DYNAMIC BASLINE DETERMINATION FOR DISTRIBUTED TRANSACTION

• US 20160050136A1
• Filed: 10/31/2015
• Published: 02/18/2016
• Est. Priority Date: 09/10/2009
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: AppDynamics, Inc. (Cisco Systems, Inc.)
• Inventors: Bansal, Jyoti, Sunkara, Bhaskar
• Granted Patent: US 9,893,963 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04L 43/022 by sampling
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation
• CPC Class Codes: H04L 43/045 for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/10 Active monitoring, e.g. heartbeat, ping or trace-route
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

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.

Claims

1. A method for monitoring an application, the method comprising:

monitoring an application on a machine;

determining a first baseline for handling a request by the application on the machine based on the monitoring;

continually updating the baseline based on subsequent monitoring of the application request

identifying a business transaction processed over multiple machines and including the request as an anomaly based on the updated baseline, the multiple machines including the first machine.

2. The method of claim 1, further including identifying a business transaction processed over multiple machines and including the request as an anomaly based on the first baseline and monitoring of the application prior to determining the updated baseline,

3. The method of claim 1, wherein monitoring includes determine rate of outliers

4. The method of claim 1, wherein the baseline is generated based on a number of outliers occurring during a time period.

5. The method of claim 1, wherein the anomaly is identified locally at an agent

6. The method of claim 1, wherein the anomaly is identified remotely at a server.

7. The method of claim 1, further including dynamically reporting an anomaly rate through an interface based on the identified anomalies and continually updated baseline.