OpenTelemetry is best understood as a standard telemetry pipeline: APIs and SDKs create signals, context propagation links work across services, semantic conventions make data consistent, OTLP transports it, Collectors process it, and exporters deliver it to observability backends.
Coding-agent cost is not mainly the price of one clever prompt. It is the recurring cost of moving repository state, tool output, and loop history through paid models until useful work is accepted. Gateway observability makes that spend attributable and governable, while agent-loop discipline determines how much context gets sent.
Tool-using AI agents need more than prompt guidance. If an action can create a real side effect, enforcement should live in executable policy that can allow, deny, stop, or escalate before the tool call happens.
A practical way to distinguish DevOps, Platform Engineering, and SRE by responsibility instead of buzzword: collaboration, paved roads, and explicit reliability ownership.
A practical primer on Kubernetes as a desired-state control system: what pods, deployments, services, ingress, config, secrets, autoscaling, namespaces, and cluster operations actually do, and what they do not do.
A practical, workflow-first guide to Docker and Kubernetes that explains images, registries, runtimes, deployment automation, and the boundaries that keep container systems understandable and secure.
A cloud-native development operating model turns delivery into a paved road for the common case—automated, observable, and governed—while keeping exceptions explicit and reviewable.
Platform engineering vs DevOps isn’t either/or. Use the right operating model for the bottleneck you actually have—ownership and feedback loops for DevOps, and self-service to reduce delivery toil for platform engineering.
Human review in AI workflows works best when you decide what the human actually owns: decide, escalate, or stop—then measure whether the boundary helps.
An agent eval harness is a versioned, scenario-based way to decide whether an agent workflow is safe and acceptable to ship. This guide shows how to design scenarios, golden tasks, trace assertions, and thresholds that stay useful as prompts, tools,