Observability Stack Audit

You have dashboards nobody trusts, alerts that fire at 3 AM for no reason, and a Loki bill that keeps climbing. The stack works, technically. But it is not working for your team.

This mission is a full-stack audit: ingestion pipelines, query performance, retention policies, label cardinality, and alert quality. I map what you have, find what is broken or wasteful, and hand you a prioritized fix list with impact estimates.

What's included

• Ingestion audit: pipeline mapping (Vector/Alloy/Promtail), label cardinality analysis, identify hot paths and silent drops
• Query performance: slow dashboard profiling, LogQL/PromQL optimization, indexing strategy review
• Cost analysis: retention vs. value matrix, storage tiering, identify over-retention and idle data streams
• Alert quality: alert noise reduction, SLO-based alerting design, eliminate flapping rules
• Coverage gaps: identify critical services lacking proper observability coverage

Deliverables

• Audit report with prioritized findings, cost-impact estimates, and a 30/60/90-day remediation roadmap
• Optimized Loki/Thanos configuration files with before/after benchmarks
• SLO dashboard templates (error budget, burn rate, availability) ready to import
• Alert rule library refactored for signal-to-noise
• 30-day handover period with Slack/Teams support for implementation questions

Ideal for

Teams running Grafana/Loki/Thanos at scale who suspect they are overpaying for storage, drowning in alert noise, or flying blind on the metrics that actually matter.

Tech stack