Dynamic baseline determination for distributed business transaction
First Claim
1. A method for monitoring an application, the method comprising:
- monitoring, by an agent on a machine, a distributed business transaction associated with a plurality of distributed applications executing across a computer network, wherein monitoring includes collecting runtime data associated with the distributed business transaction;
based on the runtime data, determining, by the agent, a performance baseline for handling an application request associated with the distributed business transaction;
comparing, by the agent, the runtime data outliers to the performance baseline to identify an anomaly in the distributed business transaction, wherein a number of outliers occurring for a business transaction within a particular time window is compared to a baseline of outlier occurrence for the distributed business transaction, wherein a behavior of the distributed business transaction is learned based on the comparison over time;
upon identifying the anomaly, automatically triggering a diagnostic session at the machine to collect one or more diagnostic parameters about the distributed business transaction based on the learned behavior of the distributed business transaction;
continually updating the performance baseline based on subsequent monitoring of requests associated with the application; and
based on the collected diagnostic parameters, causing, by the agent, a model of a distributed business transaction flow to be generated, wherein a flow map of the one or more distributed business transactions is generated that includes a map of applications or virtual machines that make up the one or more distributed business transactions associated with the diagnostic session triggered by the anomaly.
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Accused Products
Abstract
The present technology may determine an anomaly in a portion of a distributed business application. Data can automatically be captured and analyzed for the portion of the application associated with the anomaly. By automatically capturing data for just the portion associated with the anomaly, the present technology reduces the resource and time requirements associated with other code-based solutions for monitoring transactions. A method for performing a diagnostic session for a request may begin with initiating collection of diagnostic data associated with a request. An application thread on each of two or more servers may be sampled. The application threads may be associated with the same business transaction and the business transaction may be associated with the request. The diagnostic data may be stored.
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Citations
20 Claims
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1. A method for monitoring an application, the method comprising:
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monitoring, by an agent on a machine, a distributed business transaction associated with a plurality of distributed applications executing across a computer network, wherein monitoring includes collecting runtime data associated with the distributed business transaction; based on the runtime data, determining, by the agent, a performance baseline for handling an application request associated with the distributed business transaction; comparing, by the agent, the runtime data outliers to the performance baseline to identify an anomaly in the distributed business transaction, wherein a number of outliers occurring for a business transaction within a particular time window is compared to a baseline of outlier occurrence for the distributed business transaction, wherein a behavior of the distributed business transaction is learned based on the comparison over time; upon identifying the anomaly, automatically triggering a diagnostic session at the machine to collect one or more diagnostic parameters about the distributed business transaction based on the learned behavior of the distributed business transaction; continually updating the performance baseline based on subsequent monitoring of requests associated with the application; and based on the collected diagnostic parameters, causing, by the agent, a model of a distributed business transaction flow to be generated, wherein a flow map of the one or more distributed business transactions is generated that includes a map of applications or virtual machines that make up the one or more distributed business transactions associated with the diagnostic session triggered by the anomaly. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A non-transitory computer readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for monitoring a garbage collection process, the method comprising:
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monitoring, by an agent on a machine, a distributed business transaction associated with a plurality of distributed applications executing across a computer network, wherein monitoring includes collecting runtime data associated with the distributed business transaction; based on the runtime data, determining, by the agent, a performance baseline for handling an application request associated with the distributed business transaction; comparing, by the agent, the runtime data outliers to the performance baseline to identify an anomaly in the distributed business transaction, wherein a number of outliers occurring for a business transaction within a particular time window is compared to a baseline of outlier occurrence for the distributed business transaction, wherein a behavior of the distributed business transaction is learned based on the comparison over time; upon identifying the anomaly, automatically triggering a diagnostic session at the machine to collect one or more diagnostic parameters about the distributed business transaction based on the learned behavior of the distributed business transaction; continually updating the performance baseline based on subsequent monitoring of requests associated with the application; and based on the collected diagnostic parameters, causing, by the agent, a model of the distributed business transaction flow to be generated, wherein a flow map of the one or more distributed business transactions is generated that includes a map of applications or virtual machines that make up the one or more distributed business transactions associated with the diagnostic session triggered by the anomaly. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A system for monitoring a distributed application, comprising:
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a processor configured to execute a process; and a memory configured to store program instructions which contain the process executable by the processor, the process configured to; monitor, by an agent executing on the apparatus, a distributed business transaction associated with a plurality of distributed applications executing across a computer network, wherein monitoring includes collecting runtime data associated with the distributed business transaction; based on the runtime data, determine a performance baseline for handling an application request associated with the distributed business transaction; compare the runtime data outliers to the performance baseline to identify an anomaly in the distributed business transaction, wherein a number of outliers occurring for a business transaction within a particular time window is compared to a baseline of outlier occurrence for the distributed business transaction, wherein a behavior of the distributed business transaction is learned based on the comparison over time; upon identifying the anomaly, automatically trigger a diagnostic session at the machine to collect one or more diagnostic parameters about the distributed business transaction based on the learned behavior of the distributed business transaction; continually update the performance baseline based on subsequent monitoring of requests associated with the application; and based on the collected diagnostic parameters, cause a model of the distributed business transaction flow to be generated, wherein a flow map of the one or more distributed business transactions is generated that includes a map of applications or virtual machines that make up the one or more distributed business transactions associated with the diagnostic session triggered by the anomaly. - View Dependent Claims (18, 19, 20)
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Specification