GPU Cost Attribution on Kubernetes: Bill on Memory, Not Compute
GPU cost attribution on Kubernetes breaks once pods share a GPU: DCGM can report 300% use. Why platform teams should split the bill on memory, not compute.
Amazon ECS GPU Auto Repair: How It Replaces Failing GPUs
Amazon ECS Managed Instances now swap out failing NVIDIA GPU hosts automatically. How the DCGM checks, Xid codes, and 20% drain cap shape AWS GPU reliability.
The Definitive Guide to Building an AI Factory on Kubernetes for Platform Teams
One GPU fleet, many teams, strict isolation: how to architect multi-tenant AI infrastructure on Kubernetes without hiding the data path behind a leaky abstraction.
How to Implement Predictive Autoscaling for GPU Workloads on Kubernetes
Reactive autoscaling can't keep up with GPU provisioning delays. This framework uses a Bi-LSTM predictor, burst detection, and a graduated scaler to close the gap.
Amazon EC2 at 20: From One Instance Type to 1,200 and What Comes Next
Amazon EC2 launched in 2006 with one instance type. At 20, it offers 1,200+ types and anchors an AI compute infrastructure its founders never anticipated.
Adobe Firefly Cut GPU Metric Query Times 28x by Moving to Amazon Managed Prometheus
Adobe moved 2 million GPU time-series metrics from self-hosted Prometheus to Amazon's managed service. 24-hour queries that took 2 minutes now complete in 10 seconds — and the team got there without replacing their existing stack.
Bedrock AgentCore Runtime Instances: Persistent Compute for Production AI Agents
AWS launched runtime instances in Bedrock AgentCore — managed EC2 infrastructure with GPU support, multi-agent collaboration, and sessions lasting up to 14 days for long-running agent workflows.
Kubeflow + Cilium: Why Your GPUs Sit 60% Idle
GPUs sat at 40% utilization while fully scheduled: a hidden Cilium network policy was silently blocking Kubernetes gradient sync.
Goodput, Not Throughput, Is the Right Metric for LLM Serving
A CNCF benchmarking study shows one configuration hit 50% more throughput while degrading user experience 10x. The metric you're optimizing for is probably wrong.
AWS Proves VM Isolation With 330,000 Lines of Mathematical Proof
Graviton5's Nitro Isolation Engine is the first formally verified cloud hypervisor — mathematical proof replaces test-based assurance for VM isolation.
GPU Autoscaling on Kubernetes with KEDA: Why CPU Metrics Fail AI Inference Workloads
KEDA's GPU external scaler reads VRAM and compute utilization via NVML, enabling scale-to-zero for AI inference pods — a different model than CPU-based Kubernetes HPA.
Mac Mini: The Accidental Infrastructure Platform for AI Agents
Three independent AI agent runtimes converged on Mac mini as reference hardware. What happens when a $600 desktop becomes the default agentic AI server.
CNCF Fluid: Cutting LLM Cold Start on Kubernetes from 42 Minutes to 30 Seconds
CNCF Fluid reduces LLM cold start on Kubernetes from 42 minutes to 30 seconds via prefetching and elastic cache, with no code changes required.
Meta's AWS Graviton5 Deal: Why Agentic AI Runs on CPUs, Not Just GPUs
Meta's multibillion AWS Graviton5 deal — tens of millions of cores — reveals why agentic AI inference is fundamentally CPU-intensive, not GPU-intensive.
Google TPU 8: Why the Agentic Era Required Two Chips Instead of One
Google split its TPU line for the first time at Cloud Next 2026: TPU 8t for training and TPU 8i for low-latency inference. The bifurcation signals that agentic workloads need fundamentally different silicon.
Vultr Claims AI Infrastructure 50-90% Cheaper Than AWS
Vultr claims AI compute costs 50-90% less than AWS on equivalent Nvidia hardware. Here's what the pricing comparison reveals for cloud platform teams.