OpenTelemetry Root Cause Analysis, Vendor-Neutral
NeuBird reads your OpenTelemetry traces, metrics, and logs from any backend, correlating every signal across your instrumented services to deliver root cause analysis without manual trace hunting.
In place
Data queried where it lives, never copied
Every agent
Inherits the connection once it is made
Earned
Write access, widened by track record
Full
Audit trail on every action
Core Capabilities
From signals to solutions
Prevent
Detect service degradation across your OTel-instrumented stack
NeuBird reads OpenTelemetry metrics and trace data continuously, detecting latency increases, error rate anomalies, and span duration outliers across your instrumented services before they reach error-budget-burning levels.
- Anomaly detection across OTLP metrics and trace span patterns
- Correlates new service versions (via resource attribute changes) with emerging regressions
- Surfaces degradation across multi-language, multi-service OTel instrumentation simultaneously
Resolve
Follow the trace, automatically
When an incident occurs, NeuBird traverses distributed trace graphs from your OTel backend, correlates span-level data with metrics and logs, and identifies the exact service, operation, and time window where the fault originated. That makes it some of the best AI root cause analysis software for incidents built on open telemetry.
- Automatic trace graph traversal to isolate root span and failing service
- Cross-signal correlation: traces + metrics + logs from the same OTel context
- Plain-language RCA including the specific service, endpoint, and error signature
Operate
Find instrumentation gaps and Collector inefficiencies
NeuBird analyzes your OTel Collector pipeline throughput, sampling configurations, and service coverage to identify uninstrumented services, over-sampled trace paths, and backend routing inefficiencies.
- Surface services not yet instrumented with OTel SDKs
- Identify trace sampling gaps that hide high-error-rate operations
- Recommend Collector tail-sampling rules based on observed trace patterns
Better Together
OpenTelemetry + NeuBird
| Capability | OpenTelemetry | NeuBird |
|---|---|---|
| Vendor-neutral instrumentation for traces, metrics, and logs | ✓ | ✓ |
| Collect and export telemetry to any backend | ✓ | ✓ |
| Correlate signals across services automatically | Manual trace inspection | ✓ |
| Root cause analysis without trace hunting | None | ✓ |
| Proactive anomaly detection from telemetry streams | None | ✓ |
| Cross-tool correlation (cloud, CI/CD, on-call) | None | ✓ |
| Autonomous 24/7 incident triage | None | ✓ |
| Instrumentation coverage analysis | None | ✓ |
Ecosystem
Works across your entire stack
OpenTelemetry is one piece of the picture. NeuBird queries it in place and correlates it with every other connected tool, and every agent in the center inherits the connection.
Trace Backends
- Jaeger
- Grafana Tempo
- Zipkin
- Honeycomb
Metrics Backends
- Prometheus
- InfluxDB
- Mimir
- New Relic
Log Backends
- Loki
- Elasticsearch
- Splunk
- Datadog
Full-Stack Observability
- Grafana
- Dynatrace
- New Relic
- Datadog
FAQ
Common questions
What makes NeuBird the best AI root cause analysis software for incidents on OpenTelemetry?
NeuBird reads your existing OTel traces, metrics, and logs from any backend and correlates them automatically, so incident root cause analysis happens without manual trace hunting or vendor lock-in. It works with whatever OTel stack you already run and delivers plain-language RCA in minutes.
Does NeuBird connect directly to the OTel Collector?
NeuBird reads from your OpenTelemetry backends: the trace store, metrics store, and log store your Collector exports to. This keeps your Collector pipeline unchanged and NeuBird observe-only.
Which OTel backends does NeuBird support?
NeuBird supports any backend your OTel Collector exports to, including Jaeger, Grafana Tempo, Prometheus, InfluxDB, Loki, Elasticsearch, and any backend with a standard query API.
Can NeuBird handle services instrumented with different OTel SDK languages?
Yes. NeuBird uses trace context propagation and resource attributes to correlate signals across services regardless of the SDK language used. Java, Go, Python, Node.js, and others all participate in the same incident analysis.
What if we are only partially instrumented with OTel?
NeuBird works with whatever instrumentation you have. It reads from all connected tools simultaneously, so gaps in OTel coverage are compensated by data from your other connected sources: infrastructure metrics, cloud APIs, CI/CD events.
Does NeuBird help with OTel sampling configuration?
Yes. NeuBird's Optimize capability analyzes your trace sampling rates and identifies operations where the current sampling policy is too aggressive, dropping traces that carry valuable error or latency signal.
Get Started
Connect OpenTelemetry to the center.
OpenTelemetry gives you the data. Connect it to NeuBird once, and every agent that touches production inherits it, including the ones you build yourself.