From Postmortem to Post‑Incident Review: Reframing for a Learning Incident Culture
Incidents happen. How an organization remembers them often determines whether similar problems repeat. The recent shift in language — vendors and teams moving from “postmortem” toward neutral terms like “post‑incident...
GitOps made simple: Deploying apps with Argo CD and OCI registries
GitOps has a rhythm to it: a clean commit, an automated reconcile, and a deployed app that behaves like a well-tuned instrument. Argo CD has been a go-to conductor for...
Intro to Observability as Code: Managing Dashboards with GitOps
Observability as code brings the same benefits we expect from infrastructure as code — versioning, reviewability, repeatability — to dashboards, alerting rules, and other observability configuration. Instead of clicking in...
Making SLOs Sing for Generative AI: SLIs (TTFT/TPOT), SLOs, and SLAs Explained
Generative AI services — chatbots, assistants, code generators — changed the choreography of reliability. Instead of a single uptime percentage, these systems have a rhythm: the first token that shows...
Lightweight Kubernetes at the Edge: Practical patterns for deploying containers closer to users
Edge computing shrinks the distance between users and the services they rely on. For latency-sensitive apps—real-time video, AR/VR, industrial control, or local ML inference—running containers near the data source is...
Keep traffic local: Topology-aware routing and EndpointSlices made simple
Kubernetes networking can feel like a crowded festival: pods are musicians on separate stages (zones), services are the festival promoters trying to route fans (traffic) to the right stage, and...
Pods, Deployments, and Services — how they work together (and why readiness checks matter)
Kubernetes can feel like an orchestra: Pods are the musicians, Deployments are the conductor’s score that tells musicians when to enter and exit, and Services are the stage crew that...
Measuring the Unseen: SLIs, SLOs, and SLAs for Generative AI Services
Generative AI — chatbots, multimodal assistants, code generators — behaves less like a traditional request/response API and more like a live performance: every call has rhythm (tokens per second), tempo...