Abstract: A digital twin of an IT infrastructure is created to identify a group of critical servers (called “base servers”) needed to replicate the IT infrastructure in a cloud-computing environment. To identify the correct base servers and their actual server configurations, the IT infrastructure is crawled and various telemetry, connection, and network data is analyzed against data sets of other known servers. The digital twin is created to include these base servers and their particular configurations. Then, the digital twin may be deployed on demand in the cloud-computing environment using executable scripts that mimic the base servers and their particular configurations, creating a replication of the IT infrastructure for various purposes (e.g., redundancy, testing, etc.).

Abstract: A digital twin of an IT infrastructure is created to identify a group of critical servers (called “base servers”) needed to replicate the IT infrastructure in a cloud-computing environment. To identify the correct base servers and their actual server configurations, the IT infrastructure is crawled and various telemetry, connection, and network data is analyzed against data sets of other known servers. The digital twin is created to include these base servers and their particular configurations. Then, the digital twin may be deployed on demand in the cloud-computing environment using executable scripts that mimic the base servers and their particular configurations, creating a replication of the IT infrastructure for various purposes (e.g., redundancy, testing, etc.).

Abstract: Methods and systems are provided for classifying free-text content using machine learning. Free-text content (e.g., customer feedback) and parameter values organized according to a schema are received. A free-text corpus is generated, and an artificial-text corpus is generated by applying rules to the parameter values. The artificial-text corpus is generated by converting the parameter values into a finite set of words based on the rules and concatenating the words of the finite set of words into a fixed sequence wordlist. Feature vectors (e.g., sentence embeddings) based on the free-text corpus and the artificial-text corpus are combined and forwarded to a machine learning model for classification. The machine learning model may be trained with a bias towards a specified metric (e.g., precision, recall, F1 score). The model may be trained using transfer learning with training data from a different category of free-text content (e.g., a different category of customer feedback).

Abstract: A digital twin of an IT infrastructure is created to identify a group of critical servers (called “base servers”) needed to replicate the IT infrastructure in a cloud-computing environment. To identify the correct base servers and their actual server configurations, the IT infrastructure is crawled and various telemetry, connection, and network data is analyzed against data sets of other known servers. The digital twin is created to include these base servers and their particular configurations. Then, the digital twin may be deployed on demand in the cloud-computing environment using executable scripts that mimic the base servers and their particular configurations, creating a replication of the IT infrastructure for various purposes (e.g., redundancy, testing, etc.).

Abstract: A digital twin of an IT infrastructure is created to identify a group of critical servers (called “base servers”) needed to replicate the IT infrastructure in a cloud-computing environment. To identify the correct base servers and their actual server configurations, the IT infrastructure is crawled and various telemetry, connection, and network data is analyzed against data sets of other known servers. The digital twin is created to include these base servers and their particular configurations. Then, the digital twin may be deployed on demand in the cloud-computing environment using executable scripts that mimic the base servers and their particular configurations, creating a replication of the IT infrastructure for various purposes (e.g., redundancy, testing, etc.).