International Business Machines Corporation

Christopher J Blythe

Aaron J Quirk

Curtis E Hrischuk

Michael H Dawson

Gennaro A Cuomo

Matt Richard Hogstrom

Erik Alan Daughtrey

Real-time application metrics of an application executed by a virtual machine are dynamically monitored by a controlling agent and analyzed to determine an optimal configuration of the virtual machine for executing the application. Based on the measured metrics, tunable parameters of the virtual machine may be adjusted to achieve desired application performance.

Optimizing virtual machine synchronization for application software

Thread pools in a multithreaded server are programmatically adjusted, based on observed statistics from the server's inbound workload. In a multithreaded server environment, response time to end users is improved while increasing the efficiency of software execution and resource usage. Execution time and wait/queued time are tracked, for various types of requests being serviced by a server. Multiple logical pools of threads are used to service these requests, and inbound requests are directed to a selected one of these pools such that requests of similar execution-time requirements are serviced by the threads in that pool. The number and size of thread pools may be adjusted programmatically, and the distribution calculation (i.e., determining which inbound requests should be assigned to which pools) is a programmatic determination. In preferred embodiments, only one of these variables is adjusted at a time, and the results are monitored to determine whether the effect was positive or negative. The disclosed techniques also apply to tracking and classifying requests by method name (and, optionally, parameters).

Dynamic thread pool tuning techniques

Workload is programmatically distributed across a set of execution resources. In a multithreaded server environment, response time to end users is improved while increasing the efficiency of software execution and resource usage. Execution time and wait/queued time are tracked, for various types of requests being serviced by a server. Multiple logical pools of threads are used to service these requests, and inbound requests are directed to a selected one of these pools such that requests of similar execution-time requirements are serviced by the threads in that pool. The number and size of thread pools may be adjusted programmatically, and the distribution calculation (i.e., determining which inbound requests should be assigned to which pools) is a programmatic determination. In preferred embodiments, only one of these variables is adjusted at a time, and the results are monitored to determine whether the effect was positive or negative. The disclosed techniques also apply to tracking and classifying requests by method name (and, optionally, parameters).

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Austin, TX, United States of America

Christopher J Blythe