VMware brings AI Capabilities to Automate Cloud Anomaly Detection

VMware brings AI Capabilities to Automate Cloud Anomaly Detection

VMware brought new forecasting capabilities based on Artificial Intelligence and Machine Learning to its Wavefront cloud monitoring and analytics platform. Easy to use UI with almost no dependency on statistical or algorithm expertise, is the key proposition of this new development.

VMware acquired Wavefront in April 2017 and added different dashboards, metrics for cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, containers services such as Kubernetes and Pivotal Container Services.

It’s easy to use Wavefront AI Genie to quickly detect true anomalies and to dramatically reduce MTTR costs.

Two broad objectives can be achieved with these new AI/ML capabilities.

  • Accelerate Troubleshooting with Automatic Anomaly Detection
  • Optimize Service Performance with AI Genie’s Automatic Forecast

It is easy to use these AI capabilities, termed as AI Genie in the Wavefront's announcement. From any Wavefront chart, you can select AI Genie with one click and choose Anomaly Detection or Forecasting. It uses anomalous() function with multiple AI/ML algorithms to monitor patterns based on a selected range of past behaviors and helps determine whether the current state can be categorized as anomalous. Once detected, Wavefront's correlation function can be used to perform root cause analysis. The detected anomaly pattern can also be saved as a new alert.

Wavefront, AI Genie Automatic Forecast Prediction
PC: Wavefront, AI Genie Automatic Forecast Prediction
AI Genie extends existing implementation of hw() function which in turn uses Holt-Winters algorithm. The user just needs to drag or move existing monitoring chart in the future weeks ahead to predict and visualize Key Performance Indicators (KPI).
Senior Product Marketing Manager for Wavefront, Gordana Neskovic, said in the announcement, "Modern cloud applications require that you extract real-time, actionable insights from thousands, if not millions of critical KPIs. The complex relationships among so many moving pieces are often overwhelming. Finding anomalies with static KPI thresholds is difficult – what’s considered an anomaly at one moment in time may be normal in another. Missed anomalies often lead to increased MTTR of critical issues. The lack of anomaly visibility and KPI forecasting makes it hard for developers and SRE teams to improve system performance and optimize customer experience."

Due to the modern nature of the new-age application, it has become not only imperative to monitor critical applications or components but their dependencies as well. Wavefront surely helps IT and Operations people to achieve this goal.

AI Genie is provided at no additional cost to the Wavefront platform.


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Mandar Pise Opinions expressed by techsutram contributors are their own. More details

Mandar is a seasoned software professional for more than a decade. He is Cloud, AI, IoT, Blockchain and Fintech enthusiast. He writes to benefit others from his experiences. His overall goal is to help people learn about the Cloud, AI, IoT, Blockchain and Fintech and the effects they will have economically and socially in the future.

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