International Business Machines Corporation

Gary M Quesenberry

Christopher L Molloy

John Sebastian Warren

James C Cook

Neal A Haggard

Robert Robinson

Chris L Molloy

Robert C Robinson, Jr

Henry L Stuck

Patrick E McCamish

Robert C Robinson

A computerized method, program product, and a service that facilitates the storage of multiple rows of data in a relational database. If the data is clustered data, the method, program product and the service first obtains the clustered data from its source. An identifying primary key of the clustered data is resolved, and the clustered data is parsed, compressed and stored as a binary large object (BLOB). The BLOB may be stored within the relational database or may be stored separately. Storage and access times for large amount of data used in relational databases are optimized.

Optimal data storage and access for clustered data in a relational database

An automated method of managing computing resources having a workload of a given type comprises providing resource data collectors for collecting data regarding performance of the resources, such as a server network, in accordance with the type of workload; developing a forecast of utilization of the resources, based on historical performance data; and collecting real-time performance data regarding the resources running under the workload. The method then includes analyzing the performance data and the forecast to identify a critical resource: and automatically adjusting a capacity of the resource to provide steady-state performance of the resource under the workload. Additional hardware resources such as CPUs, computer memory and computer disk storage are initially available to, but unused by, the computing resources.

Automatic data interpretation and implementation using performance capacity management framework over many servers

A method of monitoring a computer network by collecting resource data from a plurality of network nodes, analyzing the resource data to generate historical performance data, and reporting the historical performance data to another network node. The network nodes can be servers operating on different platforms, and resource data is gathered using separate programs having different application programming interfaces for the respective platforms. The analysis can generate daily, weekly, and monthly historical performance data, based on a variety of resources including CPU utilization, memory availability, I/O usage, and permanent storage capacity. The report may be constructed using a plurality of documents related by hypertext links. The hypertext links can be color-coded in response to at least one performance parameter in the historical performance data surpassing an associated threshold. An action list can also be created in response to such an event.

Performance/capacity management framework over many servers

Growing community of inventors

Clayton, NC, United States of America

Gary M Quesenberry