A Blueprint of Log Based Monitoring and Diagnosing Framework in Large Distributed Environments

Abstract

Distributed systems have kept scaling upward since this concept appears, and they soon evolve to environments that contain heterogeneous components playing different roles, making it difficult to understand how the large environment works or if any undesired matters happened from security point of view. Logs, produced by devices, sub-systems and running processes, are a very important source to help system maintainers to get relative security knowledge. But there are too many logs and too many kinds of logs to deal with, which makes manual checking impossible. In this work we will share some of our experiences in log processing and analyzing. We have summarized some common major steps that appear in most of the existing log analysis approaches, including log selection, log classification, information analyses and result feedback. We also represent a general framework that monitors events, analyzes hidden information and diagnoses the healthy state for large distributed computing environments bases on logs. Although the framework we initially designed was for the maintenance for CNGrid, its process is adaptable to other distributed computing environments.