Pre-production observability

Your staging environment
is flying blind

StageRadar brings AI-powered observability to your pre-production environment. Group metrics by deploy, branch, or team. Catch regressions before they become incidents.

73%
of prod incidents visible in staging first
$0
spent on staging observability today
4.2x
faster regression detection

Built for what comes before production

Existing tools charge production prices for staging telemetry. StageRadar is purpose-built for pre-production environments.

Cohort-Based Metrics

Group staging metrics by deploy, feature branch, team, or PR. See how each cohort performs relative to your baseline, not just in isolation.

AI Regression Detection

Automatically surfaces performance drift and anomalies between staging deploys. Know something broke before your team merges to main.

Staging-First Pricing

No per-host fees. No per-GB traps. Flat pricing designed for high-churn staging environments where services spin up and down constantly.

Deploy Confidence Score

Every deploy gets a confidence score based on staging metrics, test coverage, and historical patterns. Ship with data, not gut feeling.

The staging observability gap

Production tools were never designed for the chaos of staging.

Today (production tools on staging)

  • Pay full production pricing for ephemeral environments
  • Alert fatigue from noisy, unstable services
  • No way to compare deploys or branches
  • Metrics disappear when staging resets
  • Teams skip staging monitoring entirely

With StageRadar

  • Flat pricing for unlimited staging environments
  • Smart alerting tuned for pre-prod instability
  • Cohort comparison across any dimension
  • Persistent history across environment resets
  • Every team gets staging visibility by default

Staging is where production incidents are born. Start watching.

The gap between "works on staging" and "works in production" isn't a mystery. It's a measurement problem. StageRadar makes that gap visible, quantifiable, and fixable before your users feel it.