Writing on Developer Experience, Cloud Native, AI and more.

How idle and abandoned computational jobs are consuming GPU capacity and power in data centers, undermining efficiency efforts at a time when AI infrastructure investment is at an all-time high.

An interview on Kubernetes' In-Place Pod Resize feature: how it tackles resource over-provisioning, reduces cloud costs, and what the ecosystem still needs to make dynamic resource scaling truly seamless.

Throughput tells you how many requests your LLM serving stack processes per second. Goodput tells you how many of those actually met your latency targets. The gap between them is where your real performance story lives.

GPU utilization for LLM inference often sits as low as 5%, yet most teams respond by buying more hardware instead of tuning what they already have. Learn why the real bottleneck is configuration, not capacity, and how to unlock 2x throughput from existing GPUs.

Break the FinOps/SRE/Developer friction by transforming optimization into an automated, invisible platform capability. Achieve continuous cost and performance balance through GitOps.

A first look at survey data from 133 contributors across nearly 100 CNCF projects, revealing how AI tools like Claude Code and GitHub Copilot are reshaping open-source workflows and why governance policies haven't kept pace.

FinOps wants savings. SREs want reliability. Developers just want to ship. See how Akamas Insights aligns teams around one shared view of Kubernetes efficiency.

Design an edge observability pipeline using OpenTelemetry and Fluent Bit to capture, sample, and reliably process telemetry under strict bandwidth limits.

Cloud native optimization 2026 explores trends, challenges, and gaps in Kubernetes, FinOps, and platform engineering.

Stop treating cloud efficiency as a quarterly cleanup. Learn how to transform optimization into a core platform capability by bridging the gap between SRE reliability and FinOps goals.