AIOps Essentials: Issue Detection using Anomaly Detection on top of APM | AIOps Use Cases (3/5)

AIOps Essentials: Issue Detection using Anomaly Detection on top of APM | AIOps Use Cases (3/5)

Jan 12, 2023

Artificial intelligence for IT operations (AIOps) is a way to automate tasks that are typically carried out by site reliability engineers (SREs). It aims to make the lives of SREs easier by helping them reduce the amount of noise coming from systems, surface issues more easily, and perform root cause analysis by correlating data from different systems

In this video, we explore using machine learning on top of data that we've already collected. Specifically, we focus on issue detection using unsupervised machine learning. We demonstrate how Elastic can both reduce noise and focus on important data, as well as detect normal or abnormal system behavior without prior knowledge of what "normal" or "good" state is. We also show how to create machine learning jobs and use anomaly detection in the APM to analyze data from microservices, system calls, and Kubernetes.


00:00 - Issue Detection introduction

03:00 - Anomaly Detection for APM

08:20 - Anomaly Detection for Hosts (Kubernetes)

12:54 - Anomaly Explorer

18:42 - Creating business metrics from logs

29:00 - Anomaly Detection on Business Metrics

31:46 - Issue detection on processed payments

34:00 - Forecast

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About Elastic
Elastic is the leading platform for search-powered solutions, and we help everyone — organizations, their employees, and their customers — find what they need faster, while keeping applications running smoothly, and protecting against cyber threats. When you tap into the power of Elastic Enterprise Search, Observability, and Security solutions, you’re in good company with brands like Netflix, Uber, Slack, Microsoft, and thousands of others who rely on us to accelerate results that matter.

#AIOps #Observability #DevOps #ElasticObservability #MachineLearning #DataAnalysis #IssueDetection #UnsupervisedLearning #APM #Microservices #Kubernetes #AnomalyDetection