23 articles
Honest hands-on review of Kubecost and OpenCost for Kubernetes cost allocation. What each tool actually does, installation via Helm, free tier limits, and when to pay for Kubecost.
Honest comparison of Hetzner, AWS, and DigitalOcean for DevOps teams. Real pricing for a 3-node Kubernetes cluster, what you give up with Hetzner, and when each platform is the right choice.
How to control LLM costs at scale — token counting, prompt compression, semantic caching with Redis, tiered model routing, and cost attribution dashboards. Python code included.
A detailed comparison of Cloudflare R2, AWS S3, and Backblaze B2 for object storage in 2026 — pricing, egress fees, S3 compatibility, performance, and which one wins for each use case.
Automatically detect unusual cloud cost spikes, identify the cause, and get an AI-generated explanation and recommended fix using Claude API and Prometheus metrics.
One Anthropic API key, ten teams using it, one bill at the end of the month with no idea who spent what. Here's how to attribute LLM costs per team, per feature, and per customer so finance can actually chargeback.
OpenCost is the open source CNCF project; Kubecost is the company that built it, offering a paid product on top. Here's what you actually get with each, and when the free tier stops being enough.
Reactive autoscaling fixes problems after they happen. Build a forecasting tool using Facebook's Prophet library on historical Prometheus metrics to predict capacity needs days ahead — before traffic spikes hit.
Your Kubernetes cluster is probably wasting 40-60% of its compute cost on over-provisioned resources. Build an AI-powered cost optimizer that reads Prometheus metrics and gives specific rightsizing recommendations.
Cloud costs spike without warning. Build a Python bot using AWS Cost Explorer + Claude API that detects anomalies using Z-score analysis and explains the spike in plain English.
FinOps keeps showing up in job descriptions and team meetings. Here's what it actually means, what DevOps engineers need to know about it, and practical techniques to implement it.
Use AI to automatically analyze your Kubernetes resource usage, detect waste, and generate optimization recommendations. Full Python project with Claude API.
Before you run terraform apply, wouldn't you want to know how much it'll cost? Build an AI cost estimator that reads your Terraform plan output and gives you a detailed cost breakdown using Claude as the reasoning engine.
AWS Cost Anomaly Detection catches spikes but gives no context. Build a system that detects anomalies, uses Claude to explain what caused them, and posts actionable Slack alerts with a fix recommendation.
Build an AI-powered bot that analyzes your Kubernetes cluster, finds idle resources, oversized pods, and unused namespaces — and gives cost-cutting recommendations.
Karpenter replaces Cluster Autoscaler with faster, more cost-efficient node provisioning. Learn architecture, NodePools, disruption budgets, Spot integration, and production best practices.
Everything you need to know about Kubernetes VPA. Covers installation, recommendation modes, right-sizing strategies, VPA vs HPA, and production best practices for resource optimization.
How to use AI and machine learning for Kubernetes capacity planning. Covers predictive autoscaling, cost optimization, tools like StormForge and Kubecost, and building custom ML models for resource forecasting.
How AI and LLMs are being used to analyze cloud spending, right-size resources, detect waste, and automate cost optimization across AWS, GCP, and Azure in 2026.
Cloud vendors are raising prices due to AI infrastructure costs. Here's a practical FinOps guide with specific strategies to cut your cloud bill by 30-50% in 2026.
NVIDIA has dominated GPU computing in Kubernetes for years. But AMD, Intel, and custom accelerators are breaking that monopoly. Here's why GPU diversification is inevitable.
Cloud costs are out of control at most companies. FinOps is the discipline that fixes it — and DevOps engineers are the most important people in any FinOps implementation. Here is everything you need to know.
Running Kubernetes in production can get expensive fast. Here are 10 battle-tested strategies to cut your K8s cloud bill by 40–70% without sacrificing reliability.