Intelligent Mainframe Management The Evolution of Expert Systems

Agenda 1 MAINFRAME AND DIGITAL TRANSFORMATION 2 CHALLENGES 3 WHAT IS INTELLIGENT MAINFRAME MANAGEMENT

The Way Customers Interact With Your Business Is Shifting Digital interaction is now the

Our Systems Can Be Used Anywhere, At Any Time SLAs are nearing, or already

The Mainframe keeps chugging behind the scenes 70% of transactions flow through mainframe 70%

Growing Workload + Growing Complexity A single transaction drives up to 100 system interactions

Now we got this Dev. Ops stuff Dev is pushing more changes, with greater

To summarize… 24/7/365 Operation 8 Workload Growth Increasing Complexity © 2016 CA. ALL RIGHTS

. . . Now look at what we’re managing! Some of the most complex

… and When Something Goes Wrong? © 2015 Diane Alber www. ca. com/ITcomics 10

Systems Malfunctions Happen Pressure is on to repair them as quickly as possible 11

Do Any of These Sound Familiar? Takes too long to identify root cause of

Here’s what happens today… Gather lots of data, multiple people, figure out what’s wrong

Information Overload Leads To Poor Decision Making Drowning in data 15 Sea of red

Guiding Principles to Achieve LEAN Mainframe Economics Exploit platform to remix MIPS, optimize performance

Building out System Intelligence- Lifting the Burden Let the DATA do the WORK for

Solution Vision: Leverage data and analytics to predict, avoid, and quickly remediate problems Use

Intelligent Mainframe Management When Something Goes Wrong, You Have Only One Place to Look

Intelligent Mainframe Management Take action earlier with embedded analytics which detects abnormal patterns of

From Reactive to Proactive Significantly Reduce Information Overload and False Alarms Drowning in data

Evolving to Expert Systems on the Mainframe Intelligent Analysis & Automation Reactive – MTTR

New: CA Mainframe Operations Intelligence (Suite) Adding Machine Learning Value to your Existing CA

Team Collaboration Hub Mainframe Team Center (MTC) Modern, consolidated view of information and activity

Flip the relationship: Don’t go to the Data, bring the data to you A

Multiple sources of data, single source of (linked) truth Ensure everyone is looking at

Predictive Analytics MTC-Operational Intelligence (OI) Detect abnormal patterns of operation, so you can take

Not just real-time truth, but past trends AND changes Correlate events and metrics to

Early Anomaly Detection Let the Data Do the Work Static Thresholds – Manual Real-time

Use Cases Problems, Opportunities and Solutions 30 © 2016 CA. ALL RIGHTS RESERVED.

Modern Tools & Views – Problem Avoidance/Remediation Who: USE CASE: • Systems Engineer •

Modern Tools & Views – Problem Avoidance/Remediation Who: USE CASE: • System Performance Analyst

Modern Tools & Views – Problem Avoidance/Remediation SOLUTION § Dashboards on demand rapid actions

Anomaly Detection – Problem Avoidance/Prediction Who: USE CASE: • Operations, Systems Programmer, • Network

Anomaly Detection – Problem Avoidance/Prediction SOLUTION § Detect anomalies predict issues real-time, alert based

Early Anomaly Detection Metric Let the Data do the Work Unlikely § Utilize historical

Magic Behind the Analytics – Data Science and Prediction Kernel Density Estimator Historical Input

Flexible Deployment – Minimize Cost and Risk Who: USE CASE: • Business Owner •

Simplified Deployment – Minimize Cost and Risk SOLUTION z/OS Correlations EXISTING PRODUCTS Metric Baseline

Commitment ANALYTICS CENTER OF EXCELLENCE DESIGN & VISUALIZATION LABS ROBUST PRODUCTS AND ENHANCEMENTS GROWING

Why CA’s Analytics for Mainframe EXPERTS IN OUR DOMAINS 41 END-TO-END INSIGHT UNIQUELY POSITIONED

Contact us to learn more about the data science algorithms behind the curtains We’ll

What Customers are Saying… “Looking forward to being able to better plan for Black

Questions? 44 © 2016 CA. ALL RIGHTS RESERVED.

Thank you. 46 © 2016 CA. ALL RIGHTS RESERVED.

For Informational Purposes Only Terms of this Presentation © 2016 CA. All rights reserved.

Slides: 46

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Intelligent Mainframe Management: The Evolution of Expert Systems David Myers Sr Principal Product Manager November 2016

The Mainframe keeps chugging behind the scenes 70% of transactions flow through mainframe 70% 55% 64% of enterprise apps rely on mainframe increase in mainframe workloads Sources: IBM, CA Voice of Customer Study conducted by IDC 5 © 2016 CA. ALL RIGHTS RESERVED. world’s corporate data resides on a mainframe

Growing Workload + Growing Complexity A single transaction drives up to 100 system interactions Fraud checks Purchase histories Customer loyalty User verification System level reconciliations Data encryption/decryption Real-time reporting Sources: IBM 6 © 2016 CA. ALL RIGHTS RESERVED.

. . . Now look at what we’re managing! Some of the most complex systems on the planet Fred John Storage Databases Debbie Network ? ? Sherman Partner Systems That guy in Secaucus Distributed Stuff Bill 9 © 2016 CA. ALL RIGHTS RESERVED. Systems / Infrastructure

Do Any of These Sound Familiar? Takes too long to identify root cause of problems and remediate them Too many lengthy war room calls involving way too many people Can’t efficiently communicate across our ops team – what’s going on in system and why Too many escalations, one-offs, and fires coming to too few mainframe experts 13 @CAWORLD #CAWORLD © © 2016 CA. ALL RIGHTS RESERVED.

Here’s what happens today… Gather lots of data, multiple people, figure out what’s wrong and what to do, do it… Systems / Subsystems The slow, manual, and painful part Monitoring Application Monitoring Network Monitoring Database Monitoring • • • Talk with people Investigate Poke / Prod Diagnose War Room Storage Monitoring Security Monitoring 14 © 2016 CA. ALL RIGHTS RESERVED. Remediation Activity

Guiding Principles to Achieve LEAN Mainframe Economics Exploit platform to remix MIPS, optimize performance and standardize to provide lowest cost per mission critical transaction 24 x 7 with high availability SYSTEM INTELLIGENCE Security and Compliance CULTURE SKILLS Secure data in rest and data in motion to control risk and also meet regulatory compliance needs Intelligent Operations 16 © 2016 CA. ALL RIGHTS RESERVED. Business Agility Adopt agile process and modernize tools, code in order to increase enterprisewide innovation velocity Automation and Management Improve efficiencies and empower staff to deliver more with less by deploying machine learning based automation

Building out System Intelligence- Lifting the Burden Let the DATA do the WORK for you ANALYTICAL TOOLS and SKILLS + IN-HOUSE DATA SCIENCE + IN-HOUSE DOMAIN EXPERTISE DATA-DRIVEN Analysis Decision Making Collaboration Automation … YOUR BURDEN 17 © 2016 CA. ALL RIGHTS RESERVED. Fueled by: § advanced analytic algorithms § machine learning Do MORE with LESS!

Solution Vision: Leverage data and analytics to predict, avoid, and quickly remediate problems Use the data you’re already collecting with the tools you use today! Systems / SYSVIEW Subsystems Monitoring CE-APM Application Automated Monitoring OPS/MVS Remediation Net. Master Detector Network Monitoring Activity Collaboration and Intelligence Engine Manual Database Remediation Monitoring Activity Feedback Loop Vantage Compliance Manager 18 Storage Monitoring Let the system learn from what’s been done in the past to improve and optimize future actions Security Monitoring © 2016 CA. ALL RIGHTS RESERVED.

Intelligent Mainframe Management When Something Goes Wrong, You Have Only One Place to Look Avoid Problems. Realize Deeper Insights. Optimize Operations. Storage Systems Intelligence Engine Across Silos. Correlate data. Network Applications Improve Customer Experiences. Automation Automatically. Data 19 © 2016 CA. ALL RIGHTS RESERVED.

Intelligent Mainframe Management Take action earlier with embedded analytics which detects abnormal patterns of operation Operational intelligence captures patterns, triggering dynamic and reliable problem remediation Predict Earlier Remediate Faster PREVENT PROBLEMS Improve Continuously Collaborate Efficiently Machine learning with operational feedback recommends the next best action for future event 20 Get everyone working together to isolate root causes faster with data insights from multiple sources © 2016 CA. ALL RIGHTS RESERVED.

From Reactive to Proactive Significantly Reduce Information Overload and False Alarms Drowning in data Sea of red Reactive fire fights FROM: Fewer false positives TO: Reactive Network Ops Center Patchwork Monitoring 21 Dynamic alerting Faster MTTR and RCA Proactive/Predictive Consolidated Alerts and Guidance Based on Machine Learning © 2016 CA. ALL RIGHTS RESERVED.

Evolving to Expert Systems on the Mainframe Intelligent Analysis & Automation Reactive – MTTR & Firefighting Proactive – Optimized Performance & Efficiency Automation INTELLIGENT AUTOMATION ENTERPRISE SUPPORT Generalist ANOMALY DETECTION Specialists COLLABORATION MAINFRAME OPERATIONS § React to events § Self service views § Modern U/X Experts 22 Data and Event Processing § Predict anomalies § Proactive response PATTERN DISCOVERY § Discover interdependencies § Predict business service disruption § Visualize cascading failures Machine Learning Algorithms © 2016 CA. ALL RIGHTS RESERVED. § Root cause analysis § Resolution guidance § Automate response Automation

New: CA Mainframe Operations Intelligence (Suite) Adding Machine Learning Value to your Existing CA Software Investments Highlights Correlate, Learn and Automate Analytics § Aggregate data across system domains § Correlate metrics across domains via machine learning Automation Database Network Systems § Understand system and application interdependencies End-to-End Monitoring and Management CA MAINFRAME OPERATIONS INTELLIGENCE 23 § Understand events affecting services § Knowledge capture and directive resolution § Create automation in real time Bottom Line § Reduced MTTR § Reduce SME dependence for issue triage/investigation § Improved end user experience © 2016 CA. ALL RIGHTS RESERVED.

Team Collaboration Hub Mainframe Team Center (MTC) Modern, consolidated view of information and activity across your mainframe Key Features • • • Vantage 24 SYSVIEW Net. Master © 2016 CA. ALL RIGHTS RESERVED. • Modernized UI for Management tools Composable Information Radiator Out-of-the-box Widgets Personal Dashboards Out-of-the box Dashboard Templates Configurable Metrics and Alarms Authorized Management Actions

Flip the relationship: Don’t go to the Data, bring the data to you A single board displaying the right set of key information from across your Mainframe Network Monitor Performance Monitor Cross. Mainframe View Open Source Tool Vendor Tool Home Grown tool Storage Monitor 25 © 2016 CA. ALL RIGHTS RESERVED.

Multiple sources of data, single source of (linked) truth Ensure everyone is looking at the same set of data to limit discrepancies and disagreement That’s on me… r. R The Wa oom Open Source Tool Vendor Tool Network Monitor Cross. Mainframe View Storage Monitor Home Grown tool 26 Performance Monitor © 2016 CA. ALL RIGHTS RESERVED.

Predictive Analytics MTC-Operational Intelligence (OI) Detect abnormal patterns of operation, so you can take action before the fire starts Key Features • • SYSVIEW 27 © 2016 CA. ALL RIGHTS RESERVED. Data Streaming APIs Historical Data Warehouse Historical Analysis tools Dynamic Baselining and Threshold Management Anomaly Detection Alarm Management and Notifications Low-touch Install Offload eligible (z. IFL)

Not just real-time truth, but past trends AND changes Correlate events and metrics to quickly get to potential root causes This says you changed a port config 10 mins before the problem hit r. R The Wa oom Open Source Tool Vendor Tool Network Monitor Metric and Change History Performance Monitor Storage Monitor Home Grown tool 28 Well that Oh…my bad shouldn’t/couldn’t have caused this? © 2016 CA. ALL RIGHTS RESERVED.

Early Anomaly Detection Let the Data Do the Work Static Thresholds – Manual Real-time Dynamic Thresholds – Historical Trending Adaptive Thresholds – Machine-Learning Dramatically reduce false positive noise! 29 © 2016 CA. ALL RIGHTS RESERVED.

Modern Tools & Views – Problem Avoidance/Remediation Who: USE CASE: • Systems Engineer • Network Engineer • Application DBA • Level 1 Support Analyst Sherman, Debbie, and Fred (skilled technical experts) are constantly seeking ways to make their jobs easier, resolve problems faster, transition to being proactive to avoid impacting events. They would like modern graphics to enable them to quickly identify where problems are occurring. Pete’s job requires him to monitor the Sysplex and take actions to keep work flowing through the systems. He does not have the experience nor skill Sherman, Debbie, and Fred have. Pete is accustomed to web interfaces and visual graphics. Pete would an interactive, modern web interface to monitor the Sysplex so that he can be as responsive and proactive as Sherman, Debbie, and Fred. PROBLEM § “Ability to see multiple views of data ” § “Ability to create views of information faster ” § “Current U/X prevents easy collaboration and access to data ” 31 © 2016 CA. ALL RIGHTS RESERVED.

Modern Tools & Views – Problem Avoidance/Remediation Who: USE CASE: • System Performance Analyst Ralph (skilled System Performance Analyst) is constantly monitoring systems to identify and resolve performance problems faster. He would like to be able to see problems coming. In either case, when Ralph identifies issues, he contacts Sherman, Debbie, and Fred to identify if the problems are in their areas, and if so, to resolve them. • Systems Engineer • Network Engineer • Application DBA Ralph, Sherman, Debbie and Fred are accustomed to web interfaces and visual graphics. They would like to have an interactive, modern web interface that they could share while performing root cause analysis on anomalies in system behavior. PROBLEM § “Ability to see multiple views of data ” § “Ability to create views of information faster ” § “Current U/X prevents easy collaboration and access to data ” 32 © 2016 CA. ALL RIGHTS RESERVED.

Modern Tools & Views – Problem Avoidance/Remediation SOLUTION § Dashboards on demand rapid actions § Leverage UX that complements SME existing workflow § Simplified U/X – browser access & designed for collaboration BOTTOM LINE § High Availability § Problem avoidance § Reduced MTTR § Reduce SME dependence for issue detection 33 © 2016 CA. ALL RIGHTS RESERVED.

Anomaly Detection – Problem Avoidance/Prediction Who: USE CASE: • Operations, Systems Programmer, • Network Engineer, Application DBA Sherman, Debbie, and Fred have deep experience and skills in their respective areas. They hate being called after a system problem has occurred and being asked to prove that their area was at fault or innocent. They would like a system that tells them when their area is behaving abnormally, so that they can address it before it comes to the attention of the Systems Performance Engineer. PROBLEM § “Avoid, detect and predict issues that might be a problem ” § “Thresholds are hard to maintain and generate large amount of false positives ” § “Ability to see multiple views of data ” § “Ability to create views of information faster ” § “Current U/X prevents easy collaboration and access to analytics ” 34 © 2016 CA. ALL RIGHTS RESERVED.

Anomaly Detection – Problem Avoidance/Prediction SOLUTION § Detect anomalies predict issues real-time, alert based on predefined rules § Leverage historical data and machine learning for dynamic thresholds § Simplified U/X – browser access & designed for collaboration BOTTOM LINE § High Availability § Problem avoidance § Reduced MTTR § Reduce SME dependence for issue detection 35 © 2016 CA. ALL RIGHTS RESERVED.

Early Anomaly Detection Metric Let the Data do the Work Unlikely § Utilize historical data Less Likely § Define bands of Likely and Unlikely § Map real-time metric streams against system defined normal § Multi-point alerts generated using industry-standard Western-Electric rules § Make static thresholds optional! Most Likely Tasks ready to be dispatched Time 36 Typical Volatility Anomaly © 2016 CA. ALL RIGHTS RESERVED.

Magic Behind the Analytics – Data Science and Prediction Kernel Density Estimator Historical Input Data, Same Stage of Business Cycle Wavelet Decomposition § Dynamically and automatically determine baselines and thresholds Predictive Model – Business cycles Exponentially. Weighted Moving. Average 37 § Generate alerts for abnormal scenarios, eliminate false positives and minimize false negatives – Natural volatility © 2016 CA. ALL RIGHTS RESERVED.

Flexible Deployment – Minimize Cost and Risk Who: USE CASE: • Business Owner • Technology Owner As someone owning IT operations and responsible for technology progress, my Mainframe systems should exploit platforms like Linux (X 86 & Z) to offload data processing and non essential management capabilities. Lack of this capability limits the ability to extend the strengths of the mainframe with next generation technology that is supported on Linux PROBLEM § “Help me utilize the cheap computing infrastructure on X 86” § “We plan to expand our z ecosystem to include Linux and require tools to leverage our strategy” § “Ensuring technology progress without losing the reliability/security of MF is high value goal” § ”Ensure resource intensive analytics solution do not increase my operations costs significantly” 38 © 2016 CA. ALL RIGHTS RESERVED.

Simplified Deployment – Minimize Cost and Risk SOLUTION z/OS Correlations EXISTING PRODUCTS Metric Baseline Rest APIs Performance Management Database Storage Management ANALYTICS STREAM Aggregation Rest API Anomaly Detection Historical Data Web-based UI Software Virtual Appliance Browser 39 © 2016 CA. ALL RIGHTS RESERVED. Virtual appliance Containerized Plug-n-play Simple Config GUI BENEFITS Low Cost computing Non-Invasive Retains Security Setup in Minutes

Commitment ANALYTICS CENTER OF EXCELLENCE DESIGN & VISUALIZATION LABS ROBUST PRODUCTS AND ENHANCEMENTS GROWING RESEARCH & IP PORTFOLIO CA Analytics ANALYTICS REFERENCE ARCHITECTURE 40 DATA SCIENCE LABS © 2016 CA. ALL RIGHTS RESERVED.

Contact us to learn more about the data science algorithms behind the curtains We’ll run YOUR data through our intelligence engine, and you’ll see why customers are so excited about this new solution! ca. com/intelligent-mainframe 42 © 2016 CA. ALL RIGHTS RESERVED.

What Customers are Saying… “Looking forward to being able to better plan for Black Friday and Cyber Monday and trend performance of specific weeks, Yo. Y. "This is great stuff… …tremendously helpful!” “Will help my teams prevent costly downtime and address problems much faster”. CA Mainframe Operations Intelligence “We’re very excited about using …static thresholds in use today are hurting us in multiple ways. ” "This is right where we want your tool to be… …I love it already!“ 43 “This is far beyond what your competitors are doing. ” © 2016 CA. ALL RIGHTS RESERVED.

For Informational Purposes Only Terms of this Presentation © 2016 CA. All rights reserved. All trademarks referenced herein belong to their respective companies. The presentation provided at CA World 2016 is intended for information purposes only and does not form any type of warranty. Some of the specific slides with customer references relate to customer's specific use and experience of CA products and solutions so actual results may vary. Certain information in this presentation may outline CA’s general product direction. This presentation shall not serve to (i) affect the rights and/or obligations of CA or its licensees under any existing or future license agreement or services agreement relating to any CA software product; or (ii) amend any product documentation or specifications for any CA software product. This presentation is based on current information and resource allocations as of November 1, 2016, and is subject to change or withdrawal by CA at any time without notice. The development, release and timing of any features or functionality described in this presentation remain at CA’s sole discretion. Notwithstanding anything in this presentation to the contrary, upon the general availability of any future CA product release referenced in this presentation, CA may make such release available to new licensees in the form of a regularly scheduled major product release. Such release may be made available to licensees of the product who are active subscribers to CA maintenance and support, on a when and ifavailable basis. The information in this presentation is not deemed to be incorporated into any contract. 47 © 2016 CA. ALL RIGHTS RESERVED.