Teams running Spot-heavy Kubernetes configurations save 77% on compute on average, compared to 59% for mixed fleets, according to the 2025 Cast AI Kubernetes Cost Benchmark. AWS gives a 2-minute inter…
Google Cloud announced that Filestore, its first-party NFS file service, now incorporates a cloud-native backend storage layer built directly on Colossus, Google's foundational distributed storage sys…
An engineer at ZopNight ran a week-long experiment giving an AI agent read-only access to AWS and GCP accounts with a single prompt: 'Cut our cloud bill by 20% without breaking anything.' The agent id…
Google Cloud announced the general availability of Managed Lustre, a high-performance storage solution powered by DDN's EXAScaler, offering throughput from 125 MB/s to 1000 MB/s per TiB and scaling up…
Kong's AI Gateway, running on GCP, extends traditional API gateways with token-aware traffic management, Model Context Protocol (MCP) support, and governance for agentic traffic. The solution addresse…
GPU utilization across production Kubernetes clusters averages just 5%, yet half of GPU cloud providers surveyed by SemiAnalysis report being completely sold out of H100 and H200 capacity, according t…
Ray 2.55 makes Google Cloud TPUs a first-class accelerator, with official pre-built images and support across core libraries. The distributed-computing framework now treats TPU slices as schedulable r…
Modelplane released v0.2 of its open-source inference orchestration platform, adding support for Nebius and Azure AKS cloud providers, weighted request routing for canarying and traffic splitting, and…
A new Kubernetes cost optimization checklist reveals that average CPU utilization across production clusters is only 8% in 2026, down from 10% the prior year, with 69% of clusters over-provisioning CP…
Autonomous AI engineer agents are industrializing inefficient infrastructure patterns at scale because their specifications lack sustainability constraints, leading to over-provisioned clusters and ov…
Karpenter, an open-source node provisioner, directly provisions cloud instances without node groups, while Cluster Autoscaler scales pre-defined node groups. Karpenter is faster, cheaper, and more fle…
A developer built an AI agent skill for the Antigravity CLI that migrates applications from AWS to GKE. The agent scans cloud dependencies, spawns parallel subagents to refactor code and infrastructur…
Agent Substrate, a new platform for running AI agents, reduces idle agent costs by 90% compared to traditional Kubernetes Pod deployments. By using an actor model with checkpoint/restore and gVisor, i…
A developer built an end-to-end AI-SRE system using HolmesGPT, mirrord, and a Claude wrapper to autonomously verify fixes on a real GKE cluster. The system investigated a checkout error, generated a c…
Google released OpenRL, an open-source API for fine-tuning large language models on Kubernetes clusters, aiming to decouple infrastructure from AI research and improve GPU utilization by running multi…
Pydantic Logfire launched a new Kubernetes cluster view that surfaces pod restart loops, memory limits, and rollout failures from a single page. The feature uses standard OpenTelemetry receivers to ag…
An engineer proposes treating prompt engineering for site reliability engineering (SRE) workflows as reusable infrastructure, introducing three production-tested patterns: structured context injection…
Google Cloud demonstrated a multi-cluster inference setup deploying an LLM across two regional GKE clusters using TPU v6e accelerators and GKE managed DRANET for networking. The experiment, documented…
A developer detailed how to build interrupt-resilient AI workloads on Google Kubernetes Engine (GKE) by handling Spot VM evictions. The approach involves catching the SIGTERM signal sent by Kubernetes…
Google engineers deployed a Gemma 3 large language model across two GKE clusters in separate regions, using four TPU v6e chips per cluster, to test multi-cluster failover with the Inference Gateway. T…