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325 ARTICLES

How the CIO of Unilever delivers business empathy
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How the CIO of Unilever delivers business empathy

In this week’s Computer Weekly, we talk to Unilever’s global CIO about empowering people to innovate – from IT departments to entrepreneurial women in India. We analyse the arguments for and against the NHS’s controversial Federated Data Platform project. And veteran IT leader Paul Coby shares his top tips for business success. Read the issue now.

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Java News Roundup: Value Objects, WildFly 41, TornadoVM, LangChain4j, Oracle AI Agent Studio
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Java News Roundup: Value Objects, WildFly 41, TornadoVM, LangChain4j, Oracle AI Agent Studio

This week’s Java roundup for July 13th, 2026, features news highlighting: a reintroduction of Value Objects (Preview); the GA release of WildFly 41; the July 2026 edition of Open Liberty 26.0.0.7; point releases of TornadoVM, Apache TomEE, Java Operator SDK and LangChain4j; a maintenance release of Micronaut; a new extension, Quarkus Shim; and a new Oracle AI Agent Studio for Fusion Applications. By Michael Redlich

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Accelerating automotive innovation with C4A-metal and Panasonic Automotive vSkipGen
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Accelerating automotive innovation with C4A-metal and Panasonic Automotive vSkipGen

As the automotive landscape accelerates toward software-defined vehicles, Cockpit Domain Controllers (CDCs) are becoming the core of next-generation in-cabin experiences. The ability to rapidly develop, test, and validate CDC software in a flexible, hardware-independent environment is critical for innovation and time-to-market. However, physical hardware constraints and the requirement for high-performance graphics present significant challenges for global development teams. Panasonic Automotive’s vSkipGen™ addresses these challenges as a next-generation CDC virtualization platform, now validated on Google Cloud’s C4A-metal, our Axion bare-metal offering. By integrating Panasonic Automotive’s advanced Unified HMI™ remote GPU offload technology with support for Android Automotive OS (AAOS) and Android SDV, vSkipGen delivers a robust, cloud-native solution for cockpit software development and validation — empowering teams to innovate without hardware limitations. At Google Cloud, we provide workload-optimized infrastructure to help ensure the right resources for every task. Similar to the entire Axion virtual machine family, C4A-metal instances are built on Google Cloud’s custom Arm-based Axion architecture. C4A-metal offers 96 vCPUs, two DDR5 memory configurations (384GB and 768GB), and up to 100Gbps of networking bandwidth. It also provides full support for Google Cloud Hyperdisk, including Balanced, Extreme, Throughput, and ML types. And like the rest of the bare metal portfolio, C4A-metal is powered by Titanium, a key component for multi-tier offloads and security that is foundational to our infrastructure. High performance for demanding workloads C4A-metal is particularly well-suited for complex tasks such as creating digital twins of vehicle cockpits where performance must accurately mirror real-world behavior. Traditionally, the transition to software-defined vehicles has relied on expensive and scarce physical prototypes; C4A-metal overcomes this by offering the high performance and hardware-level access of bare metal with the scalability of the cloud. Panasonic Automotive leverages C4A-metal to bypass traditional hardware bottlenecks, enabling their teams to execute complex virtualization tasks and accelerate the development of next-generation cockpit software. “Google Cloud’s Axion Bare Metal has been a game-changer for our vSkipGen™ platform. By providing scalable, high-performance Arm-based infrastructure, C4A-metal allows our teams to develop and test production-intent software in the cloud with behavior that closely matches target automotive hardware. This cloud-to-car bit parity reduces dependence on costly physical prototypes, improves validation efficiency, increases test coverage and accelerates time-to-market for next-generation cockpit platforms.” - Andrew Poliak, CTO, Panasonic Automotive Systems America. By leveraging vSkipGen and Unified HMI on C4A-metal, automotive manufacturers can now build, test, and validate full AAOS stacks in a hardware-independent, cloud-native environment, moving from physical dependency to scalable digital twins. Figure 1: Unified HMI solution overview How vSkipGen works: Virtualizing the cockpit with Cuttlefish Panasonic Automotive’s vSkipGen acts as a digital twin for physical CDC hardware. To provide a hardware-agnostic environment for Android virtual machines, vSkipGen uses components of Android Cuttlefish. At its core, vSkipGen leverages a cloud-optimized Virtual Machine Monitor (VMM) built on crosvm (the open-source, security-focused VMM originally developed for Chrome OS) which utilizes Linux KVM (Kernel-based Virtual Machine) for hardware-assisted virtualization. The VMM backend is implemented in Rust for enhanced security, scalability, and performance. By running the full stack on C4A-metal (see Figure 2), Panasonic lets developers boot a full AAOS image in the cloud, which behaves exactly like the software running in a physical vehicle. The platform virtualizes all essential peripherals, such as the audio, GPU, sensors, cameras, Controller Area Network (CAN), Bluetooth, and Wi-Fi, using the VirtIO standard. This VirtIO-native approach allows developers to interact with the virtual devices exactly as they would with the physical hardware. Furthermore, vSkipGen seamlessly connects with automotive simulators and software-in-the-loop (SiL) environments for comprehensive scenario and edge-case validation, enabling teams to conduct software validation and run automated test suites without needing early access to physical prototypes. Figure 2: vSkipGen Cockpit virtualization architecture Figure 3: Remote GPU rendering flow Accelerating graphics on the go with Unified HMI High-performance graphics is central to the modern driving experience, but rendering it in a virtual environment can be challenging. Panasonic’s Unified HMI solves this by decoupling HMI rendering from specific hardware. A lightweight Unified HMI component operates outside the VM to offload OpenGL ES commands (the specific data being rendered) from the Cuttlefish instance to GPU-equipped compute resources on Google Cloud, which handle the workloads with hardware acceleration. The rendered UI is then streamed to any standard browser using low-latency WebRTC. This helps ensure that global development teams can experience high-fidelity visuals in real time, regardless of their location. Unified HMI establishes a unified virtual display layer across multiple Electronic Control Units (ECUs) and virtual machines, allowing applications to render to different displays from anywhere within the system. Benefits for software-defined vehicle development With C4A-metal and Panasonic Automotive’s vSkipGen, manufacturers building software-defined vehicles can: Build and validate AAOS-based software in the cloud using Cuttlefish before physical hardware is available Use industry-standard VirtIO to emulate critical CDC devices for robust, production-grade validation Stream interactive cockpit experiences to any browser to support distributed engineering teams Run multiple isolated CDC instances in parallel to support large-scale automated testing and CI/CD pipelines Reduce cost and environmental impact by minimizing the need for expensive physical hardware prototypes, supporting sustainable development practices Enjoy a future-ready architecture built on open standards, crosvm, and Rust for enhanced security, performance, and long-term adaptability Get started C4A-metal is generally available worldwide; please refer to the public documentation for additional information. Panasonic Automotive’s vSkipGen with Unified HMI for Google Cloud will soon be available for evaluation access. To explore how these solutions can help you speed up cockpit software development, contact the team at vSkipGenSupport@panasonicautomotive.com. Disclaimer All trademarks, tradenames, and service marks used herein are the property of their respective owners.

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Making highly available, multi-region Cloud Run services just got easier
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Making highly available, multi-region Cloud Run services just got easier

Application downtime for mission-critical services can directly impact your reputation and bottom line. To avoid that, you need to be able to deploy regionally resilient workloads that detect and automatically recover from failures. But setting up multi-region, highly available deployments often involves complex configurations, and responding to incidents or outages is usually a manual process. Multi-region services on Cloud Run provide a one-command approach to deploying the same service configuration across multiple regions. When deployed with a global external application load balancer, you can serve traffic from different regions. Now, we’ve made it easier to detect regional service disruptions and automatically fail over to a healthy region within seconds with new capabilities: Readiness probes provide instance-level health checks for your Cloud Run service to determine exactly when your containers are ready to serve traffic. You can also use these probes to monitor how many healthy or unhealthy instances exist for your service in each region. Service health aggregates instance-level health checks from readiness probes to calculate the health of your service in each region. This aggregate health is exposed via serverless network endpoint groups (NEGs) in each region. When your service is connected to a global application load balancer, traffic automatically fails away from regions with unhealthy services. Service health can be used with both single and multi-region services. Let’s take a closer look at some scenarios where these new capabilities can come in handy. Use cases To make your Cloud Run applications highly available, it is essential to minimize the downtime for each incident. In high availability scenarios, readiness probes can help you detect regional service failures and automatically fail over, minimizing service degradation or disruptions. To achieve automated failover, one key thing to consider is whether you plan to support application traffic from the public internet or from within your private network (VPC). Public internet applications: When you have a public-facing website or API, configure Cloud Run with a global external application load balancer for automatic detection and failover capabilities. Private network applications: When you have private applications with internal traffic, configure Cloud Run with a cross-regional internal application load balancer for automatic detection and failover capabilities. Design Considerations Cloud Run’s new service health excels at quickly detecting and recovering outages in active-active configurations, where two or more regions are actively configured to serve traffic. Some things to consider when designing your multi-region setup: Single points of failure: As you design your application, ensure that each layer of your application, including your database layer, has regional redundancies to avoid any single points of failure. For three-tiered applications on Cloud Run, consider setting up your web tier and application tier with distinct multi-region architectures to handle public internet and private networking respectively. Data replication: When replicating data across regions and evaluating your recovery point objective (RPO), consider whether you require zero data loss. Cloud Run service health works best with read- and write-heavy applications that actively synchronize data across regions. Data residency: Google Cloud offers several multi-region database configurations with managed multi-region solutions including Firestore, Spanner, Cloud Storage, and Cloud SQL. These all work great for multi-region architectures on Cloud Run that have strict data sovereignty requirements. Get started Cloud Run’s enhanced multi-region high availability services are currently available in all Cloud Run regions at no additional cost. You only pay for the standard CPU and memory required to run the readiness probes. To learn more, check out our documentation.

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DoorDash Uses Envoy and Valkey for a 1.5M RPS Proxy Cache with 99.99999% Availability
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DoorDash Uses Envoy and Valkey for a 1.5M RPS Proxy Cache with 99.99999% Availability

DoorDash has developed Entity Cache, a transparent proxy caching platform built on Envoy and Valkey to reduce redundant service-to-service requests across its microservices architecture. Operating within DoorDash’s service mesh, the platform serves over 1.5M requests per second with 99.99999% availability through caching, event-driven invalidation, failure handling, and performance optimizations. By Leela Kumili

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Three InfoQ Certification Cohorts Start This August: Meet the Facilitators
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Three InfoQ Certification Cohorts Start This August: Meet the Facilitators

InfoQ has opened enrollment for three five-week online certification cohorts starting in August, each led by a senior practitioner applying QCon talk frameworks to participants’ own work: architecture with Luca Mezzalira, engineering leadership with Michelle Brush, and AI security and privacy with Katharine Jarmul. By Artenisa Chatziou

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