Hire Grafana Engineering
for full-stack observability

From Prometheus metrics dashboards to unified LGTM observability stacks, our Grafana engineers give your team real-time visibility into every layer of your production system.

Discuss your monitoring project

40+

monitoring stack deployments

150+

data sources supported

25+

DevOps & observability engineers

Core Capabilities

What we build
with Grafana

Metrics Dashboards & Alerting

Prometheus, InfluxDB & cloud metrics

Production-grade Grafana dashboards for infrastructure, application, and business metrics — with multi-dimensional Prometheus alerting, PagerDuty/Slack routing, and on-call runbook links.

LGTM Observability Stacks

Loki + Grafana + Tempo + Mimir

Full open-source observability stacks — logs via Loki, distributed traces via Tempo, long-term metrics via Mimir — all visualised and correlated in Grafana without per-seat licensing costs.

Kubernetes Cluster Monitoring

kube-prometheus-stack with custom dashboards

Complete Kubernetes observability — node, pod, and namespace dashboards from kube-prometheus-stack, with custom panels for your application SLIs and automated capacity planning alerts.

How It Works

From blind spots to
production confidence

Observability
Assessment

We audit your current monitoring gaps — identifying uncovered services, missing SLI/SLO definitions, and alerting blind spots — then design a Grafana stack architecture that fills them.

Data Source
Integration

Prometheus exporters, OpenTelemetry collectors, and Loki agents are deployed across your infrastructure — instrumenting applications, Kubernetes nodes, databases, and cloud services with consistent labelling.

Dashboard &
Alert Build

Our DevOps engineers build role-specific dashboards — ops, engineering, and business — with Grafana alerting rules, escalation policies, and runbook annotations for every critical alert.

GitOps &
Provisioning

Dashboards, alert rules, and data source configurations are managed as code — versioned in Git, reviewed in pull requests, and deployed automatically via Grafana provisioning or the Kubernetes grafana-operator.

Hire Grafana Engineers

Observability specialists ready
to join your team

Scale your monitoring capabilities with dedicated Grafana engineers who build production-ready observability stacks from day one.

Hire Grafana Engineers

Prometheus + Grafana metrics stack setup and tuning

LGTM stack deployment (Loki, Grafana, Tempo, Mimir)

kube-prometheus-stack for Kubernetes cluster monitoring

Dashboard-as-code with GitOps provisioning

SLO-based alerting with PagerDuty & Slack routing

AI + Grafana

Dashboards that don't just
display — they diagnose

ML-powered
forecasting

Grafana's built-in ML forecasting predicts metric trends — projecting when disk, memory, or throughput limits will be reached and triggering preventive actions before incidents occur.

Anomaly
detection

Grafana Machine Learning automatically learns seasonal patterns in your metrics and surfaces deviations — catching subtle anomalies that threshold-based alerts miss entirely.

Natural language
query generation

Grafana's LLM integrations let engineers query metrics in plain English — generating PromQL or LogQL automatically and explaining what existing queries mean for non-experts.

AI incident
correlation

Cross-signal correlation in Grafana connects a Loki log spike to a Tempo trace to a Prometheus metric — with AI-assisted root cause summaries sent directly to your on-call channel.

FAQ

Frequently Asked
Questions

Grafana supports 150+ data sources including Prometheus, InfluxDB, Elasticsearch, PostgreSQL, MySQL, CloudWatch, Azure Monitor, Google Cloud Monitoring, Loki (logs), Tempo (traces), and more. This makes it the central observability hub for heterogeneous stacks — visualising metrics, logs, and traces in a single pane of glass.

LGTM stands for Loki (logs), Grafana (visualisation), Tempo (distributed traces), and Mimir (long-term metrics storage). Together they form a fully open-source, cost-effective alternative to commercial observability platforms — giving you metrics, logs, and traces correlated in Grafana without per-seat licensing costs.

We configure Grafana Alerting with multi-dimensional alert rules that evaluate against any data source. Alerts route through contact points (Slack, PagerDuty, email, webhooks) with notification policies defining routing, grouping, and silencing rules. For Kubernetes environments, we often pair Grafana with Prometheus Alertmanager for a complete on-call workflow.

Yes. We provision Grafana dashboards as JSON via Grafana's provisioning system or tools like grafana-operator for Kubernetes — storing dashboard definitions in Git and deploying them through CI/CD. This means dashboard changes go through code review, and your entire observability configuration is reproducible from scratch.

We deploy Grafana in high-availability mode with shared database backends (PostgreSQL) for session state, configure LDAP or OAuth SSO for team authentication, and use Grafana's organisations and folder-level permissions to isolate dashboards by team. For large metric volumes, we pair Grafana with Thanos or Mimir for horizontally scalable long-term storage.