Live AI Multi-Cloud Anomalies
About
About
Live AI Multi-Cloud Anomalies Dashboard
Multi-Cloud network infrastructure has high entropy. This dashboard provides continuous real-time observability of this entropy across virtual networks in AWS, Azure and GCP and interconnect data center fabrics. Machine learning is used to dynamically learn the normal patterns of packet loss ratio and round trip delay metrics across a matrix of senders and receivers and find anomalies when a metric is abnormal.

You can use this dashboard to quickly understand if abnormal behavior in specific availability zones or regions in a provider that you rely on is the source of an application issue that you are experiencing. You can also use this dashboard to audit the performance of various providers.

This service will evolve significantly in the coming months.

  • Network Telemetry Data
  • This dashboard uses Augtera synthetic probes that are placed throughout the Multi-Cloud infrastructure. They measure the packet loss ratio and round trip delay across virtual networks in AWS, Azure and GCP and interconnect data center fabrics. This telemetry data is streamed in real-time to the Augtera Network AI platform. These probes can also be installed in your private infrastructure on request.
  • Machine Learning Based Anomaly Detection
  • Machine learning is used to dynamically learn the normal patterns of packet loss ratio and round trip delay metrics across a matrix of senders and receivers and find anomalies when a metric is abnormal. High entropy is normal in Multi-Cloud infrastructure and Augtera AI learns this normal. Anomalies indicate changes that deviate from the expected entropy.
  • Visualization
  • This dashboard visualizes:
    • Raw data heatmaps based on source / destination (Y axis / X axis) for both packet loss ratio (in blue) and round trip delay (in green)
    • ML-based anomaly heatmaps based on source / destination (Y axis / X axis) for both packet loss ratio and round trip delay ( both in red)
    • All individual end-to-end ML-based anomalies related to packet loss ratio and/or RTT with detailed information including the historical graph with anomaly zone visualization

    You can zoom into any heatmap or anomaly graph by clicking the left button of the mouse and drawing a zone selection area

Comments

We would love to hear your feedback.

Comment

Your email address will not be published. All fields are required.

This field is required.

This field is required.