Hire Prometheus Engineering
for metrics-driven observability

From metric collection and alerting rules to Grafana dashboards and long-term storage, our Prometheus engineers build comprehensive monitoring solutions that give you complete visibility.

Discuss your Prometheus monitoring

PromQL query design, recording rules & alerting rule configuration

Service discovery with Kubernetes, Consul, EC2 & static targets

Thanos & Cortex for long-term storage and global query views

Alertmanager integration with PagerDuty, Slack & Opsgenie

Exporters for databases, message queues, web servers & custom apps

Core Capabilities

What we build
with Prometheus

Metrics & Collection

Scalable and reliable

Multi-dimensional data collection with PromQL, optimized scrape configurations, federation for hierarchical setups, and custom exporters for application-specific metrics.

Alerting & Incident Response

Proactive and actionable

Alertmanager with intelligent routing, grouping, inhibition, and silencing. Integration with PagerDuty, Slack, Opsgenie, and Webex for multi-channel notifications.

Long-Term Storage

Scalable and cost-effective

Thanos and Cortex for horizontally scalable, highly available long-term metric storage with global query views, downsampling, and S3-compatible object storage backends.

How It Works

From metrics strategy to
production

Metrics Strategy &
Design

We identify key metrics for your services, design scrape configurations, define recording and alerting rules, and plan the architecture for your scale and retention requirements.

Agile
Development

Our DevOps engineers work in 2-week sprints with continuous integration and demo cycles. You see dashboards and alerts evolving every step of the way.

Testing &
CI/CD

Alert rule testing with promtool, integration testing of the full monitoring stack, and our QA specialists validate alert accuracy and notification delivery through automated pipelines.

Deployment &
Monitoring

Prometheus deployed with Docker and Kubernetes, Thanos sidecars for HA, remote write to Cortex/Mimir, and monitoring of monitoring with dead man's switch alerts.

Hire Prometheus Engineers

Prometheus engineers ready
to join your team

Gain complete visibility into your systems with dedicated Prometheus engineers who build custom monitoring solutions from day one.

Hire Prometheus Engineers

Why product Enhancement

Improve with intent,
not impulse

AI-assisted
alert design

AI tools analyze your metrics patterns and suggest alert thresholds, recommend recording rules, and identify noisy or missing alerts in your Alertmanager configuration.

AI-powered
testing

Automated validation of PromQL queries, alert rule regression testing, and chaos engineering integration to verify alerts fire correctly under failure scenarios.

Query
optimization

AI-driven PromQL optimization, recording rule recommendations to reduce query load, and cardinality analysis to prevent high-cardinality metric explosions.

Intelligent
automation

Automated dashboard generation from service topology, anomaly detection on metric patterns, and smart capacity forecasting from historical Prometheus data.

FAQ

Frequently Asked
Questions

Prometheus is the de facto standard for cloud-native monitoring. Its dimensional data model, powerful PromQL query language, pull-based architecture, and tight Kubernetes integration make it the cornerstone of modern observability stacks.

We use federation for hierarchical setups, Thanos or Cortex for horizontal scaling and long-term storage, sharding with hashmod, and remote write to compatible backends for high availability.

Yes. We configure intelligent routing trees, grouping to reduce noise, inhibition rules to suppress dependent alerts, and multi-channel notification delivery to PagerDuty, Slack, Opsgenie, email, and custom webhooks.

We use node_exporter, kube-state-metrics, Blackbox exporter, JMX exporter, PostgreSQL exporter, Redis exporter, and build custom exporters with the Prometheus client libraries in Go, Java, Python, and .NET.

We build Grafana dashboards with Prometheus as the primary data source, create templated dashboards for multi-environment views, set up alert annotations on graphs, and integrate Loki for log correlation and Tempo for traces.