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Anomaly Detection

AppDynamics Cloud enhancements for hybrid cloud, anomaly detection and usability

Introducing new capabilities expanding hybrid cloud support for VMs, Kubernetes and Linux apps running in public or private clouds, enhancements in application to infrastructure correlation using AI/ML-powered anomaly detection and more.

Using Elastic Anomaly detection and log categorization for root cause analysis

Elastic's machine learning helps support several easy-to-use features to help determine root cause analysis for logs. This includes anomaly detection and log categorization, which are easy-to-use features aiding in analysis without the need to understand or know about machine learning.

Anomaly Detection Using OSquery and Grafana

Detecting unauthorized usage and malicious applications in an instance involves analyzing OS and application logs. Doing this manually is a herculean effort because of the number of logs and the patterns one has to look for. Having a tool that can provide an aggregated view of your instance and the ability to analyze them easily can greatly reduce manual effort.

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Machine-Learning Automation: Processing, Storing, & Analyzing Data in the Digital Age

The world of software is growing more complex, and simultaneously changing faster than ever before. The simple monolithic applications of recent memory are being replaced by horizontal cloud-native applications. It is no surprise that such applications are more complex and can break into infinitely more ways (and ever new ways). They also generate a lot more data to keep track of. The pressure to move fast means software release cycles have shrunk drastically from months to hours, with constant change being the new normal.

Anomaly detection on Prometheus metrics

We have recently extended the native machine learning (ML) based anomaly detection capabilities of Netdata to support all metrics, regardless on their collection frequency (update every). Previously only metrics collected every second were supported, but now Netdata can run anomaly detection out of the box with zero config on metrics with any collection frequency.