Learn how to do Kafka Stream with Spring Boot! 🍃 With a city tour visits system…
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Java, What’s Old? Part I: Collections
Table of Contents OptionalStatisticsLinkedHashMapWeakHashMapBitSet A few weeks ago, I had the honor to present at the Arnhem JUG in the Netherlands about “Java, What’s old?” In this series, I’m focusing on what’s old in the JDK, not that known, and …
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Foojay Podcast #73: JCon Report, Part 2 – Evolutions in the Java Language and Runtime
Table of Contents VideoPodcast (audio only)Content In the second part of our JCON interviews, recorded at the conference in May, we focuses on general evolutions within the Java world and how they influence how we write code and develop applications. …
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Java Concurrency Best Practices for MongoDB
Table of Contents Lost updatesDirty readsNon-repeatable readsPhantom readsHow to avoid these issuesIsolationRead concernWrite concern In a multi-threaded, distributed environment like MongoDB, when clients execute queries concurrently, operations interleave with one another if they are not isolated, whether those operations involve …
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Performance Best Practise No. 1: Optimize Database Operations
Table of Contents How GlassFish helps with improving database performanceConnection pool configurationJDBC batchingJakarta Persistence (JPA) batchingNext Steps Database operations are a very critical part of most applications in regards of performance. There are multiple reasons why database operations can significantly …
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Faster Java Warmup: CRaC versus ReadyNow
Table of Contents What happens at Java startupJava warmup phase DeoptimizationsSolutions Provided by AzulCoordinated Restore at Checkpoint (CRaC) ReadyNow Cloud Native CompilerCRaC Compared to ReadyNow Conclusion This is the first blog post in a series on faster Java application warmup with ReadyNow.Azul has developed …
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Java’s Structured Concurrency: Finally Finding Its Footing
Table of Contents What Actually Changed This TimeThe Core Concept Remains StrongThe headline change: static factory methodsJoiners: pick your success policyRolling your own JoinerBetter cancellation and deadlinesScoped values ride alongGuard-rails against misuseObservability improvementsSome more examples to try outFinal thoughts The …
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Brokk: AI for Large (Java) Codebases
Table of Contents Sidebar: Under the HoodRecommendationsWorking with GitSidebar: LLM ModelsThe Edit Loop There are two reasons that AI makes mistakes writing code: The LLM just isn’t smart enough to tackle the problem effectively, and it simply gets the answer …
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10 Best Practises For Jakarta EE Performance Optimization
Table of Contents Quick ComparisonSecrets of Performance Tuning Java on Kubernetes by Bruno BorgesNext Steps With this article, we start a series where we compiled 10 best practices for performance optimizations and suggestions how to implement them using Jakarta EE & Eclipse GlassFish. Enjoy …
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AI Test Generation: A Dev’s Guide Without Shooting Yourself in the Foot
Table of Contents So, AI Can Write Tests Now? Cool, But…How AI Learns to Code (And Why That’s a Problem for Tests)Problem #1: AI Tests Might Just Be WrongProblem #2: Testing the Code You Have, Not the Code You Need …
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How to send prompts in bulk with Spring AI and Java Virtual Threads
Table of Contents Here’s the flow:Virtual Threads for Massive ParallelismSpring AI Prompt CallProcessing in BatchesHandling Errors GracefullyProcess Results in BulkFull ImplementationStay curious! TL;DR: You’re building an AI-powered app that needs to send lots of prompts to OpenAI. Instead of sending …