Accurate and Predictable Scoring for Hardware Contention in Microservices

This talk presents a practical approach to quantifying and forecasting hardware contention in microservices so mitigation can happen before SLO violations. It motivates why contention remains underappreciated in containerized systems, introduces a general contention score (0-1) designed around four properties (correlation with latency degradation, sharp rise, slow decay, and predictability), and describes the Gordion pipeline: workload/stress generation (wrk2 + stress-ng), multi-layer instrumentation (within-service gRPC timing plus perf counters), score labeling, and ML-based next-step prediction. The evaluation highlights both usefulness and deployability, including competitive prediction quality and low runtime overhead near saturation (about 1% mean and 8% P90 at 500 RPS). Slides: (Industry) Accurate and Predictable Scoring for Hardware Contention in Microservices.