Book Image

Running Windows Containers on AWS

By : Marcio Morales
Book Image

Running Windows Containers on AWS

By: Marcio Morales

Overview of this book

Windows applications are everywhere, from basic intranet applications to high-traffic public APIs. Their prevalence underscores the importance of combining the same tools and experience for managing a modern containerized application with existing critical Windows applications to reduce costs, achieve outstanding operational excellence, and modernize quickly. This comprehensive guide to running and managing Windows containers on AWS looks at the best practices from years of customer interactions to help you stay ahead of the curve. Starting with Windows containers basics, you’ll learn about the architecture design that powers Amazon ECS, EKS, and AWS Fargate for Windows containers. With the help of examples and best practices, you’ll explore in depth how to successfully run and manage Amazon ECS, EKS, and AWS Fargate clusters with Windows containers support. Next, the book covers day 2 operations in detail, from logging and monitoring to using ancillary AWS tools that fully containerize existing legacy .NET Framework applications into containers without any code changes. The book also covers the most common Windows container operations, such as image lifecycle and working with ephemeral hosts. By the end of this book, you’ll have mastered how to run Windows containers on AWS and be ready to start your modernization journey confidently.
Table of Contents (22 chapters)
1
Part 1: Why Windows Containers on Amazon Web Services (AWS)?
4
Part 2: Windows Containers on Amazon Elastic Container Service (ECS)
9
Part 3: Windows Containers on Amazon Elastic Kubernetes Service (EKS)
14
Part 4: Operationalizing Windows Containers on AWS

Exploring Windows host and Pod resource management

In Chapter 1, Windows Container 101, we learned how Windows Server implements resource management on Windows containers and how the Host Computer Service (HCS) governs these resources.

In Kubernetes, you can specify how many resources (memory, RAM, and CPU) a Pod can request and be limited to before it gets scheduled to a host. kube-scheduler is responsible for using the request/limit information in order to decide which node to schedule the Pod on.

We learned that the Windows Server OS is entirely different from Linux, thus changing the behavior of how a Windows Pod performs and allocates memory and CPU per Pod. I often see customers overlooking Amazon EC2 Windows node capacity planning and usually only figuring out they could have done better when the problem has already happened. The beauty of the cloud is that it allows quick changes, but imagine if it did not do so.

However, understanding how resource management works...