International Business Machines Corporation

Globalfoundries Inc.

Upendra Sharma

Aaron J Quirk

Rahul Ghosh

Giribabu V Paramkusham

Isabelle Marie Rouvellou

Han Chen

Ignacio Silva-Lepe

Thomas Arthur Mikalsen

Revathi Subramanian

Paula K Austel

Sambit Sahu

Ajay Mohindra

Akshat Verma

Rohit Jain

Manoj N Kumar

Ramani Ranjan Routray

Mukesh Kumar Mohania

Murthy V Devarakonda

Sandeep Madhav Uttamchandani

Divyesh Jadav

Inderpal Singh Narang

Vijay Krishnarao Naik

Marc Adam Kaplan

Pradeep Varma

Prashant Pandey

Vishal Singh Batra

Tapan Kumar Nayak

James Rubas

Vitthal Mahadeo Gogate

Nagraj Alur

Mandis Sadr Mohammad Beigi

A method, system and computer program product for selecting virtual machines to be migrated to a public cloud. The current resource usage for virtual machine instances running in the private cloud is determined. Furthermore, any scaling policies attached to the virtual machine instances running in the private cloud are obtained. Additional resource usages for any of the virtual machine instances with a scaling policy are computed for when these virtual machine instances are scaled out. A cost of running a virtual machine instance in the public cloud is then determined using its current resource usage as well as any additional resource usage if a scaling policy is attached to the virtual machine instance based on the cost for running virtual machine instances in a public cloud. If the cost is less than a threshold cost, then the virtual machine instance is selected to be migrated to the public cloud.

Selecting virtual machines to be migrated to public cloud during cloud bursting based on resource usage and scaling policies

A method, system and computer program product for optimizing runtime performance of an application workload. Network input/output (I/O) operations between virtual machines of a pattern of virtual machines servicing the application workload in a private cloud are measured over a period of time and depicted in a histogram. A score is generated for each virtual machine or group of virtual machines in the pattern of virtual machines based on which range in the ranges of I/O operations per seconds (IOPS) depicted in the histogram has the largest sample size and the number of virtual machines in the same pattern that are allowed to be in the public cloud. In this manner, the runtime performance of the application workload is improved by minimizing the network input/output communications between the two cloud environments by migrating those virtual machine(s) or group(s) of virtual machines with a score that exceeds a threshold value.

Optimizing runtime performance of an application workload by minimizing network input/output communications between virtual machines on different clouds in a hybrid cloud topology during cloud bursting

A solution descriptor comprises a set of component workload units, a workload unit describing a deployable application component with application binary, configuration parameters and dependency declarations. An environment descriptor specifies a set of target platforms and plugins in an execution environment. A deployer interprets the solution descriptor and the environment descriptor, and generates a list of tuples comprising compatible workload-plugin-platform combinations. The deployer determines an execution order for the list of tuples, and invokes the plugins in the list of tuples in the execution order, wherein each of the plugins executes a corresponding compatible workload on a corresponding compatible target platform specified in the list of tuples.

Release and management of composite applications on PaaS

Release and management of composite applications on PAAS

Enabling remote debugging of virtual machines, in one aspect, may comprise attaching a debug virtual machine to a target virtual machine deployed in a virtualized environment. Interactions and/or access to the target virtual machine may be performed via the attached debug virtual machine. The debug virtual machine may be created and attached to the target virtual machine in response to receiving a request to debug the target machine, for example, from a remote user of the target virtual machine.

Enabling remote debugging of virtual machines running in a cloud environment

An automated disaster recovery (DR) planning system for a computing environment is provided. A discovery module discovers servers, networks, and storage devices in a computing environment. An expert knowledge base module captures best practices in planning, and capabilities, interoperability, limitation and boundary values for different DR technologies. A match-making module determines multiple DR plans as combinations of one or more replication technologies that can be used to satisfy DR requirements. And, an optimizer configured for assessing a feasible DR plan from said multiple DR plans, to deploy for DR planning of a primary computing environment.

Method and system for automated integrated server-network-storage disaster recovery planning

Growing community of inventors

Elmsford, NY, United States of America

Upendra Sharma