Chapter 1, Introduction to Amazon Web Services, briefly introduces you to AWS, where you will not only learn about the background and industry shift that started the movement into utility computing, but also where AWS fits into it.
Chapter 2, Core Services – Building Blocks for Your Product, introduces you to various AWS components that you will use to build your products.
Chapter 3, Availability Patterns – Understanding Your Needs, combines some of the components into architectures aimed toward creating your own highly available services.
Chapter 4, Security – Ensuring the Integrity of Your Systems, covers some of the best security practices that will allow you to establish a perimeter around all of your products from the start.
Chapter 5, Continuous Deployment – Introducing New Features with Minimal Risk, covers some of the practices that you can use to provide a continuous deployment pipeline, which will enable you to put your product in front of your clients quickly and in a reliable and reproducible way, whether this includes new product features, experiments, or configurations.
Chapter 6, Ephemeral Environments – Sandboxes for Experiments, supplies a design pattern to aid you in your move to the cloud. The financial benefits, the advantages for your customers, and the improved velocity of your software engineers will be considered. Some high-level topics that are making headlines in the DevOps movement and can improve our productivity within AWS will also be covered.
Chapter 7, Operation and Maintenance – Keeping Things Running at Peak Performance, combines various processes that will help you to deliver a product with high availability and ensure that, in the event of a disaster, you have practiced your recovery methods.
Chapter 8, Application Virtualization – Using Cloud Native Patterns for Your Workloads, shows how to isolate services for performance improvements and cost savings. You will inspect the choices available for reducing product complexity and review enterprise patterns for mitigating failures through the separation of concerns
Chapter 9, Antipatterns – Avoiding Counterproductive Solutions, attends to the difficulties you might encounter as your product complexity grows.
Chapter 10, Databases – Identifying Which Type Fits Your Needs, helps identify how to collect and learn from data that can help you avoid anomalies that haven't been widely encountered in the cloud yet.
Chapter 11, Data Processing – Handling Your Data Transformation, discusses various techniques for processing the data in your infrastructure, especially in the field of machine learning.
Chapter 12, Observability – Understanding How Your Products Are Behaving, covers how to observe your application with logging, metrics, and tracing, which will help you track changes in your infrastructure, find inconsistencies, and provide insights into process improvements.
Chapter 13, Anti-Patterns – Bypassing Inferior Options, analyzes persistence paradigms, that are ineffective and may result in undesired consequences.
