Batch and online anomaly detection for scientific applications in a Kubernetes environment

Keyphrases

• Anomaly Detection 100%
• Scientific Applications 100%
• Online Anomaly Detection 100%
• Kubernetes 100%
• User Interface 50%
• Ancillary 50%
• Graphical User Interface 50%
• Resilient 50%
• Streaming Data 50%
• Scalable Services 50%
• Desirable Output 50%
• Detecting Anomalies 50%
• Cloud-based 50%
• Subscribe 50%
• Technical Knowledge 50%
• Service Framework 50%
• Anomalous Objects 50%
• Data Anomalies 50%
• Containerized 50%
• Astronomical Surveys 50%
• Kubernetes Cluster 50%
• Isolation Forest 50%
• Batch Data 50%
• Streaming Mode 50%
• Spark Cluster 50%
• Extended Isolation Forest 50%

Computer Science

• Scientific Application 100%
• Anomaly Detection 100%
• Kubernetes 100%
• Scientific Data 33%
• Graphical User Interface 33%
• Data Streaming 33%
• Detect Anomaly 33%
• Anomaly-Based Detection 33%
• Technical Knowledge 33%
• User Interface 33%

Physics

• Astronomical Survey 100%
• Graphical User Interface 100%