What is it about?
The finer-granularity of microservices facilitate their evolution and deployment on shared resources. However, resource concurrency creates elusive interdependencies, which can cause complex interference patterns to propagate in the form of performance anomalies across distinct applications. Meanwhile, the existing methods for Anomaly Detection (AD) and Root-Cause Analysis (RCA) are confounded by this phenomenon of interference because they operate within single call-graphs. To bridge this gap, we develop a graph formalism (Spatio-Temporal Interference Graph - STIG) to express interference patterns and an artifact to simulate their dynamics. Our simulator contributes to the study and mitigation of interference patterns as a performance phenomenon that emerges from regular resource consumption anomalies.
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Why is it important?
Our approach overcomes these limitations by formulating the interference phenomenon as a spatio-temporal graph. Our corresponding simulation helps mitigate the probability and impact of the interference phenomenon by de-confounding the diagnostics from the AD, RCA, and IM methods,
Perspectives
We contribute with (1) a formalism to capture interference patterns as spatio-temporal graphs (STIG), (2) a simulator called STIGS (Figure 2) for generating interference patterns, and (3) a practical evaluation with three popular microservice benchmarks.
Iqra Zafar
Hasso-Plattner-Institute (HPI) , Potsdam, DE
Read the Original
This page is a summary of: STIGS: Spatio-Temporal Interference Graph Simulator for Self-Configurable Multi-Tenant Cloud Systems, May 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3629527.3653664.
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