Abstract: A method, system and computer program product for selecting an appropriate platform to run an application deployed in a cloud computing environment. The appropriate platform is selected by employing a two phase process, where the first phase occurs prior to the deployment of the application and the second phase occurs after the application has been deployed. In the first phase, the cloud computing node selects a platform using various factors, such as application binaries, application metadata and artifacts, and qualities of service and application requirements. In the second phase, the cloud computing node determines whether an alternative platform needs to be implemented for subsequent deployments of the application using various factors, such as application runtime metrics and garbage collection metrics. In this manner, an appropriate platform is automatically selected thereby removing the requirement for the user to indicate the type of platform for the target environment.

Abstract: A method, system and computer program product for selecting an appropriate platform to run an application deployed in a cloud computing environment. The appropriate platform is selected by employing a two phase process, where the first phase occurs prior to the deployment of the application and the second phase occurs after the application has been deployed. In the first phase, the cloud computing node selects a platform using various factors, such as application binaries, application metadata and artifacts, and qualities of service and application requirements. In the second phase, the cloud computing node determines whether an alternative platform needs to be implemented for subsequent deployments of the application using various factors, such as application runtime metrics and garbage collection metrics. In this manner, an appropriate platform is automatically selected thereby removing the requirement for the user to indicate the type of platform for the target environment.

Abstract: A method, system and computer program product for selecting an optimal transport protocol in a cloud computing environment. An application creates a socket to communicate with a destination Virtual Machine (VM). The application requests a daemon agent to query a virtual machine manager to determine if the destination VM is on the same hypervisor as the application. The daemon agent receives a VMCI address (“context ID”) and an indication of the hypervisor associated with the destination VM from the virtual machine manager. The daemon agent enables the transport layer to route traffic over the VMCI protocol to the destination VM using its context ID in response to the destination VM being on the same hypervisor as the application. In this manner, the application is able to route traffic using an optimal transport protocol, including VMCI, depending on peer hypervisor association without requiring any code modifications to the application.

Abstract: A method, system and computer program product for selecting an optimal transport protocol in a cloud computing environment. An application creates a socket to communicate with a destination Virtual Machine (VM). The application requests a daemon agent to query a virtual machine manager to determine if the destination VM is on the same hypervisor as the application. The daemon agent receives a VMCI address (“context ID”) and an indication of the hypervisor associated with the destination VM from the virtual machine manager. The daemon agent enables the transport layer to route traffic over the VMCI protocol to the destination VM using its context ID in response to the destination VM being on the same hypervisor as the application. In this manner, the application is able to route traffic using an optimal transport protocol, including VMCI, depending on peer hypervisor association without requiring any code modifications to the application.

Abstract: Provided are techniques for text prediction using environment hints. A list of words is received, wherein each word in the list of words has an associated weight. For at least one word in the list of words, an environment weight is obtained from an environment dictionary. The associated weight of the at least one word is updated using the obtained environment weight. The words in the list of words are ordered based on the updated, associated weight of each of the words.

Abstract: Provided are techniques for text prediction using environment hints. A list of words is received, wherein each word in the list of words has an associated weight. For at least one word in the list of words, an environment weight is obtained from an environment dictionary. The associated weight of the at least one word is updated using the obtained environment weight. The words in the list of words are ordered based on the updated, associated weight of each of the words.

Abstract: A method, system and computer program product for managing resource utilization of virtual machines in a cloud computing environment. A cloud controller computes an index of the utilization of a resource by a virtual machine to determine its adverse impact on its neighboring virtual machine(s) that share the same resource. If the interference index is greater than a threshold, then the utilization of the resource by that virtual machine will be throttled or reduced provided that the servicing of its workload is not weighted at too high of a priority and that one or more of its neighboring virtual machines are not able to meet their service-level agreement requirements. In this manner, the adversely affected neighboring virtual machines may have its performance restored in meeting their service-level agreement requirements without having to add additional resources and/or be migrated to other areas of the cloud computing environment.

Abstract: Provided are techniques for text prediction using environment hints. A list of words is received, wherein each word in the list of words has an associated weight. For at least one word in the list of words, an environment weight is obtained from an environment dictionary. The associated weight of the at least one word is updated using the obtained environment weight. The words in the list of words are ordered based on the updated, associated weight of each of the words.

Abstract: Provided are techniques for text prediction using environment hints. A list of words is received, wherein each word in the list of words has an associated weight. For at least one word in the list of words, an environment weight is obtained from an environment dictionary. The associated weight of the at least one word is updated using the obtained environment weight. The words in the list of words are ordered based on the updated, associated weight of each of the words.

Abstract: A method, system and computer program product for managing resource utilization of virtual machines in a cloud computing environment. A cloud controller computes an index of the utilization of a resource by a virtual machine to determine its adverse impact on its neighboring virtual machine(s) that share the same resource. If the interference index is greater than a threshold, then the utilization of the resource by that virtual machine will be throttled or reduced provided that the servicing of its workload is not weighted at too high of a priority and that one or more of its neighboring virtual machines are not able to meet their service-level agreement requirements. In this manner, the adversely affected neighboring virtual machines may have its performance restored in meeting their service-level agreement requirements without having to add additional resources and/or be migrated to other areas of the cloud computing environment.

Abstract: A method, system and computer program product for selecting an optimal transport protocol in a cloud computing environment. An application creates a socket to communicate with a destination Virtual Machine (VM). The application requests a daemon agent to query a virtual machine manager to determine if the destination VM is on the same hypervisor as the application. The daemon agent receives a VMCI address (“context ID”) and an indication of the hypervisor associated with the destination VM from the virtual machine manager. The daemon agent enables the transport layer to route traffic over the VMCI protocol to the destination VM using its context ID in response to the destination VM being on the same hypervisor as the application. In this manner, the application is able to route traffic using an optimal transport protocol, including VMCI, depending on peer hypervisor association without requiring any code modifications to the application.

Abstract: A method, system and computer program product for selecting an optimal transport protocol in a cloud computing environment. An application creates a socket to communicate with a destination Virtual Machine (VM). The application requests a daemon agent to query a virtual machine manager to determine if the destination VM is on the same hypervisor as the application. The daemon agent receives a VMCI address (“context ID”) and an indication of the hypervisor associated with the destination VM from the virtual machine manager. The daemon agent enables the transport layer to route traffic over the VMCI protocol to the destination VM using its context ID in response to the destination VM being on the same hypervisor as the application. In this manner, the application is able to route traffic using an optimal transport protocol, including VMCI, depending on peer hypervisor association without requiring any code modifications to the application.

Abstract: A method, system and computer program product for selecting an appropriate platform to run an application deployed in a cloud computing environment. The appropriate platform is selected by employing a two phase process, where the first phase occurs prior to the deployment of the application and the second phase occurs after the application has been deployed. In the first phase, the cloud computing node selects a platform using various factors, such as application binaries, application metadata and artifacts, and qualities of service and application requirements. In the second phase, the cloud computing node determines whether an alternative platform needs to be implemented for subsequent deployments of the application using various factors, such as application runtime metrics and garbage collection metrics. In this manner, an appropriate platform is automatically selected thereby removing the requirement for the user to indicate the type of platform for the target environment.