Emc Corporation

Open Text Corporation

Dmitry Limonov

Boris Shpilyuck

Dmitry Volchegursky

Alex Rankov

Shu-Shang Sam Wei

Dmitry Yuryevich Korshunov

Linda J Wong

Pavel Balan

Optimizing synchronization of enterprise content management systems is described. A system identifies multiple synchronization intervals corresponding to multiple synchronization tasks. The system estimates multiple execution times corresponding to the multiple synchronization tasks. The system calculates multiple remaining times corresponding to the multiple synchronization tasks, wherein the multiple remaining times are based on the multiple synchronization intervals corresponding to the multiple synchronization tasks minus the multiple execution times corresponding to the multiple synchronization tasks. The system orders the multiple synchronization tasks for execution based on corresponding multiple remaining times, from a lowest remaining time to a highest remaining time. The system executes a set of the multiple synchronization tasks based on a corresponding set of the multiple remaining times, wherein at least one of the corresponding set of the multiple remaining times equals the lowest remaining time.

Optimizing synchronization of enterprise content management systems

Projecting resource allocations to achieve specified application operation times in a virtually provisioned environment is described. A system identifies a time period associated with an average of application operation times. The system calculates a resource ratio based on a resource allocated to a number of application operations associated with the time period divided by the number of application operations associated with the time period. The system calculates a projected resource allocation based on a projected number of application operations multiplied by the resource ratio. The system outputs the projected resource allocation to assist in resource management.

Projecting resource allocation to achieve specific application operation times in a virtually provisioned environment

Tracking changes to application model definitions for application model migration is described. A combined history file is created based on changes associated with application model definition files. A first property for a first model definition file of the application model definition files is identified that depends on a second property for a second model definition file of the application model definition files. A change for the second property is identified based on the combined history file. A transformation file is constructed that includes a change for the first property based on the change for the second property.

Method and system for tracking changes to application model definitions for application model migration

Adjustments for application underachievement in a virtually provisioned environment are described. If an average of application operation times exceeds a first time constraint, a utilization measurement is recorded for each resource for each server in a virtually provisioned environment associated with an application operation when an application operation time exceeds a second time constraint. The resources include a central processing unit resource, a memory resource, a network resource, and/or an input-output resource. Each utilization measurement is converted to a corresponding utilization range of multiple utilization ranges. After the application operation time exceeds the time constraint on a specified number of occasions, an additional resource is provisioned to adjust the specific resource for the specific server based on an enhancement factor applied to the specific resource if the utilization record includes a specific range for the specific resource for the specific server more than a specified frequency.

Method and system for adjustments for application underachievement in a virtually provisioned environment

A method for automatically provisioning a virtual computing environment comprising a plurality of virtual computing nodes includes provisioning a virtual base node using base configuration information that includes a base endpoint that identifies interconnectivity parameters required to communicate with the virtual base node, and storing the base endpoint in an endpoint registry. The method further includes determining that a virtual first node depends on the virtual base node, and receiving the base endpoint from the endpoint registry. Thereafter, the virtual first node is provisioned using the received base endpoint and first configuration information for the virtual first node.

Provision a virtual environment based on topology of virtual nodes, node dependencies and base node configuration information

Calculating costs of application operations in a virtually provisioned environment is described. Servers are identified that support application operations associated with executing an application, based on a configuration file. A count of each type of application operation currently executing and a resource utilization associated with each of the servers are recorded. A set of linear equations is created if the resource utilization is recorded on the number of occasions that equals the number of application operation types. Each linear equation equates a sum of a count of each type of application operation recorded as executing during an occasion with the resource utilization recorded on the occasion. The set of linear equations is solved to estimate and output resource costs of each individual type of application operation to assist in resource management.

Method and system for calculating costs of application operations in a virtually provisioned environment

Identifying root causes of application underachievement in a virtually provisioned environment is described. A utilization measurement is recorded for each resource for each server in a virtually provisioned environment associated with an application operation if an application operation time exceeds a time constraint. The resources include a central processing unit resource, a memory resource, a network resource, and/or an input-output resource. Each utilization measurement is converted to a corresponding utilization range of multiple utilization ranges. After the application operation time exceeds the time constraint on a specified number of occasions, an identification of a specific resource for a specific server as a root cause of the application operation time exceeding the time constraint is output if the utilization record includes a specific range for the specific resource for the specific server more than a specified frequency.

Method and system for identifying root causes of application underachievement in a virtually provisioned environment

Estimating required resources to support a specific number of users in a virtually provisioned environment is described. Servers are identified that support application operations associated with executing an application, based on a configuration file. A count of each type of application operation currently executing and a resource utilization associated with each of the servers are recorded. A set of linear equations is created and solved to estimate resource costs of each individual type of application operation and ultimately to calculate required resource costs to support the projected number of concurrent users.

Method and system for estimating required resources to support a specific number of users in a virtually provisioned environment

A method for load balancing resource requests among a plurality of servers is disclosed and includes providing an enterprise content management (ECM) system coupled to processing servers for managing a plurality of resources, where each resource is identified by a resource identifier. The ECM system includes a load manager that receives a first plurality of requests. Each request includes a resource identifier and an action, and is assigned to a processing server for processing. The method includes recording performance statistics for each request when each request is processed. Request types based on the resource identifier and the action of each request are also identified. For each request type, a weighting factor is generated based on the performance statistics for each request of the request type. Thereafter, a new request is assigned to a processing server based on the weighting factor for request type of the new request.

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Dublin, CA, United States of America

Dmitry Limonov