Proactively identify operational issues and avoid costly incidents by detecting anomalies in both log and metric data
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.
Improves detection accuracy by building comprehensive models of regular operations across multiple subsystems, allowing for precise identification of deviations from the norm.
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.
The system helps ensure timely, informed decisions based on the most current and actionable insights.
Features
The solution continuously monitors real-time metric and log data, detecting deviations in frequency, occurrence or sequence patterns to provide immediate insights into emerging anomalies.
The platform continuously monitors real-time operational data and log messages, detecting deviations in frequency, occurrence or sequence patterns to provide immediate insights into emerging anomalies.
IBM Z Anomaly Analytics correlates and prioritizes anomalous event groups, helping ensure that IT teams are alerted only to high-confidence issues, which streamlines the response process and reduces false positives.
Correlate and analyze anomalous event groups to help IT operators and system programmers prioritize which operational issues to address. This helps ensure that your team is only alerted to high-confidence event groups, reducing false positives.
The solution continuously monitors real-time metric and log data, detecting deviations in frequency, occurrence or sequence patterns to provide immediate insights into emerging anomalies.
The platform continuously monitors real-time operational data and log messages, detecting deviations in frequency, occurrence or sequence patterns to provide immediate insights into emerging anomalies.
IBM Z Anomaly Analytics correlates and prioritizes anomalous event groups, helping ensure that IT teams are alerted only to high-confidence issues, which streamlines the response process and reduces false positives.
Correlate and analyze anomalous event groups to help IT operators and system programmers prioritize which operational issues to address. This helps ensure that your team is only alerted to high-confidence event groups, reducing false positives.
Technical details
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.
Key components
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.