Grafana + Prometheus on a Raspberry Pi: Build a Telemetry Dashboard That Actuall

<p>A solid observability setup usually comes down to three pieces working together: something that <strong>collects</strong> metrics, something that <strong>exposes</strong>

<h1> Grafana Dashboards for Non-Prod Environment Observability: Cost + Performance in One View </h1> <p>Non-production environments are the most expensive things nobody talks

<p><em>Originally published on <a href="https://kuryzhev.cloud/2026/09/17/alertmanager-routing-fixes-to-cut-prometheus-alert-fatigue" rel="noopener

<p>When building a data-intensive platform, real operational visibility becomes necessary quickly. A core API might be fast, but if event consumers lag or the database strains,

<p>One of our users reached out recently with a familiar problem: search had suddenly become noticeably slower, even though nothing looked obviously broken.</p> <p>The service was

<p><em>Originally published on <a href="https://kuryzhev.cloud/2026/06/23/ai-anomaly-detection-in-grafana-3-mistakes-we-made" rel="noopener noreferrer">kuryzhev.cloud</a></em></p>

<h1> Prometheus Metrics for Your Node.js Circuit Breakers (opossum-prom) </h1> <p>You've added opossum circuit breakers to protect your Node.js app from cascading failures. Good.

<p><strong>Memory is easy. CPU humbled me.</strong></p> <p>With memory, the rule is brutal but clear — cross the limit, the pod gets OOMKilled. Done.</p> <p>CPU? CPU is sneaky.