Summary of Anomaly Detection For Incident Response at Scale, by Hanzhang Wang et al.
Anomaly Detection for Incident Response at Scale
by Hanzhang Wang, Gowtham Kumar Tangirala, Gilkara Pranav Naidu, Charles Mayville, Arighna Roy, Joanne Sun, Ramesh Babu Mandava
First submitted to arxiv on: 24 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary We introduce AI Detect and Respond (AIDR), a machine learning-based anomaly detection product that monitors Walmart’s business and system health in real-time. The solution utilizes a combination of statistical, ML, and deep learning models to detect anomalies, along with rule-based static thresholds for domain-specific knowledge incorporation. AIDR is deployed through distributed services for scalability and high availability, featuring both univariate and multivariate ML models. The product includes a feedback loop that assesses model quality using drift detection algorithms and customer feedback, as well as self-onboarding capabilities and customizability. During validation, AIDR served predictions from over 3000 models to more than 25 teams, covering 63% of major incidents, reducing mean-time-to-detect (MTTD) by over 7 minutes. The solution has achieved success with various internal teams, showing lower time to detection and fewer false positives compared to previous methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine a system that can quickly spot when something goes wrong in Walmart’s business and technology systems. This is what AI Detect and Respond (AIDR) does! AIDR uses special computer programs called machine learning models to analyze data and find problems before they become big issues. It even takes into account the unique things that happen in each area of the business, so it can be more accurate. AIDR has already shown how effective it is by helping teams detect and fix problems faster than before. |
Keywords
» Artificial intelligence » Anomaly detection » Deep learning » Machine learning
