Neocloud Service Delivery Manager

Mirantis has announced that its k0rdent AI platform has been certified through the NVIDIA-Certified Hypervisors programme, validating its performance for high-performance GPU virtualisation for enterprise AI factories and cloud service providers. The Campbell, California-based company demonstrated through benchmarking tests that k0rdent virtualisation delivers near bare-metal performance on NVIDIA GB200 NVL72 and NVIDIA HGX-based validation tracks. Across validation scenarios, the k0rdent AI virtualisation stack achieved performance within 5% of comparable bare-metal deployments whilst providing operational flexibility and tenant isolation required for large-scale AI infrastructure. Mirantis is one of the inaugural independent software vendors participating in the NVIDIA-Certified Hypervisors programme. The platform's topology-aware scheduler understands how GPUs, CPUs, network interfaces, and storage are physically connected, enabling intelligent workload placement whilst avoiding performance bottlenecks.

gVisor Support comes to MCR. Drew Erny - August 05, 2026 Summarize with AI. This new runtime option provides stronger isolation for container workloads, without moving them into virtual machines. Starting with release 29.6.1, Mirantis Container Runtime (MCR) supports gVisor as an OCI runtime. OCI runtimes are the low-level components that create and run containers. MCR uses runc by default and also supports crun. With gVisor, MCR adds a third supported runtime option for teams that need stronger workload isolation without moving those workloads into full virtual machines. That matters because containers are no longer used only as a convenient packaging format for trusted application code. Increasingly, they are part of the infrastructure layer itself. Service providers use Mirantis software to build public cloud and managed cloud services where customer workloads may arrive from many sources and run on shared infrastructure. Enterprises build private clouds that serve many internal business units, application teams, and development groups, each with different security practices, maturity levels, and operational requirements. For communications service providers, containerized network functions and cloud-native network functions may run on shared infrastructure that handles traffic or control-plane data for many customers. gVisor does not secure those streams inside the workload, but it can help reduce the risk that a compromised container escapes to the shared host or affects neighboring workloads. AI cloud providers and enterprise AI platforms must keep tenant workflows, models, prompts, embeddings, and datasets isolated even when GPUs, storage, and cluster infrastructure are shared. In these environments, stronger runtime isolation is not just a defense-in-depth feature. It is part of the platform trust model. Operators need ways to reduce the risk that a compromised, misconfigured, experimental, or simply unknown container workload can expose the host, affect neighboring workloads, or reach sensitive infrastructure services. gVisor gives MCR users another tool for making those risk-based placement decisions: run workloads that need stronger isolation with gVisor, while continuing to use runc or crun where standard container behavior, compatibility, or performance characteristics are the better fit. gVisor is designed to improve container security by placing an additional isolation layer between the application and the host operating system. It acts as an application kernel: a user-space runtime that implements a Linux-like interface for containerized applications while reducing the host-kernel surface exposed to those applications. This gives operators a middle path between standard container isolation and full VM isolation. That makes gVisor especially useful for environments where containers may run less-trusted, externally supplied, or multi-tenant workloads. In many cases, it can be used as a drop-in replacement for the default runtime, allowing existing container workflows to stay largely unchanged while adding an extra security boundary. As with any sandboxing technology, gVisor involves tradeoffs. Because it intercepts and handles system calls differently from a standard Linux container runtime, syscall-heavy or performance-sensitive workloads may see additional overhead. There are also compatibility considerations: gVisor implements a large portion of the Linux system interface, but not every syscall or kernel feature is fully supported. Most common applications and language runtimes work well, but operators should test workloads with specialized kernel, filesystem, networking, device, or performance requirements before adopting gVisor broadly. MCR can use multiple OCI runtimes on the same machine, so you do not need to choose one runtime for every workload. You can run security-sensitive workloads with gVisor and continue using runc or crun where compatibility or performance characteristics make them a better fit. Get started. For installation and configuration instructions, see the MCR documentation for using gVisor as an alternative container runtime. The docs include the current package names, supported operating systems, repository setup requirements, and runtime configuration steps. The leading, fully-supported secure Container Runtime. If your container applications require exceptional compatibility, reliability, and security, learn more about MCR, the leading fully-supported enterprise container runtime or contact Mirantis.

Azul announces monthly Critical Security Patch Updates for Java across all supported LTS versions. July 23, 2026 Azul announced that it will deliver monthly Critical Security Patch Updates (CSPUs) for Java Long-Term Support (LTS) versions for both Azul Core and Azul Prime, starting in August 2026. The traditional quarterly update cadence can no longer keep pace, as a serious vulnerability surfacing just after a scheduled update can sit unpatched for weeks before the next fix ships. Azul is moving to a monthly rhythm to close that exposure window, delivered with the production-grade stability enterprises depend on. Azul's CSPUs will be released monthly, on the third Tuesday of each month, when a high-priority fix is warranted, giving organizations a predictable, plannable security cadence rather than waiting for the next quarterly update. Azul will provide CSPUs across all the LTS versions it supports - Java 8, 11, 17, 21 and 25 - as well as the current release (Java 26). Azul will also deliver CSPUs for the Java 6 and 7 versions it supports, extending the same monthly security cadence to organizations still running older Java versions in production. Azul brings a proven model to this faster cadence. For years, it has delivered Java updates in two forms each quarter: Patch Set Updates (PSUs), which carry the full set of quarterly changes (typically measured in the hundreds), and Critical Patch Updates (CPUs), which deliver security fixes only, built on a stabilized, production-proven code base. Azul's CSPUs extend that same security-only, stability-first CPU model to a monthly rhythm - targeted fixes for identified vulnerabilities tracked as Common Vulnerabilities and Exposures (CVEs), without the unrelated changes that raise regression risk. Azul will continue to work within the OpenJDK community and the OpenJDK Vulnerability Group to advance Java security. "For years, the world's most demanding enterprises have trusted Azul to deliver security and stability together, and on time," said Scott Sellers, co-founder and CEO of Azul. "As AI sharply increases the volume of threats enterprises face, enterprises shouldn't have to choose between the two. Monthly security-only updates are the new standard Azul is setting for how enterprises protect their Java estates." Industry news. July 23, 2026 Azul announced that it will deliver monthly Critical Security Patch Updates (CSPUs) for Java Long-Term Support (LTS) versions for both Azul Core and Azul Prime, starting in August 2026. July 23, 2026 Prismatic announced native large data sync, a set of new capabilities that enables teams to move high volumes of customer data through the same integration platform they already use to build, deploy, monitor, and manage customer-facing integrations. July 23, 2026 Harness and Kong announced an expansion of their strategic partnership to address the growing security challenges posed by AI-driven architectures, autonomous agents, and Model Context Protocol (MCP) deployments. July 22, 2026 Sauce Labs introduced AURA, its AI-Unified Release Assurance platform, to close that gap. July 22, 2026 Harness announced the Harness AppSec Alliance, a strategic partner ecosystem that brings together application security, API and Agent security capabilities on a single platform. July 22, 2026 Mirantis announced that both k0s, its lightweight single-binary Kubernetes distribution, and k0rdent, its open-source distributed container management platform, have achieved CNCF Certified Kubernetes AI Conformance at Kubernetes v1.35. July 21, 2026 Google introduced Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber to help developers and customers build AI agents in production with higher token efficiency, lower latency, and reliable performance. July 21, 2026 Harness is extending its platform to cover the full AI Agent Development Lifecycle (DLC), giving enterprises a single set of pipelines and controls to build, test, deploy, and run agents the same way they already ship everything else. July 21, 2026 BellSoft announced the general availability of a new hardened builder image for Paketo Buildpacks(TM). July 20, 2026 Testlio unveiled the next evolution of its AI-driven testing platform, LeoCore(TM). July 20, 2026 Agent Island released v1.7.1. July 17, 2026 GitLab(link is external) released GitLab 19.2. As AI generates more code, dependencies, and change than developers can keep up with, GitLab 19.2 brings agentic automation to clear that load. July 16, 2026 Progress Software(link is external) announced that its Progress Chef(link is external) platform now delivers enterprise lifecycle management and configuration capabilities for NVIDIA DGX Spark, enabling IT teams to securely provision, monitor and manage the desktop AI supercomputer at scale. July 16, 2026 Atlassian Corporation announced new capabilities in Jira to advance AI-native software development for every engineering organization. July 16, 2026 Intruder announced the launch of AI Pentesting for web applications, providing on-demand penetration testing.