Step into the Future of Operational Excellence with IBM Z Anomaly Analytics
Proactively detect anomalies and avert costly operational disruptions.
Overview of the Product
IBM Z Anomaly Analytics revolutionizes operational efficiency by empowering enterprises to proactively detect and address anomalies in both log and metric data across hybrid environments. By leveraging intelligent anomaly detection, this solution ensures that potential disruptions are identified early, helping organizations prevent incidents and keep their services running seamlessly.
Why Choose IBM Z Anomaly Analytics?
Utilize detailed models of typical operations across IBM Z subsystems, including Db2®, CICS®, MQ®, IMS®, and z/OS® to ensure accurate anomaly identification.
Analyze live operational data and spot deviations instantly, allowing for immediate corrective actions.
Receive early notifications of unusual behaviors to mitigate risks before they impact business operations.
Visualize anomalies within their topological context, enabling quick identification of root causes and their operational impacts.
Seamlessly integrate with IBM Cloud Pak for Watson AIOps for rapid incident resolution across hybrid environments.
Leverage specialized metric-based and integrated log anomaly detection tools to keep your systems running smoothly.
What the Numbers say?
Trusted by Fortune 500 companies and leading global financial institutions, demonstrating its scalability and reliability.
30% faster issue detection and resolution, leading to significant cost savings.
Over 75% of enterprises leveraging IBM Z technologies use IBM Z Anomaly Analytics for proactive operations.
What the Numbers Say?
01
Lightning-fast data access, 8 times speedier, while slashing costs across cloud and on-premises data sources.
02
Free up data engineers for high-value tasks with 25-65% fewer ETL requests.
03
Say goodbye to $27 million in manual cataloging costs, just as IBM Global Chief Data Office did.
Features
Customized KPIs across IBM Z subsystems for operational excellence.
Detects and visualizes anomalies within logs alongside metric-based insights.
Correlate anomalies with hybrid application impacts, providing enterprise-wide visibility.
Visualize system and application dependencies to understand the broader impact of anomalies.
Integrate with IBM Cloud Pak for Watson AIOps for faster incident resolution.
Real-time operational insights powered by AI, ensuring optimal service availability.
Key Facts
IBM Z Anomaly Analytics leverages AI for real-time, data-driven insights.
Consistently outperforms traditional monitoring solutions by identifying anomalies before they disrupt operations.
Ideal for both large enterprises and small to medium-sized businesses across various industries.
What The Users Say
IBM Z Anomaly Analytics has transformed our ability to stay ahead of potential disruptions. The proactive anomaly detection and real-time insights have allowed us to enhance operational efficiency across our hybrid systems.
IT Operations Manager, Global Financial Institution
FAQs
IBM Z Anomaly Analytics is a machine learning-based tool designed to detect unusual behavior or system anomalies in mainframe environments before they lead to service disruptions. It continuously monitors operational data and uses advanced analytics to flag outliers or deviations from normal baselines—helping IT teams reduce downtime, improve SLA adherence, and optimize system health.
Z Anomaly Analytics uses unsupervised learning techniques to build a model of “normal” system behavior based on historical telemetry such as SMF, RMF, and log data. It then compares real-time data to this baseline to detect subtle performance or usage anomalies, alerting operators to investigate root causes early.
Z Anomaly Analytics is a key component of IBM’s AIOps strategy for mainframe operations. It integrates with other monitoring and incident management tools (like Instana and OMEGAMON) to enable predictive automation and root cause identification, creating a feedback loop for continuous service improvement.
The solution can detect CPU or memory usage spikes, storage I/O irregularities, transaction slowdowns, workload distribution changes, and even application behavior anomalies. It distinguishes between meaningful outliers and normal workload variability by learning from patterns over time.
Absolutely. For industries like banking, insurance, and telecom, where IBM Z runs mission-critical workloads, early anomaly detection ensures uptime, helps prevent fraud, and reduces operational risk. Z Anomaly Analytics provides visibility into z/OS and related environments, which is crucial for maintaining business continuity.
Yes. The tool allows administrators to configure detection rules, set alert thresholds, and monitor KPIs that matter to their specific use cases. It also supports visual dashboards and REST APIs for exporting alerts into third-party tools like Splunk or ServiceNow.
The tool integrates with IBM Z OMEGAMON, IBM Z Service Management Suite, and external observability platforms through APIs. It can export anomaly events into dashboards, trigger remediation workflows, or send alerts to SIEM and APM tools for unified operations management.
Resources
IBM Z Anomaly Analytics – AI-Powered Threat Detection
Ready to transform your operational performance with IBM Z Anomaly Analytics?