Hewlett Packard Enterprise Development LP

Bluedata Software, Inc.

Swami Viswanathan

Joel Baxter

Xiongbing Ou

Thomas A Phelan

Michael J Moretti

Gunaseelan Lakshminarayanan

Kartik Mathur

Vadim Finkelstein

Christopher M Crawford

Richard B Peterson

Thomas M Kelley

Alok Daipuria

Elias S Alagna

Rohan Jayaraj

Randy Thomasson

Krishna C Sagiraju

Lakshminarayanan Gunaseelan

Lakshm Inarayanan Gunaseelan

Xionbing Ou

Embodiments described herein are generally directed to a containerized application software deployment architecture. According to an example, a system includes multiple hosts that are part of aa stretch cluster spanning multiple data centers. Each of the hosts include a processing resource, a memory, and a storage device. Each host of a first subset of the multiple hosts runs multiple containerized instances of a component of a Security Information and Event Management (SIEM) application within respective containers. At least one host of the multiple hosts is separate from the first subset and is dedicated to running at least one containerized ingress gateway application operable to load balance requests directed to the SIEM application among the multiple containerized instances running on the first subset of hosts.

Infrastructure for deploying a security information and event management application on a container platform

Example implementations relate to a role-based autoscaling approach for scaling of nodes of a stateful application in a large scale virtual data processing (LSVDP) environment. Information is received regarding a role performed by the nodes of a virtual cluster of an LSVDP environment on which a stateful application is or will be deployed. Role-based autoscaling policies are maintained defining conditions under which the roles are to be scaled. A policy for a first role upon which a second role is dependent specifies a condition for scaling out the first role by a first step and a second step by which the second role is to be scaled out in tandem. When load information for the first role meets the condition, nodes in the virtual cluster that perform the first role are increased by the first step and nodes that perform the second role are increased by the second step.

Autoscaling nodes of a stateful application based on role-based autoscaling policies

Described herein are systems, methods, and software to enhance the management of virtual nodes in a computing environment. In one example, a system is configured to mount storage repositories to a host. Once mounted the system may identify a request to initiate a virtual cluster on the host and may identify permissions associated with the virtual cluster. The system further determines at least one storage repository from the storage repositories for the virtual cluster based on the permissions and initiate execution of the virtual cluster with access to at least one file system corresponding to the at least one storage repository.

Enhanced management of storage repository availability in a virtual environment

Described herein are systems, methods, and software to migrate virtual nodes of a data processing cluster. In one implementation, a management system monitors an executing data processing cluster on one or more first hosts to determine when the data processing cluster satisfies migration criteria. Once satisfied, the management system selects one or more second hosts to support the data processing cluster based on accommodation data associated with the hosts. After selection, the management system may initiate operations to migrate the data processing cluster from the one or more first hosts to the one or more second hosts.

Enhanced migration of clusters based on data accessibility

Described herein are systems, methods, and software to enhance the management of virtual nodes in a computing environment. In one example, a method includes identifying a transition event for a first version of a virtual node executing on a first host, identifying a second host to support a second version of the virtual node, and initiating execution of the second version of the virtual node on the second host. In some implementations, the virtual node comprises a non-persistent portion on the executing host and a persistent portion on a second storage element.

Enhanced data storage and versioning of virtual nodes in a data processing environment

Enhanced data storage of virtual nodes in a data processing environment

Systems, methods, and software described herein facilitate the management of virtual clusters in a large-scale processing environment. In one implementation, a method of operating a control node includes receiving a request to configure a virtual cluster with one or more data processing nodes, and identifying a tenant associated with the request. The method further provides identifying a namespace for the tenant, and identifying internet protocol (IP) addresses for the one or more data processing nodes. The method also includes generating namespace to IP address pairs for the one or more data processing nodes based on the namespace and the IP addresses, and configuring a domain name system (DNS) for the virtual cluster with the namespace to IP address pairs.

Management of domain name systems in a large-scale processing environment

Systems, methods, and software described herein provide for enhancements to large scale data processing architectures. In one implementation, a service architecture for large scale data processing includes a host computing system, and a virtual machine executing on the host computing system. The service architecture further includes a plurality of application containers executing on the virtual machine, wherein each of the application containers comprises a large scale processing node running one or more java virtual machines.

Employing application containers in a large scale processing environment

Growing community of inventors

Morgan Hill, CA, United States of America

Swami Viswanathan