Vmware, Inc.

Aayush Asawa

Akshay Bhandari

Rachil Chandran

Karthik Seshadri

Shrisha Chandrashekar

Tyler J Curtis

Radhakrishnan Devarajan

Gaurav Gupta

Ritesh Ranjan Jha

Shubham Verma

Gopal Gorthi

Satish Anumalasetty

Methods, apparatus, systems and articles of manufacture to establish a data pipeline between cloud computing platforms. An apparatus includes at least one memory, machine readable instructions in the apparatus, and processor circuitry to execute the machine readable instructions to at least extract a data producer name from data, the data to be provided from a data producer to a data consumer, identify a buffer identifier based on a mapping of the data producer name to the buffer identifier, cause transmission of the data to a buffer associated with the buffer identifier, and cause transmission of the data from the buffer to the data consumer based on an association between the buffer identifier and a data consumer name, the data consumer name corresponding to the data consumer.

Methods and apparatus for data pipelines between cloud computing platforms

Methods, apparatus, systems and articles of manufacture are disclosed to establish a data pipeline between cloud computing platforms. An apparatus includes a producer registration controller to register a data producer with a data pipeline service in a public cloud network, the data producer associated with a private cloud network, a consumer registration controller to register a data consumer with the data pipeline service, and a communication controller to, in response to the registration of the data consumer, transmit data generated by the public cloud network from the data consumer to the data buffer via a first data plane gateway, and, in response to a validation of the data consumer, transmit the data from the data buffer to the data consumer via a second data plane gateway, the first data plane gateway different from the second data plane gateway.

Embodiments disclosed herein relate to a method, system, and computer-readable medium for monitoring an application executing across a plurality of containers. A performance monitor requests a list of containers created on at least one computing system. The performance monitor retrieves information associated with a creation of each container in the list. The performance monitor parses the information associated with each container in the list to identify a cluster of related containers that are running the applications. The performance monitor displays a topology that relates the containers of the cluster to resources in the at least one computing system. The performance monitor identified a pair of containers that are negatively correlated based on the topology. The performance monitor adjusts the application to remove the negative correlation between the pair of containers.

Monitoring applications running on containers

Embodiments disclosed herein relate to a method, system, and computer-readable medium for monitoring an application executing across a plurality of containers on a computing system. A performance monitor requests a list of containers created on the computing system. The performance monitor retrieves information associated with a creation of each container in the list. The performance monitor parses the information associated with each container in the list to identify a cluster of related containers that are running the applications. The performance monitor associates the cluster of related containers with the application. The performance monitor assesses a health of the application based on metrics collected from the identified cluster of containers.

Various examples are disclosed for predictive allocation of computing resources in a virtual desktop infrastructure environment. A computing environment can generate a predictive usage model as a time series that forecasts a usage of virtual machines that provide virtual desktop sessions in a virtual desktop infrastructure environment. The computing environment can determine a number of the plurality of virtual machines that will be operating at a future time utilizing the predictive usage model and identify computing resources required for the number of the virtual machines to operate at the future time. The computing environment can allocate the computing resources such that the computing resources are available at the future time.

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Bengaluru, India

Aayush Asawa