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Explore function tracing enhancements using BTF to display return values and arguments, improving debugging capabilities in Linux kernel development.
Explore Datadog's eBPF journey, uncovering challenges, pitfalls, and lessons learned in observability, security, and networking. Gain insights into eBPF hook points, security bypasses, and networking complexities.
Explore bpftime, a userspace eBPF runtime offering faster uprobes and syscall hooks. Learn about its performance benefits, implementation techniques, and compatibility with existing eBPF toolchains.
Exploring open-source attestation service for confidential computing, addressing challenges in guest attestation and verification. Introduces KBS API and discusses future integration of trusted device attestation.
Exploring pstore technology as a lightweight alternative to kdump for kernel debugging, focusing on Steam Deck use case and potential improvements for efficient data collection during kernel panics.
Exploring strategies to enhance kernel CI systems for better regression detection, analysis, and reporting. Discusses standardizing workflows, improving data processing, and addressing challenges in regression tracking.
Exploring a framework for host-guest communication in KVM to minimize VM latencies by dynamically boosting vCPU thread priorities based on guest scheduling needs and host insights.
Enhancing Linux Perf tool to accurately measure CPU usage and task sleep time, addressing limitations in sample collection for sleeping processes.
Exploring ftrace_regs as a unified interface for function tracing, addressing limitations of pt_regs and improving efficiency across architectures. Discusses integration with fprobe, eBPF, and function-graph tracer.
Enhancing Linux kernel security through KVM-based protection mechanisms, offering improved defense against vulnerabilities and discussing new features for mainline integration.
Proposal for a syscall to migrate physical memory contents between NUMA nodes, exploring integration with mm/migrate.c and potential applications in tiering frameworks.
Explore kernel debugging without DWARF using Drgn, leveraging BTF/CTF, kallsyms, and other introspection tools for efficient and flexible debugging in various situations.
Automated solution for optimizing Linux kernel parameters using machine learning, focusing on memory management. Explores design, architecture, and results, proposing future in-kernel ML framework.
Explore eBPF profiling for interpreted languages and JIT runtimes, discussing challenges in scalability, uniformity, and integration with cloud-native ecosystems. Learn about edge cases and low-level observability implementation.
Learn to install LKMM on Linux systems and explore its capabilities through sample litmus tests, gaining insights into interpreting its output for enhanced kernel development.
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