How it works

Drop it in.
See everything.

No collectors to operate, no query language to learn. Instrument once, and SentriNode handles ingestion, analysis, prediction, and the fix.

Three steps

From zero to insight in minutes.

01

Instrument

Add the SDK to your app — two lines for Python or Node, or point any OpenTelemetry client at our endpoint. Your services and LLM calls start streaming spans instantly.

02

Collect & analyze

We compute live latency (p50/p95), error rates, throughput, and LLM cost per model — and run anomaly detection across every service in real time.

03

Predict, replay, fix

SentriNode warns you before an incident breaks, lets you replay exactly how it happened, and hands you the root cause, a Jira ticket, and the commands to run.

Built in

An incident-intelligence suite, not just charts.

Most tools show you a graph and leave the thinking to you. SentriNode does the thinking.

LLM cost & usage

Per-model spend, tokens, and latency — so the call that quietly costs 15× as much stops hiding in your bill.

Predictive alerts

A trend forecast that warns you a breach is coming, names the culprit service, and gives you an ETA — before the page fires.

Ghost mode replay

Scrub any incident frame by frame. Watch the latency spike build and the failure cascade, exactly as it happened.

One-click Fix It

AI root cause + a filled-in Jira ticket + the exact diagnostic commands, generated from the live anomaly.

What-if simulator

Model traffic spikes, added latency, or extra capacity against your real baseline — and see the projected impact and cost.

Adaptive Telemetry

Recommendations on what to sample or drop, with savings estimates, so you ingest only what's worth paying for.

Ready when you are

See your stack in two minutes.

Free to start. No credit card.

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