InfoQ Homepage News
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How Datadog Used Claude and Cursor for Test-Driven Production Migration
In a recent article, Datadog engineer Arnold Wakim shared what worked, what didn't, and the lessons they learned while evolving a critical production system using AI to overcome hard limits in its storage backend and significantly improve performance.
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WordPress 7.0 Ships with AI Foundations in Core, a Modernized Admin, and New Design Tools
WordPress 7.0, released on May 20, 2026, includes new AI infrastructure, a redesigned admin interface, and updated design tools. Key features comprise an AI Client, Abilities API, and Command Palette, alongside increased PHP requirements. Community feedback is mixed, particularly regarding AI integration. Developers are advised to consult the official documentation for upgrade guidance.
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How Open Source Enables Collaboration in Creating a Platform
A platform is a collaboration system: platform teams depend on application teams, and both need shared standards. Engineers trust a platform through its predictable behavior, not its features. Being an engineer is about problem-solving and being passionate about it. And being an engineer means sharing your passion for problem-solving.
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OpenAI Fixes 18-Year-Old GNU libunwind Bug by Treating Crash Debugging Like Epidemiology
OpenAI found two unrelated bugs masquerading as one in ChatGPT's data infrastructure. Silent hardware corruption on one Azure host and an 18-year-old race condition in GNU libunwind's setcontext function with a one-instruction vulnerability window. The breakthrough came from switching to population-level crash analysis rather than examining individual core dumps.
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AlloyDB Ships Proxy Models That Replace LLM Calls with Local Inference inside the Database
Google shipped AlloyDB AI functions GA with a proxy model architecture that trains a lightweight local model from LLM outputs, then runs queries at database speed without external calls. Smart batching delivers 2,400x throughput improvement. The proxy model reaches 100,000 rows per second in preview, but benchmark numbers apply only to ai.if in internal testing.
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AWS Details How One Customer Scaled to One Million Lambda Functions
AWS has outlined how ProGlove, an industrial-wearables manufacturer, was able to scale its SaaS platform to run more than one million AWS Lambda functions spread across thousands of dedicated customer accounts.
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The Kubernetes Approach to AI-Assisted Maintainership Prioritises Human Accountability
The Kubernetes community has introduced a framework for integrating AI into open-source maintainership, emphasising human accountability in code quality and oversight. AI tools may streamline workflows, but ultimate responsibility lies with human maintainers. The framework requires disclosure of AI usage in contributions and prohibits AI-generated commit messages.
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Airbnb Shares Architecture behind Sitar-Agent Dynamic Configuration Sidecar for Kubernetes Services
Airbnb engineers detailed Sitar-agent, a Kubernetes sidecar for dynamic configuration delivery across tens of thousands of pods, processing updates several times per minute. The system was redesigned with Java, Amazon S3 snapshot bootstrapping, and a migration from Sparkey to SQLite to improve reliability, startup performance, and configuration availability at scale.
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Switching from PostgreSQL to ClickHouse for Improved Performance and Scalability
Momentic, the company behind an AI-driven software testing platform, recently rearchitected its caching system to handle over 2 million queries per day across 20 billion total entries, while maintaining an average response latency of around 250 ms. This improvement was made possible by transitioning from PostgreSQL to the column-oriented database ClickHouse.
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AWS Expands DevOps Agent with AI-Powered Release Management to Validate Code before Production
Amazon Web Services (AWS) has announced a major expansion of its AWS DevOps Agent, introducing new release management capabilities designed to assess code changes and autonomously test software before it reaches production.
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How HubSpot Scaled Semantic Search to 20 Billion Vectors
SaaS software vendor HubSpot has described how its semantic search platform grew from a proof of concept into an internal service that now manages more than 20 billion vectors across 38-plus teams. The company says the system now supports agents, RAG, and contact deduplication, and that the increase in agent usage has made retrieval quality and latency more important than before.
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Node.js 26: Temporal API Enabled by Default, V8 14.6, and a Round of Deprecations
Node.js 26 has been released, featuring the Temporal API enabled by default, an updated V8 engine to version 14.6, and the Undici HTTP client upgraded to 8.0. The release also removes deprecated legacy APIs. Developers should note migration points related to NODE_MODULE_VERSION changes. Node.js 26 is current for six months before entering long-term support.
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Java News Roundup: Strict Field Initialization, GlassFish, GraalVM, JReleaser, RefactorFirst
This week's Java roundup for June 29th, 2026, features news highlighting: a new JEP candidate, Strict Field Initialization; point releases of GraalVM, JReleaser, RefactorFirst and Java Operator SDK; maintenance releases of GlassFish and Micronaut; the second milestone release of Grails 8.0; and the beta release of Open Liberty 26.0.0.7.
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Netflix Cuts Cassandra Read Latency from Seconds to Milliseconds with Dynamic Partition Splitting
Netflix engineers introduced dynamic partition splitting for Cassandra to address wide partitions in time series workloads. The metadata-driven approach detects oversized partitions, splits them smaller units, and routes reads across child partitions. Netflix reported lower read latency from seconds to milliseconds, reduced timeouts, and improved cluster stability while maintaining transparency.
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InfoQ Opens AI Security & Privacy Engineering Cohort for Regulated Industries
InfoQ has opened enrollment for a five-week AI Security & Privacy Engineering cohort for senior engineers and architects in regulated industries, focused on applying security, privacy, threat modeling, observability, and governance practices to production AI systems.