Integrations
Your JTL tells you what was slow.
Connect your stack to find out why.
JMeter analysis works out of the box โ no setup, no credentials. Add infrastructure or APM tools to go from "something is slow" to "here is exactly why."
JMeter JTL
Liveby ApacheUpload any .jtl or .csv file. Services are auto-detected from URL patterns and analysis runs in under 60 seconds โ no configuration needed.
Percentile analysis
P50, P95, P99 per service
SLA violation detection
Threshold breach alerts
Degradation patterns
Trend & spike recognition
Connection starvation
Connect time analysis
Coming soon
Connect one and the engine automatically correlates it with your load test results.
Infrastructure Metrics
ยทWhere was the stress?Correlate response times with CPU, memory, GC and thread pool data โ timed to your exact load test window.
Prometheus
Query per-service CPU, memory, GC and thread pool metrics timed to your load test window.
- CPU & memory per service
- GC pause times
- Thread pool saturation
- Custom metrics
AWS CloudWatch
Pull EC2, ECS, RDS, and ALB metrics via IAM key โ no VPN or network changes required.
- EC2 CPU utilization
- RDS read latency
- ECS memory usage
- ALB response times
APM & Distributed Traces
ยทWhy did it fail?Find where time was spent inside your services โ slow DB queries, downstream calls, and individual spans.
New Relic
Run NRQL queries for transaction traces, DB query times, and Apdex scores during the test window.
- Transaction traces
- DB query breakdown
- Apdex score
- Downstream latency
Datadog
Fetch APM traces and infrastructure metrics via API key with read-only scope.
- APM trace correlation
- Service map
- Infrastructure metrics
- Custom dashboards
Jaeger
Query distributed traces from your self-hosted Jaeger to find slow spans and dependency bottlenecks.
- Span breakdown
- Dependency latency
- Slow DB calls
- Service graph
Logs
ยทWhat errors were thrown?Surface the actual error messages and stack traces that occurred during your load test.
Grafana Loki
Run LogQL queries to find error log spikes and connection pool exhaustion correlated to your test timeline.
- Error log spikes
- Connection pool errors
- Stack trace correlation
- Log volume trends
Security model
How credentials are handled when integrations launch.
Read-only access
No write permissions ever requested. We query, never modify.
Server-side only
Credentials stay on the backend. Never sent to the browser.
Encrypted at rest
AES-256 encryption. Never stored in env files or source code.
Verified before saving
Every connection is health-checked before credentials are saved.
Don't see your tool? Request an integration โ
โ Back to analysis