Directory Observability & MonitoringAPM & Distributed TracingGrafana Pyroscope

Grafana Pyroscope

About Grafana Pyroscope

Grafana Pyroscope is an open source continuous profiling database. It helps users understand resource usage in applications down to the line number. It allows users to aggregate continuous profiling data with high availability, multi-tenancy, and durable storage. It was formed by the merger of two open source continuous profiling projects, Phlare and Pyroscope. The project natively integrates with Grafana.

Products

Grafana Pyroscope: Open source continuous profiling database for storing and querying profiling data.

Used for

Collecting CPU and memory profiles from applications that expose pprof endpoints.
Visualizing profiling data using Grafana's flame graph, histogram, and table views.
Optimizing code by identifying the slowest and most memory-hungry parts.
Correlating profiling data with metrics, logs, and traces.
Identifying changes and trends over time using durable, long-term storage of profiling data.

Who it is for

Developers seeking to understand the resource usage of their code.
Users running multiple independent teams or business units on one database.

From Grafana Pyroscope's own website, read 2026-10-23. How we build listings.

How to evaluate APM & Distributed Tracing

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Grafana Pyroscope. It comes from our Observability & APM Platforms buyer guide.

22%

Telemetry Coverage & Correlation

Unified metrics, traces, logs, real-user monitoring, synthetics, and continuous profiling; automatic correlation across signals; service maps and topology; Kubernetes, container, serverless, and cloud-provider auto-discovery; breadth and quality of the integration catalog

22%

Cost Control, Cardinality & Data Governance

Pricing-unit transparency and overage terms; high-cardinality handling without runaway cost; ingest-time filtering, sampling, aggregation, and tiered retention; a native or compatible telemetry pipeline; per-team budgets, quotas, and chargeback visibility so spend is governable, not just observable

20%

Distributed Tracing & APM Depth

End-to-end trace correlation across services and async boundaries, tail-based and adaptive sampling, code-level and method-level profiling, error tracking and exception grouping, database and dependency visibility, and frictionless OpenTelemetry trace ingestion alongside any native agent

16%

AIOps, Anomaly Detection & Root Cause

Quality of automated anomaly detection and alert noise reduction, causal versus correlative root-cause analysis, forecasting and capacity signals, and emerging agentic remediation — judged on accuracy during a real incident, not on the marketing name of the AI engine

12%

OpenTelemetry & Openness

Depth of native OTel support (traces, metrics, logs) versus a proprietary agent; whether collection is genuinely vendor-neutral or quietly locks you in; query-language portability; export and data-egress freedom; and how much re-instrumentation a future migration would actually require

Scale, Reliability & Operability

Proven performance at your peak event and series volumes, multi-region availability and platform SLA, data-retention options, RBAC and SSO, and — if self-hosted — the operational burden of running and upgrading the backend at high cardinality

Other APM & Distributed Tracing Vendors

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Airbrake

Alibaba Cloud Application Real-Time Service

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Quick Facts

grafana.com/oss/pyroscope

CategoryObservability & Monitoring

SubcategoryAPM & Distributed Tracing

DeploymentSelf-hosted

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