Prometheus and Grafana consulting for monitoring that drives action

Prometheus and Grafana consulting for monitoring that drives action

More dashboards do not create better visibility. Critical services hide behind infrastructure averages, while on-call receives hundreds of alerts from one failure. Our Prometheus and Grafana consulting and outsourcing services build monitoring around user impact, SLOs and fast diagnosis — with storage and cardinality under control.

Metrics architecture before dashboard design

We map Kubernetes, virtual machines, databases, queues and external dependencies to owners and failure modes. Node Exporter, kube-state-metrics, cAdvisor, Blackbox Exporter and OpenTelemetry Collector are added only where they answer an operational question.

Metric names and labels follow one convention. User IDs, request paths and other unbounded values stay out of labels before they create millions of series. Relabeling removes useless dimensions, while recording rules precompute expensive PromQL for dashboards, alerts and SLOs.

Prometheus that stays reliable as load grows

For smaller environments, a well-sized Prometheus pair may be enough. Multi-cluster estates can use regional collectors with remote write to VictoriaMetrics, Grafana Mimir or Thanos for long-term retention and global queries.

We size scrape intervals, retention, WAL, memory and storage around the sample rate. Remote-write queues, pending samples, series churn and ingestion lag are monitored so a slow backend does not create gaps. High availability covers Prometheus and Alertmanager rather than assuming a load balancer provides redundancy.

Grafana dashboards built for decisions

Fleet views answer whether infrastructure has capacity. Service dashboards show traffic, errors, latency and saturation. Incident dashboards connect a user-facing symptom to pods, nodes, databases, queues and recent deployments.

FinTech teams can track payment authorization; SaaS teams can see tenant impact and background-job delay. Business metrics complement technical telemetry without placing customer identifiers in labels.

Dashboards, data sources and alerts are provisioned from Git. Changes become reviewable, environments stay consistent and a Grafana rebuild does not erase operational knowledge.

SLOs instead of arbitrary thresholds

We define indicators around successful events, latency, availability or data freshness. Recording rules calculate good and total events; Grafana shows SLO compliance and error-budget consumption.

Multi-window burn-rate alerts distinguish a fast outage from slow degradation. Teams are paged when reliability is being consumed dangerously, not whenever CPU crosses a generic percentage.

Alertmanager that sends signal

Alertmanager routes by service, severity and ownership to PagerDuty, Opsgenie, Slack, Microsoft Teams or webhooks. Grouping combines related alerts, inhibition suppresses downstream symptoms when a dependency fails, and maintenance silences expire automatically.

Every page contains impact, dashboard, runbook and owner. Warning signals can create a ticket without waking an engineer. We also test the full alert path so a green dashboard cannot hide broken notifications. Logs from Loki or VictoriaLogs complete the diagnosis after a page.

Prometheus and Grafana outsourcing

We build a new stack, repair slow PromQL and alert fatigue, migrate from Zabbix or operate monitoring continuously. Support covers upgrades, exporters, target discovery, rules, retention and capacity.

You receive a metrics catalogue, architecture, dashboards as code, SLOs, alert-routing model and runbooks. Incidents are detected through customer impact, engineers reach the failing dependency faster, and cost grows through deliberate retention — not accidental cardinality.