大规模云计算环境故障预测数据集

大规模云计算环境故障预测数据集是关于大规模云计算系统中基于系统日志的故障预测任务，它包含约30万个控制节点共约27亿条日志记录，由**云计算公司提供。数据集开放于亚太最大数据集管理平台——天池，目的是利用大规模的日志数据集研究基于统计学的故障预测算法，希望实现先进算法与实际生产环境接轨、实现故障预测问题与机器学习尤其是深度学习的交叉融合，促进云计算领域稳定性方向的发展和技术交流。

The Large-Scale Cloud Computing Environment Fault Prediction Dataset targets the fault prediction task based on system logs in large-scale cloud computing systems. It comprises approximately 300,000 control nodes and a total of around 2.7 billion log records, and is provided by a cloud computing company. Released on Tianchi, the largest dataset management platform in the Asia-Pacific region, this dataset aims to leverage its large-scale log data to study statistical fault prediction algorithms, bridge advanced algorithms with real-world production environments, achieve cross integration between fault prediction problems and machine learning (particularly deep learning), and promote the development and technical exchanges in the field of cloud computing stability.

搜集汇总

背景与挑战

背景概述

该数据集是一个专注于大规模云计算系统故障预测的日志数据集，包含约30万个控制节点和27亿条日志记录，旨在通过机器学习方法预测系统宕机风险。数据集提供了详细的训练和测试数据，包括原始日志、宕机时间和采样时间，并强调了类别不平衡、长尾分布等实际挑战，适用于研究先进算法与实际生产环境的结合。