Pixie Live Debugging with eBPF: The Complete Guide for Developers and Engineers

"Pixie Live Debugging with eBPF"

"Pixie Live Debugging with eBPF" is an authoritative and in-depth guide to harnessing the power of Pixie and extended Berkeley Packet Filter (eBPF) technology for live, production-grade observability. Navigating from foundational concepts to advanced distributed debugging techniques, this book presents a detailed exploration of Pixie’s architecture—unveiling how its collectors, query pipelines, and user interfaces work seamlessly with eBPF to bridge kernel and user space for real-time application diagnostics. Readers gain a solid understanding of the eBPF program lifecycle, secure instrumentation, and the robust integration points that make live debugging both effective and safe for production environments.

The book takes practitioners through every stage of deploying Pixie, from installation and configuration to integrating with Kubernetes-native clusters, automated CI/CD workflows, and achieving high availability at scale. It equips readers with advanced tracing and troubleshooting methodologies, including custom eBPF scripting, dynamic instrumentation, distributed tracing, and root cause analysis in complex microservices architectures. Practical sections delve into scripting with the Pixie Query Language (PxL), reusable automation patterns, and pipeline integration, empowering teams to standardize and accelerate their debugging workflows.

With a strong emphasis on performance optimization, security, and compliance, "Pixie Live Debugging with eBPF" addresses concerns such as minimizing instrumentation overhead, maintaining privacy under regulations like GDPR and HIPAA, and enforcing enterprise-grade access controls and auditability. Comprehensive chapters on extending Pixie through open-source integrations, plugin development, and analytics pipelines, coupled with real-world case studies and operational playbooks, make this book an indispensable resource for engineers, architects, and SREs seeking deep observability and rapid incident response in cloud-native environments.

© 2025 HiTeX Press (E-book): 6610001027773

Wydanie

E-book: 20 sierpnia 2025