Kubernetes: Up and Running
Java 8 in Action
Chapter 11. CompletableFuture: composable asynchronous programming This chapter covers Creating an asynchronous computation and retrieving its result Increasing throughput using non-blocking operations Designing and implementing an asynchronous API Consuming asynchronously a synchronous API Pipelining and merging two or more asynchronous operations Reacting to the completion of an asynchronous ope
Achieving cloud-native operability with microservices, DevOps, and continuous delivery
Software developers like to make lists of three things and then say, smugly, “Pick any two.” For example, the Project Management triangle is good, fast, cheap (pick any two), and the CAP Theorem offers consistency, availability, and partition tolerance (pick any two). When working with cloud-native software, you don’t have the luxury of picking just two items from the trio of microservices, DevOps
Defining a reactive microservice
Editor’s Note: The following post is an excerpt from the report “Reactive Microservices Architecture: Design Principles for Distributed Systems,” by Jonas Bonér, due out in March. Sign up to be notified when the free report download becomes available. One of the main principles for employing a reactive microservices-based architecture is the algorithmic design pattern divide and conquer: the decom
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Spock: Up and Running
Building Evolutionary Architectures
Kafka: The Definitive Guide
Managing for Happiness
Microservices with Docker on Microsoft Azure™ (includes Content Update Program)
Building Microservices
Patterns, Principles, and Practices of Domain-Driven Design
Spring Microservices
Domain-Driven Design Distilled, 1/e
Dependency Injection in .NET
Building Microservices with Spring Boot LiveLessons (Video Training)