Ca, Inc.

Computer Associates Think, Inc.

Other

Brian Zuzga

Ling Thio

Mark Jacob Addleman

John Branson Bley

Ramesh Mani

Daniel L Keller

Jon Ruiz

Ryan Oblak

Krates Ng

Virginia Chiu

Alec Embke

Jeffrey Robert Cobb

Hu Zhou

Ka Wing Kevin Arion Loo

A system prioritizes workflows based on priority levels and calculates an amount of resource consumption associated with the workflows. Each client starts a predefined time period with a certain amount of credits that indicate a degree of resource consumption. Workflows may be run with high priorities using credits. Workflows that are run with higher priorities are scheduled to run before workflows with lower priorities. A degree of resource consumption for running a workflow may be calculated based on resources consumed by the system, such as central processing unit (CPU), memory storage, network usage and elapsed time. The degree of resource consumption for running a workflow may be calculated and converted to an amount of credits and the respective amount of credits may be deducted from a credit balance associated with the client's account. The degree of resource consumption associated with a workflow may be estimated before the workflow starts running.

Server-based workflow management using priorities

Authorizing access to a web domain involves a server device receiving, from a browser of a computing device, a request to access a web domain. The server device sends a web page to the browser of the computing device. The web page includes a redirect script that redirects the browser to a particular companion domain of the web domain, wherein the particular companion domain comprises a domain name system (DNS) zone file comprising an ALIAS record for the particular companion domain. The server device sends to the browser an authentication challenge for access to the web domain. The server device receives a Kerberos service ticket from the browser of the computing device. The server device provides the browser with access to the web page.

Dual domain cloud Kerberos authentication

A benchmark response time is determined for a browser application request sent to a network server over a network. The response time is determined by performance monitoring code that is loaded into and monitors the browser application from the client. The performance monitoring code automatically sends a request to a network server; the request is not sent in response to user input. The network server receives the request, generates a response and provides the response to the browser application. The response includes a fixed amount of randomly generated data. The browser application receives and processes the response, but does not display the bytes or change the content displayed in the browser application as a result of the response. The browser application sends the times at which the browser application sends the request and the browser application completes processing the response data to the network server for further processing.

Response time benchmarking

Multiple transaction components that comprise a transaction are correlated using a GUID generated at a browser application. The transaction components may occur asynchronously or synchronously between a network browser and one or more applications. An identifier is generated for a set of network browser requests corresponding to a single user input or some other event and the identifier is included in each request. Server traffic and the servers processing the request are monitored and data which includes the identifier is generated. Data for the transaction with multiple transaction components is reported using the GUID associated with the transaction.

Monitoring related content requests

Synthetic transactions for a network system are generated based on monitoring of the network system to determine whether the network system may be blind to traffic. A process determines whether an application within an application server in a network system is processing traffic received by the application server, and whether a web server within the network system and in communication with the application server is receiving traffic that requires processing by the application. The process determines that the network system may be blind to the traffic, and, in response, generates a synthetic transaction instruction and a corresponding synthetic transaction to test whether the network system is blind to the traffic. Based on a response of the network system to the synthetic transaction, the process determines whether there is a malfunction of the application server or a period of low traffic activity of the application server.

Synthetic transactions to test blindness in a network system

Data collected during runtime and associated with a service level agreement and operating level agreement for a network service are automatically correlated together. A network monitoring system monitors the network service during runtime to determine SLA and OLA violations. An SLA is tested against traffic monitoring data derived from monitoring traffic between a network service system and one or more users of the system. An OLA is tested against application runtime data generated from monitoring a transaction occurring between an application server and a backend or other internal entity of the network service system. The data collected during runtime can be correlated using a hierarchy based on business transactions or in some other manner. Because the traffic monitoring data and application runtime data are organized using a similar data hierarchy, the traffic monitoring data corresponding to an SLA may be correlated to the application runtime data corresponding to the same business transaction and one or more OLAs.

Automatic correlation of service level agreement and operating level agreement

Network performance is monitored using timing information retrieved from a client device, server in communication with the client, or both. Client side timing information is retrieved using performance monitoring code provided by the server. The code may be provided to the client as part of a content response. Once content in the provided content response is loaded, the code sends the timing information to the server. The server may then process the timing information to calculate response time and other time information metrics.

Performance monitoring of network applications

Synthetic transactions for a network system are generated based on monitoring of the network system. One or more network system monitoring systems receive network system traffic, traffic monitoring data and/or application runtime data during a monitoring process. The traffic monitoring data may be derived from network system traffic and the application runtime data may be data associated with application transactions. The traffic, traffic monitoring data and application runtime data may contain information regarding the scope and frequency of the functionality tested by the actual traffic received by the network system. Synthetic transactions may be generated and transmitted to test the network system based on the scope and frequency of the functionality tested by actual traffic.

Synthetic transactions based on system history and load

Resource pool depletion information, including the estimated time until the resource pool is depleted, is derived from resource pool data. Data regarding the size of a resource pool is collected over a period of time. The data may include the resource pool size and other information. One or more functions are then generated to fit one or more sets of data within the collected resource pool data. The best fitting function is selected from the generated functions and used to determine the time at which the particular resource pool will become depleted. Values for the selected function can be generated at future points in time to determine the depletion point of the resource pool. The time information as well as depletion confidence values are provided to a user or otherwise processed.

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San Francisco, CA, United States of America

Brian Zuzga