Building scalable observability for a high-growth React Native app
By introducing custom performance tracking and stabilizing their test infrastructure, we helped the client detect incidents faster, improve release quality, and enable reliable performance insights across their React Native mobile app.
Fragmented observability and limited visibility into real-world performance
The client relied on multiple disconnected tools (Heap, New Relic, Datadog RUM) to monitor their React Native mobile app. Key business flows were hard to track, alerts were noisy or missing, and incident response was delayed due to limited dashboard coverage and inconsistent data. The team also struggled with test reliability, slow feedback loops, and a navigation setup that made changes risky and hard to validate.
Creating a unified monitoring layer and improving delivery confidence
We began with a full audit of the client’s analytics setup, performance instrumentation, test infrastructure, and CI/CD pipeline. From there, we delivered targeted improvements across several areas:
Monitoring and observability
- Built a shared abstraction layer to unify tracking across Heap, New Relic, and Datadog RUM
- Improved Datadog RUM setup with standardized interaction tracking and ESLint rules
- Migrated dashboards and monitors from New Relic to Datadog, adding richer metrics and widgets
- Ran a hands-on observability workshop covering dashboards, RUM, APM, and alerting best practices
Performance instrumentation
- Added custom native markers with
react-native-performanceto measure startup phases and TTI - Created reusable components to instrument key screens and user flows
CI/CD and testing improvements
- Migrated navigation from React Navigation v6 to v7 with test-friendly abstractions
- Improved test speed, coverage, and reliability through caching, nightly runs, and parallelization
- Integrated Reassure for render performance regression tracking
- Cleaned and modularized the automation framework with Slack-integrated reporting
Faster incident response, clearer insights, and shorter CI feedback loop
Our work gave the client accurate visibility into app startup and interaction timing, unified analytics workflows across systems, and reduced regression risk with automated performance checks. The CI pipeline became faster and more predictable, while updated dashboards and monitors enabled quicker, more informed response to production issues.
Key highlights
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How we’ve solved similar challenges
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