SOL: safe on-node learning in cloud platforms

Abstract

Cloud platforms run many software agents on each server node. These agents manage all aspects of node operation, and in some cases frequently collect data and make decisions. Unfortunately, their behavior is typically based on pre-defined static heuristics or offline analysis; they do not leverage on-node machine learning (ML). In this paper, we first characterize the spectrum of node agents in Azure, and identify the classes of agents that are most likely to benefit from on-node ML. We then propose SOL, an extensible framework for designing ML-based agents that are safe and robust to the range of failure conditions that occur in production. SOL provides a simple API to agent developers and manages the scheduling and running of the agent-specific functions they write. We illustrate the use of SOL by implementing three ML-based agents that manage CPU cores, node power, and memory placement. Our experiments show that (1) ML substantially improves our agents, and (2) SOL ensures that agents operate safely under a variety of failure conditions. We conclude that ML-based agents show significant potential and that SOL can help build them. CCS CONCEPTS• Computer systems organization → Other architectures; Cloud computing; • Software and its engineering → Software creation and management.

Exploring the Innovative Application of Azure Cloud Computing Platform in Cross-border E-commerce Operation

“…Its flexible and scalable features make it an important tool for Cross-border E-commerce enterprises around the world to support and expand their business operations [6] [7]. The main functions of Azure are mainly focused on big data processing, machine learning, data analysis, and application development [8] [9].…”

“…In terms of data analysis, Azure provides a series of powerful analysis tools, such as Power BI. These tools can help Cross-border E-commerce enterprises to extract valuable information from massive data, realize intelligent decisionmaking, and improve customer satisfaction and business operation efficiency [6] [8].…”

“…Therefore, the Azure cloud computing platform has shown its powerful functions in processing large-scale data and providing machine learning and data analysis tools, especially in Cross-border E-commerce [7] [8]. Its depth and breadth of service capabilities enable enterprises to process and analyze massive data flexibly, thus providing strong support for business operations and decision-making [7] [9].…”