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Microservices Deployment Cookbook

Microservices Deployment Cookbook

By : Vikram Murugesan
3.8 (6)
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Microservices Deployment Cookbook

Microservices Deployment Cookbook

3.8 (6)
By: Vikram Murugesan

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 (9 chapters)
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Introduction


Streaming has been picking up traction lately. It is one way of processing your data. In fact, there are two modes in which your data processing application can operate: batching and streaming. In batching, you work on batches of datasets at frequent intervals. However, in streaming, you process data as it gets streamed. This mode has always been a challenge. Achieving this type of streaming behavior will open up a lot of different opportunities.

You could make things happen quickly. For example, a banking application can send you relevant coupons based on your spending activity. Or a shopping application can recommend products based on your viewing activity. And all this will happen right away instead of waiting until the middle of the night for a batch job to run. Streaming has become a critical part of many businesses these days. The past couple of years have seen a tremendous improvement in streaming technologies. Frameworks such as Apex, Storm, Spark, Flink, Kafka Streams...

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