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Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Instant, code‑free observability for Kubernetes applications and clusters
Pixie provides automatic, eBPF‑based telemetry and a Pythonic query language to visualize network, infrastructure, and application performance directly inside your Kubernetes cluster, using under 5% CPU.
Pixie is built for developers, SREs, and platform engineers who run containerized workloads on Kubernetes and need instant visibility without adding instrumentation code.
Using eBPF, Pixie automatically captures full‑body requests, resource metrics, network flows, and application profiles across the entire cluster. The data is stored and queried locally, keeping CPU usage under 5 % in most cases. PxL, a Python‑style query language, lets users explore traffic maps, flame graphs, latency per service, database query performance, and continuous profiling through the web UI, CLI, or API.
Installation takes minutes via the provided Helm chart or operator. All telemetry components run as in‑cluster edge services, eliminating the need for external collectors. Once deployed, teams can start querying immediately, create custom dashboards, and integrate Pixie into CI/CD pipelines or alerting systems.
When teams consider Pixie, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Network Monitoring
Visualize intra‑cluster traffic flows, DNS queries, TCP drops, and retransmissions in real time.
Service Performance
Measure per‑service latency, identify slow endpoints, and view full‑body request traces.
Database Query Profiling
Track query latency, error rates, and throughput per pod and per normalized query.
Continuous Application Profiling
Generate flame graphs and CPU usage profiles to pinpoint performance bottlenecks in running code.
Pixie is an observability platform that automatically collects telemetry from Kubernetes clusters using eBPF and provides a queryable interface for deep insight.
It leverages eBPF probes built into the Linux kernel to capture network packets, system calls, and resource metrics directly from the running pods.
The edge compute component is designed to use less than 5 % of CPU in typical workloads, often under 2 % after optimization.
Pixie offers PxL, a Python‑style query language accessible via the web UI, CLI, or programmatic API.
Yes, Pixie is released under the Apache‑2.0 license and can be deployed freely on any compatible Kubernetes cluster.
Project at a glance
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