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Title: BurstRadar: Practical real-time microburst monitoring for datacenter networks
Authors: JOSHI RAJ 
Qu, Ting
Leong Wing Lup,Ben 
Loo, B.T.
Keywords: Networks
Issue Date: 27-Aug-2018
Publisher: Association for Computing Machinery, Inc
Citation: JOSHI RAJ, Qu, Ting, CHAN MUN CHOON, Leong Wing Lup,Ben, Loo, B.T. (2018-08-27). BurstRadar: Practical real-time microburst monitoring for datacenter networks. Proceedings of the 9th Asia-Pacific Workshop on Systems, 2018. ScholarBank@NUS Repository.
Related Datasets: 10.1145/3265723.3265731
Abstract: Microbursts can degrade application performance in datacenters by causing increased latency, jitter and packet loss. The detection of microbursts and identification of the contributing flows is the first step towards mitigating this problem. Unfortunately, microbursts are unpredictable and typically last for 10’s or 100’s of μs. The high line rates (> 10 Gbps) in modern datacenter networks further exacerbate the problem. In this paper, we show that modern programmable switching ASICs have made it practical to detect and characterize microbursts at multi-gigabit line rates. Our system, called BurstRadar, operates in the dataplane and monitors microbursts by capturing the telemetry information for only the packets involved in microbursts. We have implemented a prototype of BurstRadar on a Barefoot Tofino switch using the P4 programming language. Our evaluation on a multigigabit testbed using microburst traffic distributions from Facebook’s production network shows that BurstRadar incurs 10 times less data collection and processing overhead than existing solutions. Furthermore, BurstRadar can handle simultaneous microburst traffic on multiple egress ports while consuming very few resources in the switching ASIC.
Source Title: Proceedings of the 9th Asia-Pacific Workshop on Systems, 2018
ISBN: 9781450360067
DOI: 10.1145/3265723.3265731
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