Post-Release Monitoring & Synthetic Journeys
Catch issues in production before your customers tweet about them
What this service delivers
Releasing is not the finish line. Our post-release monitoring combines crash-free session tracking, synthetic journey execution, RUM telemetry analysis, and SLA-backed alerting to detect regressions within minutes of deployment, and feed them back into the next test cycle.
- SLA-backed crash-free session and checkout success rate alerting
- Synthetic journey execution on real devices every 15 minutes
- RUM and APM telemetry loop feeding test case recommendations
- Cohort crash analysis to protect high-value user segments
- Weekly quality business review with trend analysis
Our approach
How we deliver post-release monitoring & synthetic journeys
A structured, evidence-based methodology that produces findings your team can act on, not reports that sit in a folder.
Telemetry baseline and alert threshold design
We instrument your production environment with the right combination of crash reporting, RUM, and APM tooling, or integrate with your existing stack (Crashlytics, Sentry, Datadog, New Relic). We establish baselines for crash-free session rate, checkout success rate, and synthetic journey pass rate, then configure alerting thresholds that signal genuine regressions rather than noise.
Synthetic journey scripting
We script your most critical user journeys, login, onboarding, checkout, core feature, as automated synthetic tests executed on real physical devices every 15 minutes against your production environment. Unlike monitoring tools that ping endpoints, synthetic journeys execute real device interactions through the actual app, catching UI rendering failures, deeplink breaks, and flow-level regressions that API health checks miss.
Crash cluster analysis and cohort segmentation
When a regression occurs, we analyse crash clusters across device, OS version, geography, and user cohort to identify the most impacted segment. This allows your team to prioritise a hotfix for the segment driving the most revenue or user complaints, rather than responding uniformly to an aggregate metric that may mask segment-level severity.
Weekly quality business review (QBR)
Every week we deliver a structured QBR report covering crash-free session trends, synthetic pass rate, detected regressions and their resolution status, and test case recommendations generated from production telemetry. The telemetry loop ensures that the patterns users encounter in production drive the test cases in the next release cycle, not only the test cases the team remembers to write.
What you receive
Every engagement delivers a defined set of artefacts. No ambiguity about what you're buying.
Discuss scope| Deliverable | Description |
|---|---|
Monitoring configuration | Crashlytics, Sentry, or Datadog setup with production-accurate thresholds and alerting rules. |
Synthetic journey suite | Real-device automation scripts for critical journeys with 15-minute cadence and Slack/PagerDuty alerting. |
Weekly QBR report | Crash-free session trends, synthetic pass rate, regression log, and telemetry-driven test recommendations. |
Crash cluster analysis | Segment-level breakdown of crash impact by device, OS, geography, and user cohort for prioritised hotfix decisions. |
Telemetry loop recommendations | Test case update list generated from production patterns for integration into the next release test cycle. |
| Tool | Category |
|---|---|
| Firebase Crashlytics | Crash |
| Sentry | Error monitoring |
| Datadog RUM | Real user monitoring |
| New Relic Mobile | APM |
| AppDynamics | APM |
Tools & technologies
We use the tools your team already knows where possible, and introduce specialist tooling where it provides accuracy or coverage advantages you can't get otherwise.
Engagement phases
What the engagement looks like from brief to delivery, so your team can plan sprint integration points from day one.
Instrumentation
- Telemetry stack integration or configuration
- Baseline measurement
- Alert threshold calibration
Synthetic suite build
- Journey scripting and device configuration
- 15-minute cadence activation
- Alerting integration with Slack / PagerDuty
Ongoing monitoring
- Weekly QBR delivery
- Crash cluster analysis on regressions
- Test recommendation updates
- Threshold tuning
Post-Release Monitoring & Synthetic Journeys, questions your team asks first
Post-release monitoring continuously tracks the health of your live app by collecting crash reports, performance metrics, and user-journey completion rates from real users in production, detecting regressions before they affect a significant user segment.
Synthetic journeys are scripted test runs executed on real devices against your production environment on a scheduled interval, simulating critical user paths like login, checkout, or media playback to detect outages and regressions in real time.
Industry benchmark for consumer apps is 99.5% crash-free sessions. Fintech and health apps target 99.9%+. Below 99.0% correlates with measurable increases in uninstalls, 1-star reviews, and support ticket volume.
Our telemetry loop analyses crash cluster patterns, failing synthetic journeys, and RUM anomalies to automatically generate test case recommendations and update device matrix weights for the next regression cycle.
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Learn moreDiscuss Post-Release Monitoring & Synthetic Journeys for your app
Talk to a test architect about your stack, release cadence, and the specific failure modes you're trying to prevent. We'll scope an engagement that fits your sprint cycle.