Observability Is Eating Your Cores: Fine-Grained Analysis of Microservice Metrics with IPU-Hosted Sketches
Alessandro Cornacchia, Theophilus A. Benson, Muhammad Bilal, Marco Canini
摘要
Observability has become mission-critical for troubleshooting cloud-native technology. However, today's observability fails to meet the demands of cloud-native environments, either resulting in crippling complexity and high costs for collecting and storing huge data volumes, or sacrificing events coverage by sampling at coarse time granularity. We present µView, which stands out from conventional cloud monitors by incorporating a lightweight observability data-plane on Infrastructure Processing Units (IPUs). Our novel architecture leverages the proximity of IPUs to the monitored services to tackle observability bloat. Crucially, µView's data-plane applies streaming data sketching techniques to continuously process and analyze microservice's metrics at fine time resolution, without hurting application performance. We show for several use cases that by anticipating SLO violations µView can help (i) narrow the focus on informative observability data, and (ii) trigger useful signals about service performance, thus enabling timely proactive actions. Our code and artifacts are available at: https://github.com/sands-lab/uview.
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