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Persistence Best Practices for Java Applications

Persistence Best Practices for Java Applications

By : Otavio Santana, Karina Varela
4.9 (9)
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Persistence Best Practices for Java Applications

Persistence Best Practices for Java Applications

4.9 (9)
By: Otavio Santana, Karina Varela

Overview of this book

Having a solid software architecture breathes life into tech solutions. In the early stages of an application’s development, critical decisions need to be made, such as whether to go for microservices, a monolithic architecture, the event-driven approach, or containerization. In Java contexts, frameworks and runtimes also need to be defi ned. But one aspect is often overlooked – the persistence layer – which plays a vital role similar to that of data stores in modern cloud-native solutions. To optimize applications and data stores, a holistic understanding of best practices, technologies, and existing approaches is crucial. This book presents well-established patterns and standards that can be used in Java solutions, with valuable insights into the pros and cons of trending technologies and frameworks used in cloud-native microservices, alongside good Java coding practices. As you progress, you’ll confront the challenges of cloud adoption head-on, particularly those tied to the growing need for cost reduction through stack modernization. Within these pages, you’ll discover application modernization strategies and learn how enterprise data integration patterns and event-driven architectures enable smooth modernization processes with low-to-zero impact on the existing legacy stack.
Table of Contents (18 chapters)
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1
Part 1: Persistence in Cloud Computing – Storing and Managing Data in Modern Software Architecture
6
Part 2: Jakarta EE, MicroProfile, Modern Persistence Technologies, and Their Trade-Offs
9
Chapter 7: The Missing Guide for jOOQ Adoption
11
Part 3: Architectural Perspective over Persistence

Architecting Distributed Systems – Challenges and Anti-Patterns

In today’s digital landscape, the demand for scalable and reliable systems has led to the widespread adoption of distributed systems. These complex networks of interconnected components are designed to handle large-scale data processing, storage, and communication across multiple machines or nodes. However, architecting distributed systems comes with a unique set of challenges and pitfalls.

Building distributed systems aims to achieve high availability, fault tolerance, and better performance and scalability while distributing the workload across multiple nodes. However, the complexity of these systems often gives rise to various challenges that architects and developers must overcome. From ensuring data consistency and synchronization to managing network latency and optimizing performance, numerous factors should be considered when designing a distributed system.

One of the critical challenges in architecting...

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