Cisco Technology, Inc.

Hewlett-packard Development Company, L.P.

Ahmed Khattab

Antonio Nucci

Carlos M Pignataro

Richard Montgomery Plane

Samudra Harapan Bekti

Duen-Uei D Chen

Prasad Potipireddi

Alexander Sasha Stojanovic

Hazim Hashim Dahir

Alex Van Truong

Daniel Scott Jorgenson

Kathleen M Cox

Kumarappan Palaniappan

Dragan Milosavljevic

Christopher John Hoffman

Nirmaladevi Kulandaivelu

Thomas M Graefe

Fabrizio Mancuso

Ping Pamela Tang

Ravi K Papisetti

Athena Wong

Kaouther Abrougui

John Oberon

Firas Fawzi Ahmed

Joseph Gerard Moffat

Richard Paul Kane

Each module of a plurality of modules receives intent metadata associated with a data product instance of a data mesh. Each module corresponds to a unique data governance category of a plurality of data governance categories and a request associated with data was intercepted at the data product instance. Each module receives policy metadata associated with the data governance category corresponding to the module. Each modules determines, based on the intent metadata and the policy metadata, whether the request is valid for the data governance category corresponding to the module. Each modules transmits an indication of whether the request is valid for the module.

Intent-based enterprise data management for simplified data governance

A Services Delivery Platform (SDP) architecture is provided that is configured to onboard new data sets into an SDP data lake. The SDP enables the crowdsourcing of data on-boarding by configuring this process into an interactive, intuitive, step-by-step guided workflow while governing/controlling key functions like verification, acceptance and execution.

Crowdsourcing data into a data lake

Presented herein are methods associated with a Services Delivery Platform (SDP) architecture for a distributed application building blocks, such as microservices, deployment-agnostic. The system includes a central compute node and numerous remote compute nodes. Techniques are provided to 'onboard' and assimilate the capabilities of remote compute nodes so that they are an integrated part of the SDP system and can be accessed and used in connection with one or more services provided by the SDP system.

Automatically and remotely on-board services delivery platform computing nodes

Systems, methods, and computer-readable media for identifying an optimal cluster configuration for performing a job in a remote cluster computing system. In some examples, one or more applications and a sample of a production load as part of a job for a remote cluster computing system is received. Different clusters of nodes are instantiated in the remote cluster computing system to form different cluster configurations. Multi-Linear regression models segmented into different load regions are trained by running at least a portion of the sample on the instantiated different clusters of nodes. Expected completion times of the production load across varying cluster configurations are identified using the multi-linear regression models. An optimal cluster configuration of the varying cluster configurations is determined for the job based on the identified expected completion times.

Cost-optimal cluster configuration analytics package

A system comprises a business entitlement object, a primary account associated with a first user, wherein the primary account is linked to the business entitlement object, a secondary user condition defined by the first user, and a first secondary account, wherein a second user links the first secondary account to the business entitlement object according to the secondary user condition.

System and method for linking user accounts to business entitlement objects

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San Jose, CA, United States of America

Ahmed Khattab