Shared todayAIGC seriesIn-depth Research Report:AIGC Special Report: AIGC Helps Improve the Energy Efficiency of Large-Scale Object Storage Service (OSS).
Report produced by Global Software Development Conference).
Report total: 18 pages.
Scenario 1: Root cause analysis is done through AI to support the achievement of availability SLAs
Scenario 2: Background of a slow request for intelligent analysis and access to end-to-end trace
Scenario 3: Use NLP to analyze a large number of work orders to mine improvement directions
Fixed-point optimization for problems entering the work order system, measure the number of work orders and the time for work order resolution. Based on the classification of work order tags, expense tickets account for the largest proportionAnalyze the flow link, and reduce the service time by X timesThrough intelligent analysis, a lot of manual annotation overhead is saved.
Scenario 4: Exploring AIGC's intelligent bots to improve ease of use
Intelligent robots trained by AIGC use text to provide services to usersSolve problems through intelligent answers, reduce the number of work orders, reduce service manpower input, respond quickly at any time, solve problems, and improve ease of use.
Accumulating massive O&M data through DataOps is the only way to move towards AIOPS (Intelligent O&M).
High-frequency problems (root cause analysis, slow requests, work order optimization, etc.) can be used to achieve great benefits by using intelligent O&M.
AIOPS The road is long and the line is coming.
Report total: 18 pages.