Revisiting Network Telemetry in COIN: A Case for Runtime Programmability

Abstract

Applications based on the compute-in-the-network (COIN) paradigm require flexible network telemetry data to drive effective allocation decisions. Telemetry systems collect such data based on queries specifying the precise traffic metrics or features required. Recent advances in programmable switch hardware have led to highly efficient methods to compute query results using in-network resources. However, current approaches fail to meet the simultaneous requirements of dynamic traffic loads, diverse query types, and query dynamics. In this work, we argue that telemetry systems should be cast as active runtime schedulers rather than static data sources. COIN-based applications can then dynamically submit telemetry queries on the fly and react to their results in a closed-loop fashion – enabling a new generation of telemetry-driven reactive applications. As a first step toward this vision, we present a single-switch telemetry operation scheduling method. Our empirical evaluation demonstrates that such a method can reduce overhead by an order of magnitude compared to worst case allocations. This initial exploration opens the door to a multi-tier scheduling framework combining switch hardware with software-based compute platforms to meet the telemetry demands of future COIN-based applications.