01
Service throughput, errors, and latency
Compare real services by request volume, error rate, p95, p99, environment, version, and deployment.
Solution · Application performance
Find the service, request, or dependency consuming the latency budget.
Turn OpenTelemetry traces into service-level throughput, error, and latency views, then continue from a regression to the representative transaction, dependency, deployment, or hot function.
- service health model
- RED
- tail latency
- p95 + p99
- transaction evidence
- trace-native
- code hotspots
- profile-aware
APM summaries that keep the underlying evidence close.
Service health, transactions, dependencies, deployments, traces, logs, and profiles stay on the same tenant and time plane.
workflow
From a service regression to the responsible operation.
The workflow narrows scope while preserving the evidence needed to explain the change.
- 101 · Detect
Compare service health
Find the service and environment where throughput, errors, or tail latency moved outside its normal range.
- 202 · Localize
Rank transactions and dependencies
Separate a slow route, failing operation, or downstream dependency from background traffic.
- 303 · Inspect
Open a representative trace
Use the complete span waterfall to identify the call that consumed time or returned the error.
- 404 · Explain
Check deployment, logs, and code hotspots
Confirm whether the regression aligns with a release, error pattern, or hot function.
proof / shipped
The APM surface is derived from trace data already in the platform.
Current product views include overview, services, transactions, dependencies, errors, deployments, service detail, and representative traces.
- Throughput, error rate, p95, and p99 overview
- Service and transaction ranking
- Dependency health and span waterfalls
- Deployment, error, log, and profile drill-downs
Solution · Application performance
Find the service, request, or dependency consuming the latency budget.
Turn OpenTelemetry traces into service-level throughput, error, and latency views, then continue from a regression to the representative transaction, dependency, deployment, or hot function.