Blog Details

Introduction & Industry Dynamics

In modern cloud infrastructures and containerized environments, eBPF (extended Berkeley Packet Filter) technology has become an indispensable component of security and observability solutions, providing visibility at the network and system levels. However, because eBPF programs execute in kernel space, the CPU cost of each operation is directly impacted. Specifically, the repeated path analysis performed during file access policy enforcement can lead to significant performance degradation in high-traffic systems. In this context, we detail how InsightTech overcame this critical bottleneck in our eBPF-based security agents using memoization, a fundamental principle of software engineering, achieving up to 90% CPU savings.

The general trend in the industry is that as the complexity of security policies increases, the speed at which these policies are enforced must increase proportionally. Traditional approaches perform a full directory tree (dentry) walk for every file access event to determine policy matching. This method, especially in applications like database servers that perform frequent file accesses, causes the same calculations to be repeated for different files within the same subtree. This situation paves the way for the accumulation of inefficient processes, referred to as the 'slow path,' resulting in system-wide latency and CPU consumption.

Technical & Architectural Deep Dive

The foundation of our architectural solution lies in a lightweight and secure caching strategy that adheres to kernel-space memory constraints and eBPF mapping mechanisms. Initially, we considered using directory entries (dentries) directly as keys; however, the pointer nature of dentries makes it impossible to store them directly in eBPF maps. Copying