Hewlett Packard Enterprise Development LP

Prabhu Murthy

Jyoti Ranjan

Rijil Abraham

Abhishek Kumar

Paul Michael Murray

Ajay Kumar Bajaj

Siddhartha Singh

Chandrasekaran Natarajan

Anusha Chaparala

Example techniques for execution of functions by clusters of computing nodes are described. In an example, if a cluster does not have resources available for executing a function for handling a service request, the cluster may request another cluster for executing the function. A result of execution of the function may be received by the cluster and used for handling the service request.

Execution of functions by clusters of computing nodes

A technique includes accessing, by a computer, a container image that is built at least in part inside a virtual machine instance; and accessing, by the computer, an image of the virtual machine instance. Pursuant to the technique, the container image and the image of the virtual machine instance are scanned for security issues; and a result of the scanning is displayed by the computer.

Scanning container images and objects associated with building the container images

Embodiments described herein are generally directed to testing a microservice to determine whether the microservice leaks sensitive information. According to an example, prior to deployment of a microservice within a production environment, a test suite for the microservice is generated based at least in part on a specification of an application programming interface (API) of the microservice defining operations supported by the API and information regarding parameters of each of the operations. The microservice is subjected to the test suite. A potential security leak by the microservice is then detected by analyzing a dataset to which the microservice outputs information, including applying security rules to the dataset.

Detecting a potential security leak by a microservice

Example implementations relate to determining and implementing a feasible resource optimization plan for public cloud consumption. Telemetry data over a period of time is obtained for a current deployment of virtual infrastructure resources within a current data center of a cloud provider that supports an existing service and an application deployed on the virtual infrastructure resources. Information regarding a set of constraints to be imposed on a resource optimization plan is obtained. Indicators of resource consumption relating to the currently deployed virtual infrastructure resources during the period of time are identified by applying a deep learning algorithm to the telemetry data. A resource optimization plan is determined that is feasible within the set of constraints based on a costing model associated with resources of an alternative data center of the cloud provider, the indicators of resource consumption and costs associated with the current deployment.

Determining and implementing a feasible resource optimization plan for public cloud consumption

A system to facilitate a container orchestration cloud service platform is described. The system includes a controller to manage Kubernetes cluster life-cycle operations created by each of a plurality of providers. The controller includes one or more processors to execute a controller micro service to discover a provider plugin associated with each of the plurality of providers, and perform the cluster life-cycle operations at a container orchestration platform as a broker for each of a plurality of providers.

Unified container orchestration controller

Examples described herein relate to method and an issue management system for handling issues reported from network devices. The issue management system may receive an issue from a network device of a plurality of network devices arranged in one or more computing environments. The issue management system may determine whether there exists a solution corresponding to the issue in a solution repository based on the issue and a knowledge base. Further, in response to determining that there exists the solution corresponding to the issue, the issue management system may communicate the solution to a computing environment of the one or more computing environments that hosts the network device reporting the issue. Alternatively, if there exists no solution corresponding to the issue, the issue management system may relay the issue to a management station for the management station to address the issue.

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Bengaluru, India

Prabhu Murthy