How to Upgrade to containerd 2.3: First Annual LTS Release with Kubernetes-Aligned Cadence
containerd 2.3.0 introduces the project's first annual LTS release with a new 4-month cadence aligned with Kubernetes. Learn how to upgrade safely.
Red Hat has released OpenShift Service Mesh 3.3, bringing post-quantum cryptography (PQC), AI enablement features, and foundational support for external VM integration. Based on Istio 1.28…
containerd 2.3.0 introduces the project's first annual LTS release with a new 4-month cadence aligned with Kubernetes. Learn how to upgrade safely.
The Kubernetes image promoter (kpromo) underwent an invisible rewrite that deleted 20% of the codebase while dramatically improving speed and reliability.
Kubernetes 1.34 brings Dynamic Resource Allocation to GA, enabling proper GPU sharing, topology-aware scheduling, and gang scheduling for AI/ML workloads.
Cilium celebrates 10 years at KubeCon Europe with CiliumCon 2026, featuring Cilium v1.19, Tetragon security advances, and sessions on multi-cluster networking at scale.
The Kubernetes community announces a new working group focused on developing standards and best practices for AI Gateway infrastructure, including payload processing, egress gateways, and Gateway API extensions for machine learning workloads.
Ollama 0.18 brings official OpenClaw provider support, up to 2x faster Kimi-K2.5 performance, and the new Nemotron-3-Super model designed for high-performance agentic reasoning tasks.
Key portions of the OpenTelemetry declarative configuration specification have been marked stable, including the JSON schema, YAML representation, and SDK operations for parsing and instantiation.
vLLM 0.17 brings PyTorch 2.10, FlashAttention 4 support, and the new Nemotron 3 Super model, delivering next-generation attention performance for LLM inference.
Ollama 0.18.0 is a short release note, but the three visible changes are telling. Better model ordering, automatic cloud-model connection with the :cloud tag, and Claude Code compaction-window control all point to a local runtime becoming a policy layer between local and remote inference.
NVIDIA’s leaderboard-topping NeMo Retriever pipeline is notable not because “agentic retrieval” sounds fashionable, but because the engineering choices are unusually revealing. The interesting story is the tradeoff between generalization, latency, and architecture complexity once retrieval becomes an iterative workflow instead of a one-shot vector lookup.