Best of The New Stack — April 2026

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    Article
    Avatar of newstackThe New Stack·6w

    In the AI Age, Java is More Relevant Than Ever

    Java is positioned as a strong choice for AI development in enterprise environments, not just Python. The JVM's runtime efficiency makes it cost-effective for AI workloads where budget spent on compute competes with token costs. Frameworks like LangChain4j, Spring AI, and embabel bring first-class AI capabilities to Java. AI coding assistants like GitHub Copilot and Cursor are now highly proficient at Java, especially with popular frameworks like Spring Boot. Java's verbosity becomes an advantage in the AI age since AI-generated code is easier for developers to read and review. AI agents are also enabling continuous modernization of legacy Java codebases, turning a historically expensive one-off project into an ongoing process. Microsoft's JDConf is highlighted as a venue for Java practitioners to explore AI-in-Java topics.

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    Article
    Avatar of newstackThe New Stack·5w

    Who will maintain the web when PHP’s veterans retire?

    A Perforce 2026 PHP Landscape Report surveying over 700 developers reveals a growing skills gap in the PHP ecosystem: more than half of PHP developers have 15+ years of experience, while only 15% have five years or less. Hiring has become the top challenge for PHP team managers, with 24% citing lack of skilled personnel as a leading operational concern. Analysts warn this isn't just a PHP problem but an open source problem, compounded by AI-generated code creating silent technical debt without enough junior developers to manage it. Despite the talent crunch, PHP remains foundational — tied with JavaScript at 72% usage — powering millions of e-commerce sites, WordPress installations, and APIs, mostly at companies with fewer than 500 employees. Symfony and Laravel lead the framework landscape.

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    Article
    Avatar of newstackThe New Stack·5w

    Why Postgres wants NVMe on the hot path, and S3 everywhere else

    Postgres commit durability requires WAL flushes that block until the kernel confirms the write is durable. On NVMe this takes tens of microseconds; on object storage like S3 it can be orders of magnitude slower. This latency difference directly caps OLTP throughput, especially at lower concurrency where group commit doesn't help. MVCC internals (tuple versioning, full-page writes, vacuum, hint bits) further amplify small scattered I/O, making fast local storage essential on the hot path. S3 excels at WAL archiving, base backups, snapshots, and feeding analytics pipelines — jobs that don't touch the commit path. PostgreSQL 18's async I/O improvements are designed to drive fast local storage harder, not to close the gap with object storage. The recommended architecture keeps NVMe (or fast block storage) on the commit and cache-miss path, and pushes cold, reconstructable state to S3.

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