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Implementation of AI in the business transaction of software monitoring

1.  Drivers

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2.  Study details (One paragraph of each)

  a.  Provide a breakdown of the 5 W’s (Who, What, When, Where and Why)

3.  Recommendations & results

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Overview of the Use-Case:

In recent years, software applications have evolved to be more complex, dynamic, and distributed in nature. Our company houses a large number complex applications distributed across its ecosystem. Therefore, monitoring these applications have become a tedious, complex and costly task. Having a real time end-to-end business transaction monitoring solutions is very important, as this will help proactively identify any issues related to its services and expedite its resolution. 

Gartner defines Application Performance Monitoring (APM) as “a suite of monitoring software comprising digital experience monitoring (DEM), application discovery, tracing and diagnostics, and purpose-built artificial intelligence for IT operations”. APM is the practice of proactively monitoring the many aspects of an application environment in order to identify and mitigate issues before they become major problems.

Our goal in this use-case is to study how the company can leverage Artificial Intelligence (AI) in APM to detect abnormalities or future issues in business transaction and proactivity resolve them.

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