When you break down your monolithic application to several focused microservices, you will have to find an efficient way to locate your services; moreover, services will have to communicate with each other. That is exactly what service discovery is all about. Now let's say you figured out a way to locate them: what happens to those services that are scaled to a factor greater than one? You have to efficiently load-balance them. This is another problem that this chapter intends to solve.
Microservices Deployment Cookbook
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Microservices Deployment Cookbook
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Overview of this book
This book will help any team or organization understand, deploy, and manage microservices at scale. It is driven by a sample application, helping you gradually build a complete microservice-based ecosystem. Rather than just focusing on writing a microservice, this book addresses various other microservice-related solutions: deployments, clustering, load balancing, logging, streaming, and monitoring.
The initial chapters offer insights into how web and enterprise apps can be migrated to scalable microservices. Moving on, you’ll see how to Dockerize your application so that it is ready to be shipped and deployed. We will look at how to deploy microservices on Mesos and Marathon and will also deploy microservices on Kubernetes. Next, you will implement service discovery and load balancing for your microservices. We’ll also show you how to build asynchronous streaming systems using Kafka Streams and Apache Spark.
Finally, we wind up by aggregating your logs in Kafka, creating your own metrics, and monitoring the metrics for the microservice.
Table of Contents (15 chapters)
Microservices Deployment Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Free Chapter
Building Microservices with Java
Containerizing Microservices with Docker
Deploying Microservices on Mesos
Deploying Microservices on Kubernetes
Service Discovery and Load Balancing Microservices
Monitoring Microservices
Building Asynchronous Streaming Systems with Kafka and Spark
More Clustering Frameworks - DC/OS, Docker Swarm, and YARN
Customer Reviews