Self-Healing in Large-Scale Datacenters

AIHS - Automated intelligent healing system for cloud-scale data centers using machine learning

AIHS (Automated Intelligent Healing System) represents a breakthrough in applying machine learning to achieve scalable self-healing in cloud-scale data centers. This research addresses the critical challenge of automatically detecting and repairing component failures in large-scale cloud infrastructure, achieving remarkable success rates in production environments.

Research Objectives

The primary goal is to enable reliable and scalable cloud services through:

  • Automated Failure Detection: Real-time monitoring and early warning systems
  • Intelligent Diagnosis: Machine learning-based root cause analysis
  • Automated Recovery: Self-healing mechanisms for common failure scenarios
  • Production Scalability: Deploying ML solutions at cloud scale

Technical Approach

AIHS employs a comprehensive ML pipeline:

Machine Learning Pipeline

  • Raw Log Analysis: Processing monitoring logs using NLP and time-series analysis
  • Pattern Recognition: Identifying failure patterns and correlations
  • Predictive Modeling: Forecasting potential failures before they occur
  • Action Recommendation: Suggesting optimal repair strategies

System Integration

  • Cloud Infrastructure: Deep integration with Alibaba Cloud management systems
  • Distributed Processing: Handling large-scale, distributed infrastructure
  • Real-time Operations: Continuous monitoring and automated response
  • AIOps Workflows: Automated operations and maintenance processes

Key Outcomes

This research has achieved:

  • 92.4% success rate in resolving 33.7 million production failures
  • 51% reduction in unavailable time per failed server
  • Publication at SRDS 2021 (25.5% acceptance rate)
  • Production deployment at Alibaba with 600K+ servers
  • “Best Newcomer Award of AIS” recognition

Impact

AIHS demonstrates the potential of AIOps in production:

  • Reliability Improvement: Significantly enhanced system uptime and availability
  • Cost Reduction: Lower maintenance costs and reduced manual intervention
  • Scalability: Proven ML solutions for cloud-scale infrastructure
  • Industry Adoption: Open-source prototype for public validation
  • Automated Intelligent Healing for Cloud-Scale Data Centers (SRDS 2021)
AIHS system architecture showing the machine learning pipeline for automated failure detection and repair in cloud-scale data centers.