IBM Z® Anomaly Analytics is software that provides intelligent anomaly detection and grouping to proactively identify operational issues in your enterprise environment.
IBM Z Anomaly Analytics uses historical IBM Z log and metric data to build a model of normal operational behavior. Real-time data is then scored against the model to detect anomalous behavior. A correlation algorithm then groups and analyzes anomalous events to proactively alert operation teams of emerging problems.
Your essential services and applications must always be available in today's digital environment. For enterprises with hybrid applications, including IBM Z, detecting and determining the root cause of hybrid application issues has become more complex with rising costs, skill shortage and changing user patterns.
Enhances operational efficiency by providing real-time notifications of correlated and grouped anomalous behavior, enabling IT teams to respond swiftly and proactively. By assessing the impact of these anomalies, the system prioritizes responses, helping ensure that resources are efficiently allocated to address critical issues and minimize disruptions.
Improves detection accuracy by building comprehensive models of regular operations across multiple subsystems, allowing for precise identification of deviations from the norm. By correlating and grouping metric and log anomaly events, the system further reduces false positives, helping ensure that true anomalies are accurately detected.
Empowers data-driven decision-making by providing detailed visualizations of anomalous activity within a topological context, making it easier to interpret complex data and diagnose issues. Coupled with real-time data analysis against established operational models, the system helps ensure timely, informed decisions based on the most current and actionable insights.
Explore the data flow among the components of IBM Z Anomaly Analytics.
Provides the infrastructure for accessing IT operational data from z/OS® systems.
Detects anomalies in z/OS systems log data.
Detects anomalies in the metric data from record types.
Correlates anomalies and scores event groups to alert teams of operational issues with high confidence.
Help ensure that your environment meets the system requirements for deploying the software containers of IBM Z Anomaly Analytics on Linux® and IBM Z Common Data Provider on z/OS system.