These two get compared constantly, but they solve overlapping, not identical, problems. Here is how Prometheus and OpenTelemetry relate, and how to use them together.
Prometheus is a metrics monitoring system and time-series database with a pull-based model; OpenTelemetry is a vendor-neutral standard for instrumenting and collecting all three signals, traces, metrics and logs, and exporting them over OTLP. They interoperate rather than compete, and most teams use both.
Prometheus is a complete metrics stack: it collects (by scraping), stores (its own TSDB), queries (PromQL) and alerts (Alertmanager), all for metrics. OpenTelemetry is not a backend at all; it is instrumentation SDKs plus the Collector and the OTLP protocol, and it is signal-agnostic, covering traces and logs as well as metrics. In short, Prometheus is a monitoring system; OpenTelemetry is how you produce and move telemetry to whatever system stores it.
Because their scopes overlap on metrics, they are built to interoperate. The OpenTelemetry Collector can scrape Prometheus endpoints and can export metrics to Prometheus via remote-write, and Prometheus can now ingest OTLP metrics directly. A very common pattern is to instrument applications with OpenTelemetry (so instrumentation is portable across all three signals and not locked to one vendor) while storing and querying metrics in Prometheus or a Prometheus-compatible backend with PromQL.
It is rarely either/or. Choose OpenTelemetry for instrumentation, because it covers all three signals and avoids lock-in. Choose Prometheus (or a compatible store) for metrics storage and query if you want the open-source standard and PromQL. The teams that get it right use OpenTelemetry to generate telemetry and Prometheus-compatible tooling to work with the metrics, rather than treating them as rivals.
| Dimension | Prometheus | OpenTelemetry |
|---|---|---|
| Scope | Metrics monitoring system + TSDB | Instrumentation and collection standard |
| Signals | Metrics only | Traces, metrics and logs |
| Model | Pull (scrapes endpoints) | Push over OTLP (and can scrape via Collector) |
| Storage | Built-in TSDB | None of its own; sends to a backend |
| Query | PromQL | Backend-dependent |
| Best for | Cloud-native metrics + alerting | Portable, vendor-neutral instrumentation |
The most frequent error is treating this as a migration, ripping out Prometheus to adopt OpenTelemetry, or refusing OpenTelemetry to protect a Prometheus investment. Both misread how the two relate. OpenTelemetry does not replace your metrics backend; it standardises how telemetry is produced and moved. Prometheus does not block OpenTelemetry; it ingests OTLP metrics and remains an excellent PromQL store. The teams that struggle are usually the ones who framed it as an either-or decision. The teams that succeed instrument with OpenTelemetry for portability and keep Prometheus-compatible tooling for the metrics they already know how to operate.
Ops Singularity is OpenTelemetry-native and works with Prometheus-compatible metrics, so it sits at the end of exactly this pattern: instrument with OpenTelemetry, keep PromQL where you want it, and let TelemetryOps and Sentinel AI correlate the signals and resolve incidents autonomously.
No. OpenTelemetry standardises instrumentation and collection across all three signals; Prometheus remains a leading metrics store and query engine. They interoperate, and many teams use OpenTelemetry to feed Prometheus-compatible backends.
Yes. Prometheus can ingest OTLP metrics, and the OpenTelemetry Collector can export to Prometheus via remote-write, so the two connect in both directions.
Ops Singularity turns open telemetry into autonomous, governed resolution. See it on your own stack.