Sap Se

Venkatesh Iyengar

Harish Kumar Sampangi Rama

Abhradeep Kundu

Amarendu Singh

Sudhakar Bommenahalli Ramamurthy

Sriram Narasimhan

Vengateswaran Chandrasekaran

Panish Ramakrishna

Heshang Majmudar

Vinay Santurkar

Amit Joshi

A method may include receiving, at a data lake platform, a packet including a metadata corresponding to a data schema of a source system. A change in the data schema of the source system may be detected based on a first checksum of the metadata and a second checksum of a previous version of the metadata. In response to detecting the change in the data schema of the source system, the metadata may be sent to a target system to enable the target system to perform, based on the data schema of the source system, a task operating on a data from the source system. The task may include reporting, visualization, advanced analytics, and/or machine learning. Related systems and computer program products are also provided.

Metadata synchronization for cross system data curation

A method may include allocating, based on a first load requirement of a first tenant, a first bin having a fixed capacity for handing the first load requirement of the first tenant. In response to the first load requirement of the first tenant exceeding a first threshold of the fixed capacity of the first bin, packing a second bin allocated to handle a second load requirement of a second tenant. The second bin may be packed by transferring, to the second bin, the first load requirement of the first tenant based on the transfer not exceeding the first threshold of the fixed capacity of the second bin. In response to the transfer exceeding the first threshold of the fixed capacity of the second bin, allocating a third bin to handle the first load requirement of the first tenant.

Data curation with capacity scaling

A method, a system, and a computer product for connecting computing components are disclosed. One or more data input and output properties of a data processing component in a plurality of data processing components are determined. At least one of the data input properties and data output properties of the data processing component are configured for connection of the data processing component to another data processing component in the plurality of data processing components in the data processing pipeline using a predetermined data pipeline connection topology. Using the predetermined data pipeline connection topology, the data processing component and another data processing component are dynamically connected using the configured properties.

Data pipeline using a pluggable topology connecting components without altering code of the components

In some embodiments, there may be provided a system. The system may be configured to receive web server data indicating a current state of a web server; determine, by a machine learning model and based on the web server data, whether the web server is in a first failure state; generate a first failure state indication for the web server in response to the determination, by the machine learning model, that the web server is in the first failure state; determine, by a forecaster and based on the web server data, whether the web server is in a second failure state; and generate a second failure state indication for the web server in response to the determination, by the forecaster, that the web server is in the second failure state.

Reinforced machine learning tool for anomaly detection

A method may include segregating an event stream that includes events associated with a cloud-based application hosted on a first remote resource and a second remote resource. The events may include metrics indicative of a state of the first remote resource and/or the second remote resource. The event stream may be segregated into a first child stream including events associated with the first remote resource and a second child stream including events associated with the second remote resource. The first child stream and/or the second child stream may be analyzed to identify a pattern indicative of a fault at the first remote resource and/or the second remote resource. An alert may be sent to in order to notify a client of the fault at the first remote resource and/or the second remote resource. Related systems and articles of manufacture are also provided.

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Bengaluru, India

Venkatesh Iyengar