Dropping eBPF CPU Cost by About 90% with Memoization (Not AI Gen)
A developer explains how they achieved a 90% reduction in CPU costs for their eBPF security agent by implementing memoization. By caching policy decisions based on file inodes, the system avoids redundant path-walking operations.
Why it matters
This demonstrates a practical, high-impact optimization technique for kernel-level security tools, which is vital for performance-sensitive infrastructure.
My brother and I spent a lot of time designing our eBPF security agent to be really fast from the ground up, but recently we discovered we could make it much faster using memoization!
A couple of weeks ago, I profiled the eBPF code and found that the most expensive part of the protection isn’t actually enforcing a policy (allow/deny), but figuring out which policy applies to a given file open.
Our policies are path based, so our eBPF leverages an LSM hook that triggers on file open. We then reconstruct the path, walk up parent dentries, and check whether the file or any ancestor directory has a matching policy. While this works, it isn’t performant, and we end up repeating much of the work for files we have already seen (for example, database accesses that repeatedly reaccess file paths).
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in