Sap Se

Mitko Kolev

Markus Muenkel

Nedelcho Nedyalkov Delchev

Georgi Dimitrov Pavlov

Yordan Pavlov Pavlov

Daniel Ritter

Manuel Holzleitner

Stefan Opderbeck

Syed Muhammad Kumail Raza

Venkata Narayana Papineni

According to some embodiments, a central cloud-based repository of data may contain consolidated facts about enterprise applications. A computer processor of a discovery engine may execute discovery in a local application process and, based on the executed discovery, automatically create a generic structured set of facts from locally accessible data. The discovery engine may then store the generic structured set of facts in the central cloud-based data repository using a standard format (e.g., JSON). The central cloud-based data repository may, for example, store facts from different application instances and/or facts from different applications. According to some embodiments, a user generated query is created in a query language (e.g., SQL) and executed on the central cloud-based repository of data to automatically create an answer. Moreover, an automated ML agent may, in some embodiments, evaluate information in the central cloud-based repository of data.

Creation of structured set of facts via enterprise information discovery

Techniques and solutions are provided for identifying sets of related data, such as for a data deletion process. Data objects can be considered as having parent-child relationships, where values for one or more attributes of a child data object are constrained by corresponding one or more attributes of a parent data object. The set of data objects and their relationships can be represented, such as in a graph. In an iterative process, the data object representation is analyzed to identify 'leaf nodes,' which are data objects that do not constrain other data objects. Relevant data is deleted from the data objects, and the representation is updated to “remove” such data objects so that a new set of leaf nodes is obtained. Optionally, when a leaf node that serves as a parent is analyzed, it can be confirmed whether corresponding data has already been deleted from its children.

Timestamp-based deletions for interdependent data objects

The present disclosure relates to computer-implemented methods, software, and systems for lifecycle processing of declarative artifacts. Declarative artifacts defining a target state for application content related to a software application are read. When running, the software application includes runtime artifacts executing in a containerized environment. Model definition objects for processing during runtime of the software application based on the declarative artifacts are created and stored in a model repository at a container associated with the software application. The model repository is scanned as well as the runtime artifacts executing as part of the software application in the containerized runtime environment to identify a model definition object from the model repository for processing at runtime of the software application. An operation related to a runtime artifact to run as part of the running software application at the containerized runtime environment is executed based on input from the identified model definition object.

Processing framework for in-system programming in a containerized environment

A system and method to determine an event for an executing integration flow defining how messages are passed between a sender system and a receiver system; determine message processing states of messages of the integration flow before an event time; determine message processing states of messages of the integration flow after the event time; determine, based on an evaluation of failed message processing states for the messages before and after the event time, whether the event is associated with a problem; assign, in response to the determination that the event time is associated with a problem, one or more categories to the problem; and store a record of the assignment of the one or more categories to the problem.

Problem detection and categorization for integration flows

Methods and systems are used for providing a domain specific language (DSL) for a cloud hosted system with metric-based state. As an example, a first DSL query request including first DSL query input based on a DSL is received. The first DSL query input is translated to a first set of query instructions based on the first DSL query input, translation rules metadata, and the DSL. The first set of query instructions is executed to retrieve, for each cloud system of a plurality of cloud systems, metrics data associated with an application state of an application deployed on each cloud system stored in a cloud deployment repository. A first set of response output is computed by matching the retrieved metrics data from the cloud deployment repository to the first DSL query input. A first DSL query response including the first set of response output is transmitted to a client system.

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Walldorf, Germany

Mitko Kolev