Book Image

Accelerating DevSecOps on AWS

By : Nikit Swaraj
Book Image

Accelerating DevSecOps on AWS

By: Nikit Swaraj

Overview of this book

Continuous integration and continuous delivery (CI/CD) has never been simple, but these days the landscape is more bewildering than ever; its terrain riddled with blind alleys and pitfalls that seem almost designed to trap the less-experienced developer. If you’re determined enough to keep your balance on the cutting edge, this book will help you navigate the landscape with ease. This book will guide you through the most modern ways of building CI/CD pipelines with AWS, taking you step-by-step from the basics right through to the most advanced topics in this domain. The book starts by covering the basics of CI/CD with AWS. Once you’re well-versed with tools such as AWS Codestar, Proton, CodeGuru, App Mesh, SecurityHub, and CloudFormation, you’ll focus on chaos engineering, the latest trend in testing the fault tolerance of your system. Next, you’ll explore the advanced concepts of AIOps and DevSecOps, two highly sought-after skill sets for securing and optimizing your CI/CD systems. All along, you’ll cover the full range of AWS CI/CD features, gaining real-world expertise. By the end of this AWS book, you’ll have the confidence you need to create resilient, secure, and performant CI/CD pipelines using the best techniques and technologies that AWS has to offer.
Table of Contents (15 chapters)
1
Section 1:Basic CI/CD and Policy as Code
5
Section 2:Chaos Engineering and EKS Clusters
9
Section 3:DevSecOps and AIOps

AIOps and how it helps in IT operations

AI is a hot topic everywhere and, unlike previously, lots of people now really understand the meaning of AI and how it is applied in real-life scenarios or use cases. Before jumping right to AIOps, we first need to set the context by understanding AI and ML.

AI is the broadest term and has been around for decades as a research topic. AI allows a computer to perform any task that normally requires human intelligence. ML is a subset of AI that solves specific tasks by learning from patterns and data and making predictions without explicitly being programmed. This phrase of explicitly being programmed is the key factor that translates some huge opportunities to transform how we do IT operations today. ML is one approach to AI, recently popular due to big data and cheap compute through cloud computing. Broadly, there are two types of ML algorithms:

  • Supervised learning algorithms take the raw data that you are inputting, and they also...