#eBPF
Articles about eBPF — exploring patterns, best practices, and real-world implementations in production systems.
8 posts tagged with ebpf. ← All posts
You rarely write raw eBPF bytecode by hand — a rich ecosystem of libraries, languages, and platforms sits on top, and one breakthrough (CO-RE) solved the portability problem that once made eBPF programs fragile across kernel versions. This closing post surveys how you actually build with eBPF, and where the technology is heading.
You rarely write raw eBPF bytecode by hand — a rich ecosystem of libraries, languages, and platforms sits on top, and one breakthrough (CO-RE, Compile Once Run Everywhere) solved the portability problem that once made eBPF programs fragile across kernel versions. This closing post surveys how you actually build with eBPF, and where it's heading.
Security is eBPF's third domain, and arguably its most natural fit: the kernel sees every syscall, every process, every file access and network connection, so an eBPF program in the kernel is perfectly positioned to watch for and stop malicious behavior in real time. This is why modern runtime-security tools — detecting and blocking threats on live systems — are increasingly built on eBPF.
Security is eBPF's most natural fit: the kernel sees every syscall, process, file access, and network connection, so an eBPF program in the kernel is perfectly positioned to watch for and stop malicious behavior in real time. This is why modern runtime-security tools — detecting and blocking threats on live systems — are increasingly built on eBPF.
Networking is where eBPF delivers its most dramatic performance wins. By running packet-processing logic in the kernel — at the earliest possible moment a packet arrives, before the kernel even builds its usual data structures — eBPF can filter, route, and load-balance at speeds user-space networking can't touch. It's why the networking layer of modern cloud-native infrastructure is increasingly eBPF underneath.
Networking is where eBPF delivers its most dramatic performance wins. By running packet-processing logic in the kernel — at the earliest moment a packet arrives, before the kernel builds its usual data structures — eBPF can filter, route, and load-balance at speeds user-space networking can't touch. It's why modern cloud-native networking is increasingly eBPF underneath.
Observability is where eBPF first went mainstream, and for good reason: it lets you see almost anything the kernel sees — syscalls, function calls, network events, disk I/O — with very low overhead and, crucially, without changing the code you're observing. That combination broke a long-standing trade-off in tracing and profiling, and it's why modern observability tools are increasingly built on eBPF.
Observability is where eBPF first went mainstream: it lets you see almost anything the kernel sees — syscalls, function calls, network events, disk I/O — with very low overhead and, crucially, without changing the code you're observing. That combination broke a long-standing trade-off in tracing and profiling, and it's why modern observability tools are increasingly built on eBPF.
The verifier is the reason eBPF exists in its modern form. Running arbitrary code in the kernel would be reckless; running code the kernel has proven safe is not. The verifier is the static analyzer that stands between your program and the kernel, mathematically checking that it can't crash, hang, or misbehave — and understanding it explains both eBPF's safety and its constraints.
The verifier is the reason eBPF exists in its modern form. Running arbitrary code in the kernel would be reckless; running code the kernel has proven safe is not. The verifier is the static analyzer that stands between your program and the kernel, mathematically checking it can't crash, hang, or misbehave — and it explains both eBPF's safety and its constraints.
An eBPF program's journey — from code you write to logic running in the kernel — has a few distinct pieces: the program itself, the hook it attaches to, the maps it uses to share data, and the load path that gets it safely into the kernel. Once you can name these four things and see how they fit together, eBPF stops being magic and becomes a system you can reason about.
An eBPF program's journey — from code you write to logic running in the kernel — has a few distinct pieces: the program, the hook it attaches to, the maps it uses to share data, and the load path that gets it safely into the kernel. Once you can name these four things and see how they fit, eBPF stops being magic. With an interactive architecture diagram.
To understand why eBPF is such a big deal, you have to understand the wall it lets you cross: the boundary between user space and the kernel. That boundary exists for good reasons — safety and isolation — but it also meant that extending the kernel was historically a choice between two bad options. eBPF is the third option nobody had before.
To understand why eBPF is a big deal, you have to understand the wall it lets you cross: the boundary between user space and the kernel. That boundary exists for good reasons — safety and isolation — but it meant extending the kernel was a choice between two bad options: a dangerous kernel module or a limited user-space workaround. eBPF is the third option nobody had before.
eBPF lets you run your own sandboxed programs inside the Linux kernel, safely, without changing kernel source or loading a risky module — and that quietly unlocks a new generation of observability, networking, and security tools. It's one of the most consequential systems technologies of the last decade, and it's worth understanding from first principles. This series builds eBPF up from the problem it solves.
eBPF lets you run your own sandboxed programs inside the Linux kernel, safely, without changing kernel source or loading a risky module — quietly unlocking a new generation of observability, networking, and security tools. It's one of the most consequential systems technologies of the last decade. This series builds eBPF up from the problem it solves.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.