Thought Leadership
Building observability in large-scale, cloud-native systems requires collecting telemetry data (metrics, traces, and logs) at extremely high volumes. Modern platforms like Kubernetes can generate millions of metrics, traces, and log events per second, and enterprises often must handle this flood of telemetry across hybrid environments (on-premises and cloud). Designing a
How To
Goal: Spin up Prometheus+Alertmanager, Loki+Promtail, Jaeger, and Grafana with a single docker‑compose.yml, then watch a tiny Java HTTP service emit metrics, logs, and traces—all in less than an hour. Why this post? You keep hearing that “observability ≠ monitoring” and that you need metrics, logs, and
Tooling Deep-Dives
OpenTelemetry’s Collector is a vendor-neutral service that sits between your applications and observability backends. It can receive telemetry data (traces, metrics, logs), process or transform it, and export it to one or multiple destinations. In a production environment, the Collector becomes essential for building a flexible and resilient observability
OpenTelemetry Corner
OpenTelemetry (OTel) has quickly become a cornerstone of modern observability. If you’re a developer or engineer looking to instrument your applications for better insight, this beginner’s guide is for you. I’ll explain what OpenTelemetry is, why it matters, and walk through a step-by-step tutorial to instrument a