Manage MQ Queue Managers and Activity with IBM Z IntelliMagic Vision for z/OS

    IBM Z IntelliMagic Vision for z/OS enables performance analysts to manage and optimize their z/OS MQ configurations and activity more effectively and efficiently, as well as proactively assess the health of their queue managers.

    View the video for an example of those capabilities.

            
        

            
        

    Manage CPU Consumption and Optimize MQ Performance with Built-In Health Insights

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    Proactively Analyze and Prevent Risks

    Utilize built-in health insights and artificial intelligence to proactively identify risks, ensure availability, and optimize your MQ environment. 

            
        

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    Save Time and Quickly Resolve Issues

    Quickly spot and resolve issues using thousands of out-of-the-box reports, built-in live edit, compare, share, and drill down features. 

            
        

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    Optimize and Lower IBM Software Costs

    Utilize the same unrivaled insights into CPU consumption and drivers of software costs used by Watson & Walker to reduce your costs. 

            
        

    Built-In Intelligence at Your Fingertips

    Proactively Assess Key Queue Manager Metrics to Enhance Availability

    Proactively Assess Key Queue Manager Metrics to Enhance Availability

    As with Db2, responsive performance from MQ relies on data residing in memory, so buffer pool management is an important aspect of managing MQ performance.
    IBM Z IntelliMagic Vision for z/OS automatically assesses every buffer pool in every queue manager to identify areas that may warrant additional investigation and presents these findings in a red/yellow/green manner that can be quickly consumed.
    Drilldown capabilities into each metric facilitate quick follow-on analysis.

    Profile Queue Manager Workloads

    Profile Queue Manager Workloads

    A view of the number of requests by type of MQ command can be a good starting point for identifying a workload baseline, as well as an indicator of any significant workload changes.
    Easy visibility into this data shows (in this example) the volume of requests to PUT messages to the queues, which queue managers have the most activity, the time of day profile, etc.

    Analyze Buffer Pool Utilizations

    Analyze Buffer Pool Utilizations for MQ Subsystems

    Views of buffer pool utilizations over time can indicate when these values are approaching thresholds that prompt automated de-staging to disk.
    This example shows an extended interval when buffer pool 4 is nearing the 85% threshold that triggers asynchronous de-staging.

    Monitor MQ Logging Infrastructure

    Monitor MQ Logging Infrastructure

    As with Db2, a well-performing MQ logging infrastructure is essential to support recovery and backout (driven largely by persistent messages) without impacting ongoing performance.
    Log Manager metrics can help identify any bottlenecks that may be occurring in log processing.
    One metric that may be useful from a profiling perspective is the volume of data being logged.

    View Activity by Queue Name

    View zOS Activity by MQ Queue Name

    MQ Accounting data provides detailed activity metrics at many levels, which are invaluable to performance specialists as they investigate application problems and carry out performance tuning.

    This example of command rates by queue name shows unique distributions across various types of queues, including a cluster transmission queue (first, no GETs), queues that process primarily PUTs and GETs in comparable numbers (second and third), and queues with high levels of OPEN and CLOSE activity (fourth and fifth).

    Breakout MQ CPU by Workload Drivers

    Breakout MQ CPU by Workload Drivers

    Another level of detail found in the MQ Accounting data is the type of work calling MQ (“connection type”).
    In this example, the three primary drivers of MQ CPU are channel initiators and work arriving from IMS and CICS.

    Analyze CPU per MQ Call

    Analyze CPU per MQ Call

    Other types of analysis may focus on metrics such as CPU and elapsed times on a per-call basis.
    Though the absolute numbers are small, this view indicates that CPU time per MQGET call for work arriving from IMS is approximately double that of other types of work.

    Compare and Correlate Multiple Metrics

    Compare and Correlate Multiple Metrics

    The capability to customize reports to combine multiple variables to analyze potential correlations can greatly aid analysis.
    In many of today’s solutions that rely on catalogs of static reports, adhoc analysis like this typically requires the coding effort to develop a new report.
    This example combining the rate of MQ GET calls and the average elapsed time for work generated by a specific CICS transaction shows a strong correlation.

    Drilldown to Isolate Message Length Profiles by CICS Transactions

    Drilldown to Isolate Message Length Profiles by CICS Transactions

    Though most sites tend to have massive volumes of MQ Accounting data, dynamic navigation and context-sensitive drilldown capabilities enable the analyst to quickly focus on a specific subset of the data.
    In this example of message length distribution data, drilldowns into work originating from CICS and then further by CICS transaction ID profile the length of messages being “PUT” by transaction.

    AIOps via SaaS Delivery

    Cloud Software as a Service (SaaS) icon

    Advantages to adopting a cloud model include rapid implementation (no lead time to install and setup the product locally), minimal setup (only for transmitting SMF data), offloading staff resources required to deal with SMF processing issues or to install product maintenance, and easy access to IntelliMagic consulting services to supplement local skills.

    Proactively Assess Key Queue Manager Metrics to Enhance Availability

    Proactively Assess Key Queue Manager Metrics to Enhance Availability

    As with Db2, responsive performance from MQ relies on data residing in memory, so buffer pool management is an important aspect of managing MQ performance.
    IBM Z IntelliMagic Vision for z/OS automatically assesses every buffer pool in every queue manager to identify areas that may warrant additional investigation and presents these findings in a red/yellow/green manner that can be quickly consumed.
    Drilldown capabilities into each metric facilitate quick follow-on analysis.

    Profile Queue Manager Workloads

    Profile Queue Manager Workloads

    A view of the number of requests by type of MQ command can be a good starting point for identifying a workload baseline, as well as an indicator of any significant workload changes.
    Easy visibility into this data shows (in this example) the volume of requests to PUT messages to the queues, which queue managers have the most activity, the time of day profile, etc.

    Analyze Buffer Pool Utilizations

    Analyze Buffer Pool Utilizations for MQ Subsystems

    Views of buffer pool utilizations over time can indicate when these values are approaching thresholds that prompt automated de-staging to disk.
    This example shows an extended interval when buffer pool 4 is nearing the 85% threshold that triggers asynchronous de-staging.

    Monitor MQ Logging Infrastructure

    Monitor MQ Logging Infrastructure

    As with Db2, a well-performing MQ logging infrastructure is essential to support recovery and backout (driven largely by persistent messages) without impacting ongoing performance.
    Log Manager metrics can help identify any bottlenecks that may be occurring in log processing.
    One metric that may be useful from a profiling perspective is the volume of data being logged.

    View Activity by Queue Name

    View zOS Activity by MQ Queue Name

    MQ Accounting data provides detailed activity metrics at many levels, which are invaluable to performance specialists as they investigate application problems and carry out performance tuning.

    This example of command rates by queue name shows unique distributions across various types of queues, including a cluster transmission queue (first, no GETs), queues that process primarily PUTs and GETs in comparable numbers (second and third), and queues with high levels of OPEN and CLOSE activity (fourth and fifth).

    Breakout MQ CPU by Workload Drivers

    Breakout MQ CPU by Workload Drivers

    Another level of detail found in the MQ Accounting data is the type of work calling MQ (“connection type”).
    In this example, the three primary drivers of MQ CPU are channel initiators and work arriving from IMS and CICS.

    Analyze CPU per MQ Call

    Analyze CPU per MQ Call

    Other types of analysis may focus on metrics such as CPU and elapsed times on a per-call basis.
    Though the absolute numbers are small, this view indicates that CPU time per MQGET call for work arriving from IMS is approximately double that of other types of work.

    Compare and Correlate Multiple Metrics

    Compare and Correlate Multiple Metrics

    The capability to customize reports to combine multiple variables to analyze potential correlations can greatly aid analysis.
    In many of today’s solutions that rely on catalogs of static reports, adhoc analysis like this typically requires the coding effort to develop a new report.
    This example combining the rate of MQ GET calls and the average elapsed time for work generated by a specific CICS transaction shows a strong correlation.

    Drilldown to Isolate Message Length Profiles by CICS Transactions

    Drilldown to Isolate Message Length Profiles by CICS Transactions

    Though most sites tend to have massive volumes of MQ Accounting data, dynamic navigation and context-sensitive drilldown capabilities enable the analyst to quickly focus on a specific subset of the data.
    In this example of message length distribution data, drilldowns into work originating from CICS and then further by CICS transaction ID profile the length of messages being “PUT” by transaction.

    AIOps via SaaS Delivery

    Cloud Software as a Service (SaaS) icon

    Advantages to adopting a cloud model include rapid implementation (no lead time to install and setup the product locally), minimal setup (only for transmitting SMF data), offloading staff resources required to deal with SMF processing issues or to install product maintenance, and easy access to IntelliMagic consulting services to supplement local skills.

    End-to-End Infrastructure Analytics for z/OS Performance Management

    zSystems Performance Management

    Optimize z/OS Mainframe Systems Management with Availability Intelligence

    Benefits

    Optimize z/OS Systems performance management using AI-driven analytics to proactively monitor and manage your z/OS environment, prevent disruptions, reduce costs, and preserve the reliability and availability that mainframes are known for.
    Explore z/OS Systems Performance Analytics

    Db2 Performance Management

    Prevent Availability Risks and Optimize Db2 Performance

    Benefits

    The volume and complexity of Db2 Statistics data and Db2 Accounting data creates a major challenge for analysts who want to derive value from the rich metrics available.
    Easy visibility into key Db2 metrics through SMF records is crucial to proactively prevent availability risks and to effectively manage and optimize performance.
    Explore Db2 Performance Analytics

    CICS Performance Management

    Monitor and Profile CICS Transactions and Regions with IBM Z IntelliMagic Vision for z/OS

    Benefits

    CICS SMF Transaction data is a rich source of performance insights, but its volume can make analysis challenging using traditional approaches that rely on static reports. Proactive assessment of key Statistics metrics across all regions is essential to identify potential risks to availability.
    IBM Z IntelliMagic Vision for z/OS enables performance analysts to manage and optimize their z/OS CICS transactions more effectively and efficiently, as well as proactively assess the health of their CICS regions.
    Explore CICS Performance Analytics

    Virtual Tape Performance Management

    Proactively Manage Virtual and Physical Tape Environments

    Benefits

    With tape virtualization, tape storage became easier and more economical, but at the same time, more difficult to understand which changes or hardware upgrades are the best choices. With tape libraries being shared across multiple z/OS images, the full picture can only be obtained by aggregating workload and tape hardware information from all z/OS LPARs.
    IBM Z IntelliMagic Vision for z/OS enables performance analysts to manage and optimize their z/OS Virtual Tape environments more effectively and efficiently.
    Explore Tape Performance Analytics

    Disk & Replication Performance Management

    Automatically Detect Disk Performance Risks & Quickly Resolve Issues

    Benefits

    As Disk speeds and throughputs have increased, z/OS applications have come to rely on fast and consistent storage performance. To respond quickly to unexpected disk and replication issues, it is essential that you have insight into the health of the various components in your storage environment.
    IBM Z IntelliMagic Vision for z/OS enables performance analysts to manage and optimize their z/OS Disk and Replication environment more effectively and efficiently.
    Explore Disk Performance Analytics

    MQ Performance Management

    Optimize and Analyze MQ Activity and Performance

    Benefits

    MQ is widely used across z/OS environments, but sites often find it challenging to derive the valuable performance insights potentially available from MQ SMF Statistics and Accounting data due to limitations in existing reporting and available tooling.
    IBM Z IntelliMagic Vision for z/OS enables performance analysts to manage and optimize their z/OS MQ configurations and activity more effectively and efficiently, as well as proactively assess the health of their queue managers.
    Explore MQ Performance Analytics

    z/OS Network Performance Management

    Automatically Monitor Mainframe Network Security and Protect Your Data

    Benefits

    TCP/IP is the core of the communication for the z/OS mainframe, both for traffic into and out of the mainframe and internal communication among z/OS images and processor complexes. Proper management is necessary to secure and protect system availability.
    IBM Z IntelliMagic Vision for z/OS automatically generates GUI-based, interactive, IBM best-practice compliant rated reports that proactively identify areas that indicate potential upcoming risk to TCP/IP health, performance, and security.
    Explore z/OS Network Performance Analytics

    z/OS Connect: Modern Mainframe API Environment

    Optimizing Mainframe API Monitoring for Improved Resource Management

    Benefits

    IBM Z IntelliMagic Vision for z/OS enhances mainframe API monitoring and profiling, providing crucial visibility to address issues at the API or service level, ultimately aiding performance analysts in better resource planning and management reporting.
    Explore z/OS Connect Analytics

    See Why IntelliMagic is Trusted by Some of the World’s Largest Mainframe Sites

    We use [IntelliMagic] Vision [for z/OS] to provide information for our mainframe disk environments. [IntelliMagic] Vision [for z/OS] provides many reports to help us understand our disk performance activity. This insures that we provide the best response time to the mainframe. It also provide us insight to capacity planning as well
    John Virzi | TIAA
    Read our case
    The ability to dive deep into the graphs is something that is provided only by IntelliMagic, no other monitoring software, real-time or not, has that ability.
    James Schlosser | Northwestern Mutual
    Read our case
    I use IntelliMagic Vision to analyze the peaks of mainframe cpu usage. IntelliMagic Vision has helped me to find opportunities to reduce cpu usage by focusing on key days of the month and key hours. Some of the reports have uncovered things I was simply not aware of. When there are many things that could be addressed it is helpful to see what will have the most impact.
    Loretta Cyr | The Hartford
    Read our case
    IntelliMagic Vision for z/OS support is first class. The 'IntelliMagicians' are both experts in the use of their product AND experts in the data that is being reported on. They have many years of experience, excellent relationships with their customers, and a real enthusiasm for analyzing and understanding what is happening in the z/OS systems they are analyzing. We couldn't ask for better partners
    Frank Kyne | Watson & Walker
    Read our case
    As a Software as a Service (SaaS) cloud solution, IntelliMagic Vision allows our infrastructure engineers to use the tool to manage our resources - rather than managing the installation/customization, and upgrade of the tool itself.
    Anonymous-04 | Insurance Company
    Read our case
    We started with a test installation of the DASD analyses and then decided to use them. Then we gradually expanded the functions (system, CF, XCF, MQ, TCP/IP and tape). This year Db2 was added and we have replaced and optimized SAS programs with IntelliMagic Vision for z/OS.
    Walter Auerochs | DATEV
    Read our case

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    Solutions for your Problems

    Elevate IT Team Impact

    Empower new staff and experts. Replace antiquated reporting with automated, intelligent analytics.

    Benefits

    Artificial Intelligence using built-in expert knowledge and statistics assesses and rates key metrics as good versus bad from a performance or efficiency perspective for the analyst.
    Force multiplier - Invite AI to the team to help both new and expert team members in a tight job market.
    Cloud Delivery - Immediate access with no maintenance needed.

    Optimize & Reduce Costs Safely

    Save money without compromising service levels or availability.

    Benefits

    Reduce cost with superior visibility into drivers of cost such as inefficient CPU utilization, configuration and priority issues, imbalance of workloads across hardware resources, consolidation opportunities, etc.
    Reduce hardware spend without negative impact on service levels.
    Avoid the costs of service delivery problems without both human cost and application unavailability cost.

    Prevent Performance Problems

    Predict and Prevent many IT issues without incurring typical false positive and false negative issues.

    Benefits

    Automatically quantify risks in the z/OS infrastructure for peak workloads or configuration issues prior to production impact being felt by application end-users. Go beyond KPI to KRI (Key Risk Indicators) root cause monitoring.
    Continuous Health Assessment of application and infrastructure stress; assesses millions of metrics using context-specific expert knowledge and statistical techniques.

    Resolve Issues Quickly

    Accelerate Mean Time To Resolution for unpredictable problems with AI-augmented diagnosis.

    Benefits

    Rapidly identify where problems are occurring with infrastructure wide exception (anomaly) tables, intelligent navigation through the data from big picture to extremely granular levels, automated compare of time periods, and more.
    See and understand what applications are affected, what part of the infrastructure, what time frames, and get clues as to probable cause.

    Flexible Deployment and Monitoring

    In the Cloud

    Cloud based deployment can be accessed from everywhere in the world and is easy to share with colleagues

    Services & Support

    Take advantage of IntelliMagic's experienced performance experts for standalone custom services or daily monitoring

    On Premise

    Install the software on premise and use it offline for total control of your installation

    Optimize and Analyze MQ Activity and Performance

    MQ is widely used across z/OS environments, but sites often find it challenging to derive the valuable performance insights potentially available from MQ SMF Statistics and Accounting data due to limitations in existing reporting and available tooling.

    When managing your MQ environment, you need an easy and effective way to focus your analysis so you can rapidly find what you are looking for.

    IBM Z IntelliMagic Vision for z/OS provides GUI-based, interactive reports with dynamic navigation and context-sensitive drilldowns to facilitate rapid and focused access to MQ data to manage, tune, and optimize your environment.

    With IBM Z IntelliMagic Vision for z/OS, you will be able to:

    • Profile MQ queue manager and buffer pool activity
    • Easily view key logging metrics as well as those produced by every MQ component
    • Proactively assess the health of all MQ queue managers
    • Analyze elapsed and CPU times for MQ activity at detailed levels (e.g., by queue name or connection type)

    IBM Z IntelliMagic Vision for z/OS offers you the out-of-the-box visibility and seamless navigation to manage every component of your z Systems infrastructure under a single solution.

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