Abstract: A system and method are presented for detecting messages relevant to users in a collaborative environment. In a unified collaboration system, large volumes of messages between a plurality of users in a group may be monitored for relevance to a particular user. Analytics may be applied to the content of the messages to determine which of the plurality of users are relevant and should be alerted. Alerts may notify relevant users that there are messages which may require attention. Non-relevant information in messages may also be hidden or filtered for a user. In an embodiment, users and subject matters may be linked together. For example, words in a message may be related to specific sub-topics of a group and may be associated with a user over time based on when the word is used and which users respond.

Abstract: A system and method are presented for detecting messages relevant to users in a collaborative environment. In a unified collaboration system, large volumes of messages between a plurality of users in a group may be monitored for relevance to a particular user. Analytics may be applied to the content of the messages to determine which of the plurality of users are relevant and should be alerted. Alerts may notify relevant users that there are messages which may require attention. Non-relevant information in messages may also be hidden or filtered for a user. In an embodiment, users and subject matters may be linked together. For example, words in a message may be related to specific sub-topics of a group and may be associated with a user over time based on when the word is used and which users respond.

Abstract: The service assignment tool analyzes a service to determine whether the service can execute on a cluster. If the service cannot execute on a cluster, the service is assigned to a single virtual machine. The service assignment tool identifies non-cluster friendly services by performing a static analysis on the bytecode of the service. The bytecode of the service is analyzed by comparing each segment of bytecode to a list of known good and bad coding conventions. If each segment of bytecode in a service meets the good coding convention criteria, then the service is cluster friendly. If one segment of bytecode does not meet the good coding convention criteria, then the entire service is considered to be not cluster friendly.

Abstract: The service assignment tool analyzes a service to determine whether the service can execute on a cluster. If the service cannot execute on a cluster, the service is assigned to a single virtual machine. The service assignment tool identifies non-cluster friendly services by performing a static analysis on the bytecode of the service. The bytecode of the service is analyzed by comparing each segment of bytecode to a list of known good and bad coding conventions. If each segment of bytecode in a service meets the good coding convention criteria, then the service is cluster friendly. If one segment of bytecode does not meet the good coding convention criteria, then the entire service is considered to be not cluster friendly.