Abstract: A computer-implemented method for receiving a first set of resource allocation data related to a first set of SRE tools and predicting a first state of a cloud environment based on the first set of resource allocation data. The method further includes switching the cloud environment to a second set of SRE tools based on the first state of the cloud environment. In embodiments, the method further includes receiving a second set of resource allocation data related to the second set of SRE tools and predicting a second state of the cloud environment based on the second set of resource allocation data. In embodiments, the method also includes switching the cloud environment to the first set of SRE tools based on the second state of the cloud environment.

Abstract: A data governance system includes a signet template generator engine, a signet specification enforcement, and a pattern based signet controller. The signet template generator engine generates a signet template by applying at least one signet to raw data received from a data producer. The at least one signet is designated with a consent level and includes at least one data field designated with a consent identifier. The signet specification enforcement engine analyzes the consent level of the at least one signet and the consent identifier of the at least one data field, and outputs first filtered data based on the consent identifier of the at least one data field. The pattern based signet controller generates second filtered data based on the consent level of the at least one signet, and outputs a combination of the first filter data and the second filtered data as final data.

Abstract: A computer-implemented method including: collecting, by a computing device, specification documentation of a product and drift data of the product during a product lifecycle; analyzing, by the computing device, the specification documentation and the drift data of the product to identify anomalies between the specification documentation and the drift data of the product during different stages of the product lifecycle; computing, by the computing device, a score of each of the identified anomalies; recommending, by the computing device, solutions to fix selected anomalies based on their score and by using content-based recommendations; and displaying the recommended solutions to an end-user in a dashboard.

Abstract: A computer-implemented method may include determining, by a computing device, a verve of a feature; determining, by a computing device, a first release intensity score (RIS) of the feature; stabilizing, by a computing device, a release train based on the verve and the RIS of the feature; and modifying, by a computing device, an engagement schedule based on the stabilized release train.

Abstract: A computer implemented method and system for supporting self-assessed upgrades using dynamic benchmarking of combinations of main and sub libraries for carrying out Library Developer Operations (LibOps) includes identifying a software library module being used in a software application, identifying dependencies and upgrades for the software library module, identifying a latest software library module version, identifying a change.log module for the latest software library module version, wherein the change.log module includes a record of all changes to the software library module, categorizing breaking changes and deprecated features for the latest software library module version and generating an upgrade score and suggesting recommendations responsive to the upgrade score.

Abstract: A computer-implemented method, according to one embodiment, includes causing a trained artificial intelligence (AI) model to derive data access privilege grants before data is stored in a predetermined database, and segmenting the data according to the data access privilege grants during storage of the data in the predetermined database. Metadata that defines the data access privilege grants is stored with the segments of data. The method further includes receiving, from a first user device, a query requesting data stored in the predetermined database. At least some of the metadata is read to identify a segment of the data associated with a data access privilege grant associated with the query. The method further includes allowing the first user device to access the identified segment of data for fulfilling the query.

Abstract: A computer-implemented method, including: receiving, by a computing device, an information technology (IT) operations request; collecting, by the computing device, information associated with the IT operation request from a knowledge bank; determining, by the computing device, a resolution resource for completing the IT operation request; and assigning, by the computing device, the resolution resource based on the information from the knowledge bank and IT operation request.

Abstract: A computer-implemented method, in accordance with one embodiment, includes collecting data relating to development of a software product, the collected data including a plurality of different types of data relating to the development of the software product. A portion of the collected data is selected based on a characteristic of an intended user, the portion of the collected data including a plurality of the types of data. The selected portion of the collected data is transformed into data visualizations representing the data, the different types of the data having different data visualizations relative to one another. The data visualizations are output in a single visual representation for display to the intended user.

Abstract: An approach is disclosed that receives a user activity from a user that is using a datastore visualization display. The display displays a first visualization pertaining to one or more datastores with the datastore visualization display provided at least in part by a context driven lateral artificial intelligence (CDLAI) engine. The received user activity is provided as input to the CDLAI to generate a second visualization that is displayed to the user at the datastore visualization display that is displayed to the user. Artificial intelligence (AI) models that are used by the CDLAI are then trained based on the received user activity. The training results in updates to the visualizations.

Abstract: A computer-implemented method, in accordance with one aspect of the present invention, includes collecting data existing in a development system that relates to the code change request, in response to receiving a code change request to merge new code with existing code. Factors from the collected data are computed for assessing a risk of promoting the new code, the factors including at least: a developer information factor, a developer availability factor, and an environment health analysis factor. The factors are processed to compute a confidence score for the code change request. If the confidence score is in a first predefined range, the new code corresponding to the code change request is promoted for merging with the existing code, without human intervention. If the confidence score is in a second predefined range, an indication that human intervention is needed before promoting the code is output.

Abstract: A computer-implemented method, in accordance with one aspect of the present invention, includes collecting data existing in a development system that relates to the code change request, in response to receiving a code change request to merge new code with existing code. Factors from the collected data are computed for assessing a risk of promoting the new code, the factors including at least: a developer information factor, a developer availability factor, and an environment health analysis factor. The factors are processed to compute a confidence score for the code change request. If the confidence score is in a first predefined range, the new code corresponding to the code change request is promoted for merging with the existing code, without human intervention. If the confidence score is in a second predefined range, an indication that human intervention is needed before promoting the code is output.

Abstract: A computer-implemented method, according to one embodiment, includes causing a trained artificial intelligence (AI) model to derive data access privilege grants before data is stored in a predetermined database, and segmenting the data according to the data access privilege grants during storage of the data in the predetermined database. Metadata that defines the data access privilege grants is stored with the segments of data. The method further includes receiving, from a first user device, a query requesting data stored in the predetermined database. At least some of the metadata is read to identify a segment of the data associated with a data access privilege grant associated with the query. The method further includes allowing the first user device to access the identified segment of data for fulfilling the query.

Abstract: In one general embodiment, a computer-implemented method includes collecting information relating at least to market trends and problem ticketing. The collected information is stored in a knowledge repository. At least some of the collected information is processed to compute weightage scores for requirements specified in a policy configuration. A list comprising at least some of the requirements and indications of the weightage scores corresponding thereto is generated and output.

Abstract: A computer-implemented method, in accordance with one embodiment, includes collecting data relating to development of a software product, the collected data including a plurality of different types of data relating to the development of the software product. A portion of the collected data is selected based on a characteristic of an intended user, the portion of the collected data including a plurality of the types of data. The selected portion of the collected data is transformed into data visualizations representing the data, the different types of the data having different data visualizations relative to one another. The data visualizations are output in a single visual representation for display to the intended user.

Abstract: A computer-implemented method, in accordance with one embodiment, includes collecting data relating to development of a software product, the collected data including a plurality of different types of data relating to the development of the software product. A portion of the collected data is selected based on a characteristic of an intended user, the portion of the collected data including a plurality of the types of data. The selected portion of the collected data is transformed into data visualizations representing the data, the different types of the data having different data visualizations relative to one another. The data visualizations are output in a single visual representation for display to the intended user.