Book Image

Hands-On Kubernetes on Windows

By : Piotr Tylenda
Book Image

Hands-On Kubernetes on Windows

By: Piotr Tylenda

Overview of this book

With the adoption of Windows containers in Kubernetes, you can now fully leverage the flexibility and robustness of the Kubernetes container orchestration system in the Windows ecosystem. This support will enable you to create new Windows applications and migrate existing ones to the cloud-native stack with the same ease as for Linux-oriented cloud applications. This practical guide takes you through the key concepts involved in packaging Windows-distributed applications into containers and orchestrating these using Kubernetes. You'll also understand the current limitations of Windows support in Kubernetes. As you advance, you'll gain hands-on experience deploying a fully functional hybrid Linux/Windows Kubernetes cluster for development, and explore production scenarios in on-premises and cloud environments, such as Microsoft Azure Kubernetes Service. By the end of this book, you'll be well-versed with containerization, microservices architecture, and the critical considerations for running Kubernetes in production environments successfully.
Table of Contents (23 chapters)
1
Section 1: Creating and Working with Containers
5
Section 2: Understanding Kubernetes Fundamentals
9
Section 3: Creating Windows Kubernetes Clusters
12
Section 4: Orchestrating Windows Containers Using Kubernetes

Available monitoring solutions

The word monitoring is commonly used as an umbrella term that covers the following:

  • Observability: Providing observability for your components means exposing information about their inner state so that you can access the data easily and do reasoning about the actual state of your components. In other words, if something is observable, you can understand it. A well-known example of a feature that provides observability is logging. Your applications produce logs so that you can examine the flow and the current state of your application. There are three pillars of observability: logging, distributed tracing, and metrics. Distributed tracing provides insight into the flow of a request going through multiple services, for example, using correlation IDs. Metrics can be just numeric information exposed by your application, for example, counters or gauges...