Prometheus and Grafana resume examples for observability engineers
Prometheus and Grafana are the de-facto open-source monitoring stack for Kubernetes environments and appear together in the vast majority of DevOps and SRE job descriptions. Strong observability experience means more than deployment — it means owning SLOs, building actionable dashboards, and designing alerting that reduces noise rather than adding to it.
What recruiters look for
SLO design and ownership — defining SLOs, mapping them to SLIs from Prometheus metrics, and managing error budgets. This separates SRE-track candidates from pure infrastructure engineers.
PromQL depth — custom recording rules, histogram_quantile for latency, and multi-label aggregations. Recruiters reviewing experienced candidates often ask about PromQL in interviews; your resume should hint you can handle it.
Grafana dashboard quality — not just 'built dashboards' but meaningful ones: golden signals, user journey views, per-team usage dashboards. Board count and who uses them is the evidence.
Alerting design — routing rules in Alertmanager, PagerDuty and OpsGenie integration, inhibition and silencing rules. Alert fatigue is a real problem; showing you've reduced it is valued.
How to phrase it — weak vs strong
Set up Prometheus and Grafana for monitoring
Deployed kube-prometheus-stack across 3 Kubernetes clusters; defined 12 SLOs mapped to Prometheus-scraped SLIs; built Grafana SLO burn-rate dashboards used in weekly reliability reviews
Created Grafana dashboards for the engineering team
Built 30 Grafana dashboards covering golden signals (latency, traffic, errors, saturation) for 20 microservices; reduced mean time to detect incidents by 40% compared to log-only monitoring
Configured alerting using Prometheus and PagerDuty
Redesigned Alertmanager routing to reduce alert noise by 65%; implemented multi-window burn-rate alerts for 5 critical user-facing services; reduced out-of-hours pages by 45% in 3 months
Wrote Prometheus exporters for our services
Instrumented 8 Go microservices with custom Prometheus metrics; defined histograms for request latency and counters for business events; added PromQL recording rules to precompute SLI aggregations across 200M daily requests
Related skills in this category
Engineers hiring for Prometheus roles often look for these adjacent skills. Including them in your resume — where you genuinely have the experience — improves your match score across a wider set of job descriptions.
Frequently asked questions
Should I list Prometheus and Grafana as separate skills or together?
They're often used together, but list them separately so ATS systems match both terms independently. A JD mentioning only 'Grafana' for a data visualisation role should match your Grafana entry; one asking for 'Prometheus + PromQL' should match your Prometheus entry. Sharpen.cv scores them independently.
How do I show Prometheus experience if I only ran it as a managed service?
Focus on what you owned: dashboard design, alerting rules, SLO definition, or PromQL queries. Operating Grafana Cloud, AWS Managed Prometheus, or Datadog with Prometheus-compatible metrics is real observability experience. Show the outcomes — SLO improvements, incident detection improvements, or on-call noise reductions.
What observability alternatives to Prometheus are worth listing?
OpenTelemetry is increasingly important as a collection layer; list it alongside Prometheus if you've used it. Datadog and New Relic are commercial alternatives common in enterprise stacks. If a JD asks for 'observability' broadly, listing your full stack (Prometheus, Grafana, OpenTelemetry, Loki) is better than picking one.
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