LINKS
White Paper
Real-time Anomaly Detection at Scale: 19 Billion Events per day
Overview
Anomaly detection is a method used to detect unusual events in an event stream. It is widely used in a range of applications such as financial fraud detection, security, threat detection, website user analytics, sensors, IoT, system health monitoring, etc. Streaming data (events) from these applications are inspected for anomalies or irregularities and when an anomaly is detected, alerts are raised either to trigger an automated process to handle the exception or for manual intervention.
Anomaly detection applications typically compare inspected streaming data with historical event patterns, raising alerts if those patterns match previously recognized anomalies or show significant deviations from normal behavior. These detection systems utilize a stack of solutions that often include machine learning, statistical analysis, and algorithm optimization, and that leverage data-layer technologies to ingest, process, analyze, disseminate, and store streaming data.
Fill out the form on the right to download the white paper to understand how we built a streaming data pipeline application that is able to overcome the hurdles of mass-scale anomaly detection with powerful open source data-layer technologies delivered through our fully managed platform.
Featured Resources
Read All
© Instaclustr Copyright
Apache Cassandra®, Apache Kafka®, Apache Spark™, Apache Kafka®, and Apache ZooKeeper™ are trademarks of the Apache Software Foundation. Elasticsearch™ and Kibana™ are trademarks for Elasticsearch BV. Kubernetes® is a registered trademark of the Linux Foundation. OpenSearch is a registered trademark of Amazon Web Services. Postgres®, PostgreSQL® and the Slonik Logo are trademarks or registered trademarks of the PostgreSQL Community Association of Canada, and used with their permission. Redis™ is a trademark of Redis Labs Ltd. *Any rights therein are reserved to Redis Labs Ltd. Any use by Instaclustr Pty Limited is for referential purposes only and does not indicate any sponsorship, endorsement or affiliation between Redis and Instaclustr Pty Limited.
All product and service names used in this website are for identification purposes only and do not imply endorsement.