International Business Machines Corporation

Mark N Weatherill

Scot W Dixon

Benjamin Hartnett

Ian L Gregor

Randy George

Steven Larcombe

Richard A Burford

Christopher R Walker

Andrew J Bailey

A computer-implemented method includes identifying one or more client-based data artefacts associated with a client device, identifying one or more backend configuration data artefacts associated with a backend device, and identifying one or more backend configuration correlation guidelines. The computer-implemented method further includes determining one or more configuration correlation conclusions based on the one or more client-based data artefacts, the one or more backend configuration data artefacts, and the one or more backend configuration correlation guidelines. A corresponding computer program product and computer system are also disclosed.

Measuring the performance of computing resources

A method of filtering authenticated synthetic transactions comprises receiving over a network, at a server providing a first networked application, a plurality of requests for the first networked application, wherein the plurality of requests includes a first synthetic transaction. The method further comprises analyzing a respective header of each of the plurality of requests; identifying a synthetic token in the respective header of the first synthetic transaction in response to analyzing the respective header of each of the plurality of requests; determining that the identified synthetic token corresponds to the first networked application; and bypassing usage monitoring for the first synthetic transaction in response to determining that the identified synthetic token corresponds to the first networked application.

Filtering of authenticated synthetic transactions

A method, program product, and system for a transaction parallelization improvement metric calculation includes receiving tracking data. The tracking data includes information about inbound and outbound subtransactions between domains over a time frame. Each domain includes at least one computer. Using the tracking data received, a number of interactions are determined based on a number of the inbound and outbound subtransactions. A total number of domains is determined using received tracking data. A transaction parallelization metric is calculated using the tracking data and a transaction parallelization improvement metric is calculated based on the number of interactions, the number domains, and the transaction parallelization metric.

Determining a transaction parallelization improvement metric

A method for processing data includes performing an extract-transform-load operation on a set of application activity data to provide a topology index comprising a plurality of unique entries, extracting node information and connection information for an application data structure and building a data structure corresponding to the application therefrom, and providing information from the application topology data structure to a user. A computer program product corresponding to the method is also disclosed herein. Also disclosed is an apparatus for processing data comprising a processing module configured to perform an extract-transform-load operation on application activity data, an extraction module configured to extract node and connection information for the application, and a topology calculator configured to build a topology data structure corresponding to the application. The apparatus may additionally include a persistent data store configured to store the topology index.

High performance topology resolution for non-instrumented nodes

Embodiments of the present invention disclose a method, computer program product, and system for calculating an average parallelization metric. A tracking application receives tracking data that tracks how at least one server processes a plurality of transactions. Each of the plurality of transactions is comprised of a plurality of subtransactions. A parallelization metric is calculated for each of the plurality of transactions and an average parallelization metric is calculated from the calculated parallelization metrics. The parallelization metric for each transactions calculating using the calculated sum of the response times for all of the subtransactions for one transaction, the longest response time for one subtransaction out of response times for all of plurality of subtransaction that comprise the one transaction, and the calculated actual execution time for the transaction based on the time when the transaction starts to when the transaction has been completed.

Method and apparatus for determining a transaction parallelization metric

Methods and apparatuses for generating an application topology are provided. A processor determines a first application profile based, at least in part, on a first network packet. A processor determines a second application profile based, at least in part, on a second network packet. A processor determines a link between a first application and a second application based, at least in part, on address information of the first network packet. A processor generates a topology comprising the first and second application profiles based, at least in part, on the link, the first application profile and the second application profile. A processor updates the first and second application profiles based, at least in part, on matching the first application profile and second application profile with an application deployment template.

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Victoria Park, Australia

Mark N Weatherill