior. * **Module 4: Aurora Reader Reboot**\ Inject a reboot fault into an Aurora reader node and observe recovery processes. * **Module 5: Fargate Load Stress Test**\ Apply CPU and memory stress to a serverless Fargate task and evaluate performance under high load. * **Module 6: EKS Memory Stress & Pod Deletion**\ Perform memory saturation tests and pod-deletion experiments in your EKS cluster to validate self-healing. * **Module 7: Availability Zone Power Interruption**\ Simulate a power outage in an entire availability zone to assess multi-AZ resilience. *** ## Conclusion By the end of this lesson, you’ll have a solid understanding of how to: * Design robust failure scenarios for cloud applications. * Execute controlled experiments safely. * Analyze results to strengthen your system’s resilience. Let’s get started and build more reliable, fault-tolerant architectures with AWS FIS! *** ## Further Reading * [AWS Fault Injection Simulator Documentation](https://docs.aws.amazon.com/fis/latest/userguide/) * [Amazon CloudWatch](https://aws.amazon.com/cloudwatch/) * [AWS X-Ray](https://aws.amazon.com/xray/) * [Amazon EC2](https://aws.amazon.com/ec2/) * [Amazon Aurora](https://aws.amazon.com/rds/aurora/) * [AWS Fargate](https://aws.amazon.com/fargate/) * [Amazon EKS](https://aws.amazon.com/eks/)