Kepler maintainers rewrote Kepler to remove eBPF. They replaced privileged kernel tracing with read-only Linux process data to attribute energy use to Kubernetes workloads... read more  

Kubernetes maintainers accept AI-assisted contributions when contributors disclose AI use, understand the code, and own the change. Maintainers test AI review tools to help them sort issues and pull requests... read more  

A blog post by Mesut Oezdil, a DevOps Engineer from Buoyant, discusses how Linkerd's proxy provides network layer metrics with zero changes to application code. The post showcases the overlap and differences between mesh-derived metrics and OpenTelemetry metrics, along with the integration pattern t.. read more  

Headlamp is an open-source, extensible Kubernetes SIG UI project designed to let you explore, manage, and debug cluster resources directly from a browser. Cluster API (CAPI) is a Kubernetes sub-project that brings declarative, Kubernetes-style APIs to cluster lifecycle management. It lets platform t.. read more  

The shift from RNNs totransformerssolved sequential bottlenecks and long-range decay issues withself-attention. Transformers use encoding, decoding, and tokenization to process sequences efficiently and accurately. This evolution led to models like GPT, which excel at tasks with minimal fine-tuning .. read more  

After a head-to-head coding test, you can use GLM-5.2 as a low-cost open-weights coding model and choose Opus when you need stronger correctness, faster responses, or visual self-checking... read more  

Teams create prompt debt when they hand-tune prompts. They turn natural-language instructions into fragile specs, spend more time adjusting wording, and tie the application to one model... read more  

Cisco executives plan to acquire WideField Security so Cisco teams can add identity and session telemetry to agentic AI security operations... read more  

The AI platforms are running the drug-dealer's algorithm, with subsidies resulting in overwhelming demand for their products. Estimates show that the cost of generating tokens ranges from $8 to $14 to generate $1 in revenue. Companies transitioning to token-based pricing have seen significant increa.. read more  

Token generation speed is constrained by the speed at which the relevant HBM can be read, depending on model size and pipeline setup. Model sizes feasible for each year between 2023 and 2031 range from 10T in 2026 to 1.4 quadrillion in 2031, with pretraining compute and HBM specifications playing es.. read more