Enabling BPF Runtime policies for better BPF management

As eBPF increasingly and rapidly gains popularity for observability, performance, troubleshooting, and security in production environments, a problem is emerging around how to manage the multitude of BPF programs installed into the kernel. Operators of distributed systems are already beginning to use BPF-orchestration frameworks with which they can set load and access policies for who can load BPF programs and access their resultant data. However, other than a guarantee of eventual termination, operators currently have little to no visibility into the runtime characteristics of BPF programs and thus cannot set policies that ensure their systems still meet crucial performance targets when instrumented with BPF programs. In this paper, we propose that having a runtime estimate will enable better policies that will govern the allowed latency in critical paths. Our key insight is to leverage the existing architecture within the verifier to statically track the runtime cost of all possible branches. Along with dynamically determined runtime estimates for helper functions and knowledge of loop-based helpers’ effects on control flow, we generate an accurate—although broad—range estimate for making runtime policy decisions. We further discuss some of the limitations of this approach, particularly in the case of broad estimate ranges as well as complementary tools for BPF runtime management.