Engineering With Java: Digest #39
Curated and Hand Picked Best Java and Spring Blogs.
This collection of articles explores various techniques and tools that enhance the performance and scalability of microservices architecture. From optimizing database interactions and implementing caching strategies to leveraging advanced patterns like CQRS and client-side load balancing, each piece provides valuable insights for developers.
Dive into these valuable resources to enhance your Java development skills. Also consider subscribing to the newsletter to get weekly feed on Java and Spring Boot articles.
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Mastering High-Concurrency with CQRS: Independent Scaling of Reads and Writes in Microservices
This article explains how separating the read and write operations using Command Query Responsibility Segregation (CQRS) can help scale microservices independently.
This approach allows the write and read services to handle different load requirements, enhancing the system’s ability to manage high concurrency and complex data consistency needs.
Ensuring Atomicity in Distributed Transactions for Microservices
This article covers strategies to maintain atomicity across services, which is challenging in distributed systems. discusses approaches like the Saga pattern, Two-Phase Commit (2PC), and outbox pattern, explaining how they manage data consistency and fault tolerance in microservices.
Each method has unique strengths and trade-offs for ensuring atomicity without compromising system scalability or reliability.
Dust: Open-Source Actors for Java
Dust is an open-source framework that enables actor-based programming for Java, enhancing concurrency and scalability. It implements lightweight actors that can communicate via messages, leveraging Java’s structured concurrency and Loom project for efficient thread management.
Dust simplifies developing highly concurrent applications by focusing on task-based processing while keeping resources optimized. The project offers useful abstractions for managing complex, asynchronous workflows, making it valuable for scenarios like distributed systems and microservices.
Implement Hibernate Second-Level Cache With NCache
This article explains how to set up Hibernate’s second-level cache with NCache, enhancing data retrieval speed by caching frequently accessed data. NCache works as a distributed cache provider, reducing database hits and improving scalability in high-load applications.
Configuration involves specifying cache regions for entities and using NCache as the provider, which helps Hibernate manage cached data efficiently across distributed environments.
How to Optimize API Payloads with Compression in Spring Boot
This article explains how to compress API payloads in Spring Boot, which helps reduce data transfer size and improve application performance. He covers setting up gzip compression in Spring Boot, a straightforward way to compress responses by adjusting configuration properties.
The guide highlights the benefits of compression, including lower bandwidth usage and faster client-server communication, which can enhance the user experience in high-traffic applications.
How to Use Connection Pooling for Faster Database Access in Spring Boot
This article explains how to set up connection pooling in Spring Boot to improve database access speeds. By using connection pooling, the application maintains a pool of database connections that can be reused, reducing the time spent on opening and closing connections.
He discusses configuration options and highlights the benefits of pooling in high-traffic environments, where it can enhance performance and resource management.
Spring Data JPA: Optimizing Performance with Pagination, Sorting, and Filtering Using Specification
This article from Java Revisited discusses optimizing performance in Spring Data JPA by implementing pagination, sorting, and filtering. Using specifications, developers can construct flexible query criteria to refine data retrieval, improving both efficiency and response time.
This approach helps manage large datasets effectively by loading only the needed records and applying filtering criteria at the database level, reducing memory load in applications.
Tutorial: Jextract - The Native Library Binding Extraction Tool
The jextract tool tutorial on Inside Java explains how to use jextract to convert native library header files (.h) into Java bindings. These bindings enable Java programs to call native code using the Foreign Function and Memory API.
The guide walks through obtaining, running jextract, and using the generated Java bindings, making it easier for developers to integrate native libraries directly into Java applications.
Single-threaded Redis Speed: How I/O Multiplexing and In-Memory Storage Make Redis a Powerhouse
This article highlights how Redis achieves high-speed data access through two key mechanisms: I/O multiplexing and in-memory storage.
I/O multiplexing allows Redis to handle multiple client requests efficiently, while in-memory storage minimizes latency, making Redis ideal for real-time applications.
These features contribute to Redis’s reputation as a powerful caching and data storage solution, capable of managing high-speed data operations.
How to Implement Client-Side Load Balancing With Spring Cloud
The article discusses implementing client-side load balancing in microservices using Spring Cloud Load Balancer. It explains the difference between client-side and server-side load balancing and outlines various algorithms like round-robin and weighted choice.
The setup involves adding dependencies to a Spring Boot project, configuring load balancing in
application.yaml, and testing it with a simple microservice example.The article emphasizes the importance of client load balancing for system resilience and includes sample code for practical implementation.