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The Hidden Cost of “Just Works” Load Balancing in a Service Mesh
If you’re running a multi-AZ Kubernetes cluster with a service mesh on top, there’s a good chance you’re paying a tax you never signed up for, and it won’t show up as ...
How We Cut Kubernetes Deployment Validation From 45 Minutes to 2 minutes
There is a moment every release engineer knows well. The CI/CD pipeline turns green. The deployment job reports success. Everyone exhales for a second and thinks, “Okay, the release is done.” But ...
Docker Desktop Gets a Hypervisor of its Own
Docker is bringing full backend parity across all of its Docker Desktop editions, ensuring that macOS, Windows, and (eventually) Linux users get the same performance and polish. The company unveiled a new ...
Kubernetes Wasn’t Built for GPUs. Make It Behave
Kubernetes counts whole GPUs and treats pods as disposable. An LLM pod is neither. Share the silicon with MIG/MPS/time-slicing and stop paying for idle ...
Sneha Gullapalli | | A100, AI infrastructure, AI Workloads, cloud native AI, Dynamic Resource Allocation, GPU autoscaling, GPU cost reduction, GPU optimization, GPU partitioning, GPU sharing, GPU time-slicing, GPU utilization, H100, Karpenter, KServe, Kubernetes DRA, Kubernetes GPU scheduling, LLM Inference, model caching, multi-instance GPU, NVIDIA GPU Operator, NVIDIA MIG, NVIDIA MPS, scale-to-zero, VRAM
How Open-Source Automation Tools Handle the Testing Problem That Cloud-Native Independent Deployment Creates
Independent deployment creates a coverage currency problem manual maintenance cannot scale to address. Learn how open-source automation tools handle it structurally. ...
Sancharini Panda | | API mocking, behavioral drift, CI/CD testing, Cloud-Native Testing, contract testing, coverage currency, eBPF, go-vcr, independent deployment, integration test fixtures, integration testing, Keploy, Kubernetes testing, Microcks, microservices testing, open-source automation tools, Pact, platform engineering, record and replay testing, service dependencies, test automation, Testcontainers, VCR, VCR.py, WireMock
Stop Treating GPUs Like Web Pods
Kubernetes schedules accelerators as opaque integers, and your bill pays for it. Share the silicon, scale on the right signal and keep weights out of the image ...
Veera Ravindra Divi | | AI infrastructure, AI serving, autoscaling, cloud costs, cloud native AI, DCGM exporter, DRA, Dynamic Resource Allocation, GPU costs, GPU scheduling, GPU sharing, GPU utilization, GPUs, inference workloads, KEDA, kubernetes, Kubernetes GPU scheduling, LLM Inference, MIG, model weights, MPS, NVIDIA GPUs, NVIDIA MIG, Prometheus, scale-to-zero, time-slicing
Kubernetes Key Management Streamlined by HashiCorp Vault Plug-In
IBM HashiCorp has released a plug-in that allows Kubernetes clusters to use HashiCorp’s Vault Enterprise as an external key management service (KMS), eliminating the need to store unencrypted passwords or bog Kubernetes ...
The Telemetry Debt Crisis: Why Cloud-Native Teams are Optimizing the Wrong Metric
Telemetry debt is overwhelming engineering teams with noisy alerts, unused dashboards and rising observability costs. Here’s how to identify, reduce and prevent it ...
David Iyanu Jonathan | | adaptive sampling, AI observability, alert fatigue, dashboard sprawl, eBPF observability, FinOps, incident response, log management, metric cardinality, MTTR, observability as code, observability costs, observability maturity, observability strategy, OpenTelemetry, platform engineering, telemetry governance, telemetry ROI, trace data
A Green Kubernetes Deployment Does Not Mean a Healthy Application
The deployment finishes, kubectl rollout status reports success, and every pod shows Running and Ready. For most teams, that is the moment the release is considered done. Then a customer transaction fails ...
NVIDIA Is Putting Real Skin in the Open AI Game
Open AI requires community-governed infrastructure and companies willing to contribute code, engineering and costly GPU cycles. NVIDIA is doing exactly that ...

