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    <title>InfoQ</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ feed</description>
    <item>
      <title>Stripe Benchmark Shows AI Agents Build Integrations but Struggle with Validation</title>
      <link>https://www.infoq.com/news/2026/07/stripe-ai-agents-benchmark/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/stripe-ai-agents-benchmark/en/headerimage/generatedHeaderImage-1783301844753.jpg"/&gt;&lt;p&gt;Stripe introduces a benchmark suite to evaluate whether AI agents can build real-world Stripe integrations across backend, frontend, and browser-based checkout workflows. The study examines end-to-end software engineering capability, focusing on execution, testing, and validation gaps in agentic systems under production-like constraints.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Integration</category>
      <category>Claude</category>
      <category>Web Browser</category>
      <category>AI Coding</category>
      <category>ChatGPT</category>
      <category>Stripe</category>
      <category>Validation</category>
      <category>Benchmark</category>
      <category>Agents</category>
      <category>AI Development</category>
      <category>Software Engineering</category>
      <category>payment</category>
      <category>AIOps</category>
      <category>Observability</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Wed, 15 Jul 2026 14:25:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/stripe-ai-agents-benchmark/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-07-15T14:25:00Z</dc:date>
      <dc:identifier>/news/2026/07/stripe-ai-agents-benchmark/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Postgres for Production Agents: Your Relational Foundation for Enterprise AI</title>
      <link>https://www.infoq.com/presentations/postgres-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/postgres-ai-agents/en/mediumimage/gwen-shapira-medium-1783500671134.jpeg"/&gt;&lt;p&gt;Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to leverage Postgres's multi-modal capabilities - including JSONB parsing and high-recall HNSW vector indexing - to deliver deterministic and semantic context to LLMs. She also discusses vector quantization to speed up queries by 4x and strategies for managing agentic memory.&lt;/p&gt; &lt;i&gt;By Gwen Shapira&lt;/i&gt;</description>
      <category>Postgres</category>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>QCon AI 2025</category>
      <category>Transcripts</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>presentation</category>
      <pubDate>Wed, 15 Jul 2026 12:57:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/postgres-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Gwen Shapira</dc:creator>
      <dc:date>2026-07-15T12:57:00Z</dc:date>
      <dc:identifier>/presentations/postgres-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>AWS Ships Claude Apps Gateway as Self-Hosted Control Plane for Claude Code and Claude Desktop</title>
      <link>https://www.infoq.com/news/2026/07/claude-apps-gateway-aws/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;AWS and Anthropic have released the Claude apps gateway for AWS, a self-hosted control plane that centralizes identity, policy, telemetry, routing, and spend caps for Claude Code and Claude Desktop. The gateway runs as a single stateless container and routes inference to Amazon Bedrock or Claude Platform on AWS.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>AWS</category>
      <category>Access Control</category>
      <category>Claude</category>
      <category>Cloud</category>
      <category>Anthropic</category>
      <category>Cloud Architecture</category>
      <category>AI Architecture</category>
      <category>Amazon Web Services</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Wed, 15 Jul 2026 11:04:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/claude-apps-gateway-aws/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-07-15T11:04:00Z</dc:date>
      <dc:identifier>/news/2026/07/claude-apps-gateway-aws/en</dc:identifier>
    </item>
    <item>
      <title>Google Cloud Workbench Notebooks Extension Connects VS Code to Google Cloud's Jupyter Notebooks</title>
      <link>https://www.infoq.com/news/2026/07/cloud-workbench-vscode-extension/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;The Google Cloud Workbench Notebooks extension for VS Code is a new tool that enables developers to connect their local IDE directly to managed Jupyter notebook environments on Google Cloud.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Jupyter Notebooks</category>
      <category>Cloud</category>
      <category>Large language models</category>
      <category>Google Cloud</category>
      <category>Google</category>
      <category>Machine Learning</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 22:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/cloud-workbench-vscode-extension/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-07-14T22:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/cloud-workbench-vscode-extension/en</dc:identifier>
    </item>
    <item>
      <title>Google and Industry Partners Announce Agentic Resource Discovery Specification for AI Agents</title>
      <link>https://www.infoq.com/news/2026/07/agentic-resource-discovery-spec/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/agentic-resource-discovery-spec/en/headerimage/generatedHeaderImage-1783309687458.jpg"/&gt;&lt;p&gt;Google and industry partners announced Agentic Resource Discovery (ARD) Specification, an open standard for publishing, discovering, and verifying AI tools, APIs, and agents. ARD introduces a discovery layer built on catalogs and registries, enabling dynamic capability discovery while leveraging existing protocols such as MCP and OpenAPI for execution and emphasizing trust and interoperability.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Specification</category>
      <category>Distributed Systems</category>
      <category>AI Coding</category>
      <category>Agents</category>
      <category>github</category>
      <category>Agent2Agent</category>
      <category>AI Security</category>
      <category>Cisco</category>
      <category>Salesforce.com</category>
      <category>Google</category>
      <category>GoDaddy</category>
      <category>AI Architecture</category>
      <category>Service Discovery</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Microsoft</category>
      <category>AI Interpretability</category>
      <category>Platform Engineering</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 13:40:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/agentic-resource-discovery-spec/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-07-14T13:40:00Z</dc:date>
      <dc:identifier>/news/2026/07/agentic-resource-discovery-spec/en</dc:identifier>
    </item>
    <item>
      <title>Meta's Noninvasive Brain–Computer Interface Brain2Qwerty Achieves 61% Accuracy</title>
      <link>https://www.infoq.com/news/2026/07/meta-brain-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/meta-brain-interface/en/headerimage/generatedHeaderImage-1783863685064.jpg"/&gt;&lt;p&gt;Meta recently open-sourced Brain2Qwerty v2, a noninvasive Brain–Computer Interface (BCI) that can decode sentences from thoughts using electroencephalography (EEG) or magnetoencephalography (MEG) signals from the brain. In evaluations, the system achieved a word accuracy rate 61% on average, compared to 8% for other non-invasive methods.&lt;/p&gt; &lt;i&gt;By Anthony Alford&lt;/i&gt;</description>
      <category>Neural Networks</category>
      <category>Deep Learning</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 13:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/meta-brain-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Anthony Alford</dc:creator>
      <dc:date>2026-07-14T13:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/meta-brain-interface/en</dc:identifier>
    </item>
    <item>
      <title>Presentation: Lessons Learned in Migrating to Micro-Frontends</title>
      <link>https://www.infoq.com/presentations/migration-micro-frontend/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/presentations/migration-micro-frontend/en/mediumimage/luca-mezzalira-medium-1783500980769.jpeg"/&gt;&lt;p&gt;Luca Mezzalira shares proven learnings from guiding hundreds of teams through the migration from monolithic web applications to distributed frontend architectures. He explains the core architectural difference between components and micro-frontends, outlines a 6-step decision framework spanning client vs. server rendering, and discusses how to utilize edge compute for safe, iterative rollouts.&lt;/p&gt; &lt;i&gt;By Luca Mezzalira&lt;/i&gt;</description>
      <category>Micro Frontends</category>
      <category>migration</category>
      <category>QCon San Francisco 2025</category>
      <category>Web Development</category>
      <category>Transcripts</category>
      <category>Architecture &amp; Design</category>
      <category>presentation</category>
      <pubDate>Tue, 14 Jul 2026 12:42:00 GMT</pubDate>
      <guid>https://www.infoq.com/presentations/migration-micro-frontend/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Luca Mezzalira</dc:creator>
      <dc:date>2026-07-14T12:42:00Z</dc:date>
      <dc:identifier>/presentations/migration-micro-frontend/en</dc:identifier>
    </item>
    <item>
      <title>Linkerd 2.20 Delivers Smarter Traffic Management and Dramatic Efficiency Gains</title>
      <link>https://www.infoq.com/news/2026/07/linkerd-2-20-improvements/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/linkerd-2-20-improvements/en/headerimage/generatedHeaderImage-1783856224998.jpg"/&gt;&lt;p&gt;The Linkerd community has announced the release of Linkerd 2.20, introducing a series of performance, observability, and traffic management enhancements that further strengthen the CNCF-graduated service mesh's position as a lightweight alternative for Kubernetes networking.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Cloud Native Computing Foundation</category>
      <category>Service Mesh</category>
      <category>Linkerd</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/linkerd-2-20-improvements/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-07-14T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/linkerd-2-20-improvements/en</dc:identifier>
    </item>
    <item>
      <title>Google's Genkit Ships Agents API with Detached Turns and Human-in-the-Loop for TypeScript and Go</title>
      <link>https://www.infoq.com/news/2026/07/genkit-agents-api-preview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/genkit-agents-api-preview/en/headerimage/generatedHeaderImage-1783618516951.jpg"/&gt;&lt;p&gt;Google released the Genkit Agents API in preview for TypeScript and Go. The open-source framework packages message history, tool loops, streaming, and state persistence behind a single chat() interface. Detached turns let agents work after clients disconnect. Interruptible tools provide human-in-the-loop control with anti-forgery validation on resume.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Java</category>
      <category>API</category>
      <category>Open Source Project Releases</category>
      <category>Cloud</category>
      <category>Agents</category>
      <category>AI Architecture</category>
      <category>Google Cloud</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 10:17:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/genkit-agents-api-preview/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-07-14T10:17:00Z</dc:date>
      <dc:identifier>/news/2026/07/genkit-agents-api-preview/en</dc:identifier>
    </item>
    <item>
      <title>Article: Comprehension at AI Speed: Building a Context Store for Evolutionary Architecture</title>
      <link>https://www.infoq.com/articles/ai-speed-context-store-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/articles/ai-speed-context-store-architecture/en/headerimage/ai-speed-context-store-architecture-header-1783673492911.jpg"/&gt;&lt;p&gt;AI makes the first 80% of development feel fast, but hides architectural complexity until it's too late. To prevent system instability, engineering leaders must shift from raw throughput to systemic comprehension. By unifying spec-anchored SDD, TDD, and automated fitness functions into a repo-bound "Context Store," teams can ensure AI agents and human reviewers evolve code safely.&lt;/p&gt; &lt;i&gt;By Stella Berhe, Stephan Bragner, Vikram Maran, Anand Jayaraman&lt;/i&gt;</description>
      <category>Specification</category>
      <category>Architecture ICSAET</category>
      <category>Evolutionary Architecture</category>
      <category>InfoQ Certification Program</category>
      <category>TDD</category>
      <category>Governance</category>
      <category>Artificial Intelligence</category>
      <category>AI Development</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Tue, 14 Jul 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/ai-speed-context-store-architecture/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Stella Berhe, Stephan Bragner, Vikram Maran, Anand Jayaraman</dc:creator>
      <dc:date>2026-07-14T09:00:00Z</dc:date>
      <dc:identifier>/articles/ai-speed-context-store-architecture/en</dc:identifier>
    </item>
    <item>
      <title>Evolutionary Data Through Schemaboi: Achieving Forward, Backwards, and Sideways Compatibility</title>
      <link>https://www.infoq.com/news/2026/07/durable-document-schema/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/durable-document-schema/en/headerimage/generatedHeaderImage-1784010959321.jpg"/&gt;&lt;p&gt;Drawing from the enduring adaptability of HTML and HTTP,  Seph Gentle proposes embedding self-contained schemas directly into file headers, ensuring data remains readable without external definitions. His experimental format prioritises forward, backwards, and sideways compatibility, enabling data format evolution without central coordination or data loss&lt;/p&gt; &lt;i&gt;By Olimpiu Pop&lt;/i&gt;</description>
      <category>Data</category>
      <category>Schema</category>
      <category>Emerging Technologies</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 08:08:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/durable-document-schema/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Olimpiu Pop</dc:creator>
      <dc:date>2026-07-14T08:08:00Z</dc:date>
      <dc:identifier>/news/2026/07/durable-document-schema/en</dc:identifier>
    </item>
    <item>
      <title>SwiftData Enhances Queries, Adds Support for External Types and Data Store Observation</title>
      <link>https://www.infoq.com/news/2026/07/swiftdata-27-whats-new/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/swiftdata-27-whats-new/en/headerimage/swiftdata-27-whats-new-1784012905834.jpeg"/&gt;&lt;p&gt;The 2027 release of SwiftData introduces support for persisting custom and third-party types via Codable, along with the ability to organize data into SwiftUI list sections. It also adds new capabilities for observing data store changes through ResultsObserver and HistoryObserver.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>Mobile</category>
      <category>SwiftUI</category>
      <category>Apple</category>
      <category>iOS</category>
      <category>Persistence</category>
      <category>MacOS</category>
      <category>Swift</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 08:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/swiftdata-27-whats-new/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-07-14T08:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/swiftdata-27-whats-new/en</dc:identifier>
    </item>
    <item>
      <title>The Path to Sovereign Data: Challenges and Priorities in Local-First Computing</title>
      <link>https://www.infoq.com/news/2026/07/data-ownership-localfirst/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/data-ownership-localfirst/en/headerimage/generatedHeaderImage-1783923656378.jpg"/&gt;&lt;p&gt;A panel on data ownership challenged the definition of "ownership," arguing it must extend beyond simple account control to include structural independence, interoperability, and community governance. Speakers like Zenna Fiscella, Paul Frazee, Boris Mann, and Robin Berjon emphasised the need for shared standards, unbundled platforms, and better tools to support user sovereignty.&lt;/p&gt; &lt;i&gt;By Olimpiu Pop&lt;/i&gt;</description>
      <category>Sovereignty</category>
      <category>Data Governance</category>
      <category>Distributed Data</category>
      <category>Architecture &amp; Design</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Mon, 13 Jul 2026 14:14:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/data-ownership-localfirst/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Olimpiu Pop</dc:creator>
      <dc:date>2026-07-13T14:14:00Z</dc:date>
      <dc:identifier>/news/2026/07/data-ownership-localfirst/en</dc:identifier>
    </item>
    <item>
      <title>How DoorDash Built an AI Shopping Assistant That Doesn’t Rely on the LLM Alone</title>
      <link>https://www.infoq.com/news/2026/07/doordash-ai-ask-assistant/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/doordash-ai-ask-assistant/en/headerimage/generatedHeaderImage-1782515732223.jpg"/&gt;&lt;p&gt;DoorDash details the architecture behind Ask DoorDash, its AI-powered conversational shopping assistant, combining LLMs, specialized AI agents, MCP-based tooling, and an intelligence layer with persistent consumer memory and live backend data. Early results show up to 24% higher checkout conversion, 17% larger baskets, and improved intent accuracy using memory-backed sessions.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Natural Language Processing</category>
      <category>Distributed Systems</category>
      <category>Microservices</category>
      <category>Retrieval-Augmented Generation</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Artificial Intelligence</category>
      <category>ChatBots</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Memory</category>
      <category>Prompt Engineering</category>
      <category>Platform Engineering</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 13 Jul 2026 14:08:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/doordash-ai-ask-assistant/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-07-13T14:08:00Z</dc:date>
      <dc:identifier>/news/2026/07/doordash-ai-ask-assistant/en</dc:identifier>
    </item>
    <item>
      <title>Java News Roundup: TornadoVM 5, JHipster, Google ADK, OmniFish Build of Payara, Introducing Vidocq</title>
      <link>https://www.infoq.com/news/2026/07/java-news-roundup-jul06-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/java-news-roundup-jul06-2026/en/headerimage/java-news-roundup-image-1783946170119.jpg"/&gt;&lt;p&gt;This week's Java roundup for July 6th, 2026, features news highlighting: the GA release of TornadoVM 5.0; point releases of JHipster, Keycloak and Google ADK; maintenance releases of GraalVM Native Build Tools and Micronaut; the OmniFish Build of Payara and introducing Vidocq, a new implementation of the Jakarta EE 11 Core Profile and MicroProfile 7.1.&lt;/p&gt; &lt;i&gt;By Michael Redlich&lt;/i&gt;</description>
      <category>Keycloak</category>
      <category>OmniFish</category>
      <category>Java</category>
      <category>JDK 28</category>
      <category>TornadoVM</category>
      <category>GraalVM</category>
      <category>Micronaut</category>
      <category>JHipster</category>
      <category>Vidocq</category>
      <category>JDK 27</category>
      <category>Google ADK for Java</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>news</category>
      <pubDate>Mon, 13 Jul 2026 12:40:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/java-news-roundup-jul06-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=global</guid>
      <dc:creator>Michael Redlich</dc:creator>
      <dc:date>2026-07-13T12:40:00Z</dc:date>
      <dc:identifier>/news/2026/07/java-news-roundup-jul06-2026/en</dc:identifier>
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