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Intelligent Software Engineering for Reliable Cloud Operations

In: System Dependability and Analytics

Author

Listed:
  • Michael R. Lyu

    (The Chinese University of Hong Kong)

  • Yuxin Su

    (Sun Yat-sen University)

Abstract

Reliable Cloud operations are vital to our daily lives because many popular modern software systems are deployed in cloud systems. In this chapter, we discuss our experience in developing an AIOps (Artificial Intelligence for IT Operations) framework to improve the reliability of large-scale cloud systems with intelligence software engineering techniques. The comprehensive AIOps framework includes anomaly detection of key performance indicators, service dependency mining for failure diagnosis, and system incident aggregation for root cause analysis from various information sources like meter data, topology, alert, and incident tickets. We also conduct extensive experiments with production data collected from large-scale Huawei Cloud systems to demonstrate the effectiveness of intelligent software engineering techniques for reliable cloud operations.

Suggested Citation

  • Michael R. Lyu & Yuxin Su, 2023. "Intelligent Software Engineering for Reliable Cloud Operations," Springer Series in Reliability Engineering, in: Long Wang & Karthik Pattabiraman & Catello Di Martino & Arjun Athreya & Saurabh Bagchi (ed.), System Dependability and Analytics, pages 7-37, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-02063-6_2
    DOI: 10.1007/978-3-031-02063-6_2
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