
Capabilities | ||
|---|---|---|
Predict and control your costs | Usage-based pricing with Adaptive Telemetry: analyze traffic by label/team → aggregate under-utilized metrics (Adaptive Metrics) → drop low-value logs (Adaptive Logs) → tail-sample traces (Adaptive Traces). Learn more | Get metered in Compute Capacity Units (CCUs) whenever you run a query, evaluate an alert, or invoke an API call, which makes spend harder to forecast as usage scales. When pricing programs shift over time, budgeting can feel like trading one cost model for a more complex one. |
Use open standards and retain portability | Native support for OpenTelemetry (OTLP), PromQL, TraceQL, and standard backends (Prometheus/Mimir, Loki, Tempo) so workflows and tooling remain portable. Learn more | Billing uses Compute Capacity Units (CCUs)—every query, alert evaluation, or API call consumes CCUs, making growth hard to predict. |
Shorten time from alert to resolution | Correlate metrics, logs, traces, and profiles in a single Explore workspace; manage incidents via IRM/OnCall, and validate fixes with k6 performance tests. | You query, alert, and investigate inside the New Relic boundary—tool hopping still required for full context. |
Bring in external data easily | Connect to 150+ data source plugins (cloud, DB, SaaS, OSS systems) and correlate signals in Grafana Cloud without forcing ingestion into a single vendor backend. Learn more | Best optimized when data is ingested into New Relic’s stack—external sources need transformation or duplicative pipelines. |
Migrate with minimal disruption | Use a coexist → consolidate → replace path: keep incident workflows running, migrate telemetry signals gradually, and cut over when ready. | Supports ingesting open telemetry, but migration from legacy tools often means dual-running, new syntax (NRQL) and re-training. |




