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10-18-2023 11:08 AM - edited 10-18-2023 11:10 AM
CONTENTS | Introduction | Video |Resources | About the presenter
Video Length: 2 min 16 seconds
The root cause of a performance transaction can be complex to troubleshoot, but it does not have to be. By using AppDynamics’s built-in machine learning capabilities, we can quickly identify Health Rule violations triggered by transaction response times deviating from their baseline and then combine those with diagnostic capabilities that get us to the specific cause. We are able to drill down into the relevant snapshots to see which method and specific line of code is to blame.
In just a few moments, we demonstrate how to data mine the root cause of a performance issue by leveraging the AppDynamics AI engine to gain insights into the exact line of code causing problems.
Learn more about Anomaly Detection in the documentation.
Vivek Inbakumar joined AppDynamics as a Sales Engineer in 2021. He got into the world of IT upon graduating as a computer engineer and subsequently completed his executive MBA from the University of London. With his passion for staying close to customers combined with strong technical knowledge - sales engineering offered the best of both worlds. Based out of the Cisco Dubai office, he helps customers across the Middle East and Africa to improve their application monitoring practices.
He is also a vital member of the Cloud Native Application Observability Champions team. Here, he extends his knowledge to empower both colleagues and customers, demonstrating how AppDynamics' cutting-edge monitoring tools can revolutionize their approach to full-stack observability.
Vivek is driven by a core belief in the power of technology to transform businesses and improve lives. His commitment to understanding and meeting the unique needs of each customer sets him apart as a dedicated advocate for client success.
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