Evolvable Network Telemetry at Facebook

Network telemetry is essential for service availability and performance in large-scale production environments. While there is recent advent in novel measurement primitives and algorithms for network telemetry, a challenge that is not well studied is Change. Facebook runs fast-evolving networks to adapt to varying application requirements. Changes occur not only in the data collection and processing stages but also when interpreted and consumed by applications. In this paper, we present PCAT, a production change-aware telemetry system that handles changes in fast-evolving networks. We propose to use a change cube abstraction to systematically track changes, and an intent-based layering design to confine and track changes. By sharing our experiences with PCAT, we bring a new aspect to the monitoring research area: improving the adaptivity and evolvability of network telemetry.