Pyroscope

Pyroscope is an open-source continuous profiling database that captures application resource usage down to the line number, designed for developers and SREs who need production-level visibility into CPU, memory, lock contention, and goroutine behavior. Founded in 2021 by Ryan Perry and Dmitry Filimonov, it merged with Grafana Labs' Phlare project in 2023 to become Grafana Pyroscope, now natively integrated into the Grafana observability stack. The tool targets teams running Kubernetes workloads who want to correlate profiling data with metrics, logs, and traces, enabling them to identify performance regressions and optimize infrastructure spend without requiring separate staging environments.

Pyroscope captures stacktraces at a regular interval of roughly 100 Hz and samples memory allocations and lock contention events, temporarily storing this data in memory before sending it to the server every 15 seconds by default. It uses a custom storage engine and proprietary compression algorithms to store profiling data efficiently, with a memory overhead typically less than 50 MB per pod—often so minimal that it becomes challenging to measure accurately. The system is horizontally scalable, supports highly available configurations for 100% uptime during upgrades or machine failures, and provides durable long-term storage. Key visualization features include flame graphs and profile comparison, and it fully integrates with Grafana to correlate profiles with other observability signals.

In the competitive landscape of continuous profiling, Pyroscope competes with Datadog, Google Cloud Profiler, Polar Signals, Parca, Dynatrace, New Relic, Sentry, and Elastic Universal Profiling. Its open-source nature and Grafana-native integration differentiate it from proprietary solutions like Datadog and Dynatrace, while its consistent architecture with Loki, Mimir, and Tempo reduces the learning curve for teams already using Grafana's database ecosystem. Compared to Polar Signals and Parca, Pyroscope emphasizes high availability and durable storage as core features, though all tools face similar challenges in capturing production profiles without impacting application performance.

A key trade-off is that if the Pyroscope backend is down or slow, the profiler discards new profiles to prevent running out of memory, prioritizing application stability over data completeness. While the memory overhead is very low, it scales sublinearly with CPU count, meaning high-CPU applications may see slightly higher overhead. The tool requires running a dedicated backend server for storage and querying, adding operational complexity for teams not already using Grafana. Additionally, because profiling data is sent in batches every 15 seconds, there is a slight delay in data availability, which may not suit real-time debugging scenarios. Pricing is not explicitly stated in the sources, but Grafana Cloud offers a managed version with free and paid tiers.

Not explicitly stated in the sources; Grafana Cloud offers a managed version with free and paid tiers, but specific pricing for Pyroscope is not detailed.