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Sage: Practical & Scalable ML-Driven Performance Debugging in Microservices

Cloud applications are increasingly shifting from large monolithic services to complex graphs of loosely-coupled microservices. Despite the advantages of modularity and elasticity microservices offer, they also complicate cluster management and …

Sage: Leveraging ML To Diagnose Unpredictable Performance in Cloud Microservices

Cloud applications are increasingly shifting from large monolithic services, to complex graphs of loosely-coupled microservices. Despite their advantages, microservices also introduce cascading QoS violations in cloud applications, which are …

Leveraging Deep Learning to Improve Performance Predictability in Cloud Microservices with Seer

Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. Predictable performance is even more critical as cloud services transition from monolithic designs to microservices. …

An Open-Source Benchmark Suite for Microservices and Their Hardware-Software Implications for Cloud and Edge Systems

Cloud services have recently started undergoing a major shift from monolithic applications, to graphs of hundreds of loosely-coupled microservices. Microservices fundamentally change a lot of assumptions current cloud systems are designed with, and …

Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices

Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. Predictable performance is even more critical as cloud services transition from monolithic designs to microservices. …

μqSim: Enabling Accurate and Scalable Simulation for Interactive Microservices

Current cloud services are moving away from monolithic designs and towards graphs of many looselycoupled, single-concerned microservices. Microservices have several advantages, including speeding up development and deployment, allowing specialization …

Seer: Leveraging Big Data to Navigate the Increasing Complexity of Cloud Debugging

Performance unpredictability in cloud services leads to poor user experience, degraded availability, and has revenue ramifications. Detecting performance degradation a posteriori helps the system take corrective action, but does not avoid the QoS …

Incentive Attack Prevention for Collaborative Spectrum Sensing: A Peer-Prediction Method

Collaborative spectrum sensing is an effective method to improve the detection rate in cognitive radio. However, it is vulnerable to spectrum sensing data falsification attacks. In order to improve the robustness, numerous attack prevention schemes …