This article explains how to use eBPF and perf events to trace NFS read/write system calls, capture kernel and user stack traces, resolve them to source locations via DWARF, and generate flame‑graph data that is pushed to Pyroscope for performance analysis.
Conan is an automated profiling solution for Go microservices that embeds an SDK to continuously or adaptively sample CPU, memory and goroutine metrics, detects anomalies via user‑defined rules, uploads data to a Pyroscope server, and reports results through Feishu or Pyroscope, delivering sub‑5 % overhead and faster root‑cause analysis.
This guide explains how to install and configure the open‑source Pyroscope continuous profiler on a Kubernetes cluster, integrate it with Python, .NET, and Go microservices, and visualize low‑overhead flame graphs to identify performance bottlenecks and reduce cloud costs.
This article explains why traditional log‑based performance debugging is inefficient, introduces continuous profiling with the open‑source Pyroscope tool, and provides step‑by‑step instructions for installing Pyroscope on Kubernetes, integrating it with Python, .NET, and Go microservices, and visualizing low‑overhead flame graphs to optimize code and reduce cloud costs.
This guide explains how to use the open‑source Pyroscope continuous profiler on Kubernetes to collect, store, and visualize performance data from microservices written in Go, Python, .NET, and more, enabling developers to pinpoint bottlenecks, reduce CPU and memory usage, and lower cloud costs.
Developers can identify performance bottlenecks in production microservices by leveraging continuous profiling tools like Pyroscope, which collects, stores, and visualizes CPU and memory usage across Kubernetes clusters, and the article provides a detailed walkthrough of installation, configuration, and integration with various language services.
This guide explains how to integrate the open‑source Pyroscope platform with Rainbond to continuously profile microservices, detect CPU bottlenecks and memory leaks, and visualize performance data through its UI and various view modes.
Learn how to use the open‑source Pyroscope continuous profiler to identify performance bottlenecks in Kubernetes‑deployed microservices, compare it with other profilers, and follow detailed installation, configuration, and integration steps for Python, Go, and .NET services, including Helm deployment and resource monitoring.
