Generating massive high quality synthetic observability data
US12321252B2 · kind B2 · utility
0Cited by
4References
20Claims
0Family size
Assignee
Inventors
Key dates
| Filing date | Aug 24, 2023 |
| Grant date | Jun 3, 2025 |
| Priority date | — |
| Expiry date | Oct 17, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F11/3466
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In several aspects for generation of high quality synthetic observability data for computing systems, traces and logs from a system are collected as a seed dataset. Multiple conditional variational autoencoder (VAE) models are trained using the seed dataset for learning association between the traces and the logs. Synthetic traces and logs are generated using the multiple CVAE models while retaining the association between the traces and the logs for the synthetic traces and logs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.