IBM Z® IntelliMagic Vision enables performance analysts to manage and optimize their z/OS CICS regions and transactions more effectively and efficiently, and proactively assess the health of their CICS regions.
Access built-in health insights that rate hundreds of critical metrics to proactively identify risks to your application health and performance. AI-derived anomaly detection highlights statistically significant changes, accelerating problem-solving.
Use thousands of out-of-the-box reports combined with a powerful, intuitive GUI plus real-time comparisons and editing. Let context-sensitive drill-down capabilities help you to maximize time spent preventing and resolving issues. Minimize downtime without the need for custom coding.
Augment the effectiveness of staff with interactive, customizable and shareable dashboards, built-in explanations and extensive drill downs. Use AI as a force multiplier to expedite learning, promote collaboration and enhance analytical effectiveness.
What's included
CICS SMF transaction data is a rich source of performance insights, but its volume can make analysis challenging when using traditional approaches. Proactive assessment of key statistics metrics across all regions helps identify potential risks to availability.
IBM Z IntelliMagic Vision assesses key CICS metrics against best practice values to identify potential risks to availability for investigation. View the assessments in user-defined logical groupings in red, yellow and green. Expand to view more levels of detail, with all regions making up the selected group or metric time charts.
Many types of CICS statistics data can be explored at deeper levels of detail. For example, file name, enqueue name, transaction class and TCB mode. This image shows the use of dynamic navigation and context-sensitive drill downs to determine which CICS storage areas are experiencing Short on Storage conditions.
CICS workload analysis usually starts with a “Top n” view of transactions by CPU consumption or by transaction volume. Next, you can focus on response time profiles with almost 100 timing buckets that are initially grouped into high-level summary categories. You can also view detailed explanations of the categories of interest.
After the initial response time display identifies the primary contributors to response time, drill downs can help identify the specific components of interest. If a primary response time category for a transaction is “Total I/O Wait Time” (as seen in the previous image), its sub-sections can be examined with a single click.
The ability to compare profiles across transactions by the primary CICS response time categories can also provide helpful insights. This example shows CPU per CICS transaction across the first set of transactions. Global filters can also be specified to further focus the selected transactions.
Comparisons across multiple time intervals are often of interest when analyzing the impact of the implementation of an application release on CPU per transaction. Throughout the product, IBM Z IntelliMagic Vision enables at-a-glance value comparisons across any two-time intervals for analysis.
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If investigating a response time issue, you can begin from a response time view. To further isolate the issue, you may examine times for the selected transaction across systems or regions. This image displays an example where a specific transaction timing component differs significantly across 2 sets of systems.
Because Db2 accounting data (SMF 101) captures the CICS transaction ID, the product seamlessly integrates key metrics from Db2 with the CICS SMF data. These charts integrate metrics from the CICS perspective on the first row (based on the transaction ID) and the Db2 perspective on the last row (by using the correlation ID from the accounting data).
Integrated visibility across various types of z/OS data aids CICS and all types of performance analysis. In this scenario, a prior view from systems data indicates an unmet WLM goal for selected time intervals, and shows corresponding increased volumes of a long-running transaction.
More than 250 non-timing fields in the CICS 110.1 records enable detailed analysis and are organized into subgroups. The customized dashboard in this image shows examples of several of these, including Db2 SQL calls per CICS transaction, log stream writes, program loads and file gets.
Advantages to adopting a cloud model include rapid implementation (no lead time to install and set up the product locally), minimal setup (only for transmitting SMF data), offloading staff resources and access to IntelliMagic consulting services to supplement local skills.