Free Prometheus Alert Rule and SLO Generator

Tools for Prometheus monitoring: SLO-based PromQL generator, error budget calculator, and scaling to avoid OOMs.

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Alerting

Articles tagged with "Alerting"

Runbook Template

October 30, 2025 Cardinality Cloud 5 min read

Every alert should have a Runbook. (Sometimes called Playbook.) A Runbook is a guide for SREs, DevOps, On-Call engineers, and Software Developers that prescribes potential remediations for specific alerts. The goal is to reduce MTTR and improve incident response with structured troubleshooting, verification steps, and escalation paths for SRE and DevOps teams. A place to build and share knowledge about a potential event.

What is an SLO and why should I use SLO-based alerts?

October 20, 2025 Cardinality Cloud 9 min read

Traditional infrastructure alerts page you when CPU hits 80%, but your users are fine. Meanwhile, degraded API performance goes unnoticed because no arbitrary threshold was crossed. An SLO (Service Level Objective) changes this - it’s a target reliability goal that measures what users actually experience, like “99.9% of requests succeed over 30 days.” Born from Google’s Site Reliability Engineering (SRE) practices, SLO-based alerting only pages when user experience is genuinely at risk, eliminating alert fatigue while catching real issues early.

Why is burn rate alerting useful?

October 18, 2025 Cardinality Cloud 2 min read

Traditional threshold alerts fire on every spike, creating alert fatigue. Burn rate alerting is different - it tracks how quickly you’re consuming your error budget and only alerts when errors are sustained enough to threaten your reliability target. This gives you early warnings before user experience degrades, while dramatically reducing noise.

Understanding SLO-Based Alerting

October 15, 2025 Cardinality Cloud 2 min read

Why does a 5% error rate trigger an alert at 2 AM? Is it catastrophic during peak traffic or meaningless during low usage? Traditional static thresholds can’t tell you. SLO-based alerting asks a better question: “Are we consuming our error budget faster than planned?” This approach ties alerts directly to user-impacting reliability issues, eliminating arbitrary thresholds and reducing alert fatigue while catching real problems early.