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CA Mainframe Resource Intelligence

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In medicine - an MRI can quickly reveal a hidden ailment and actionable insight to get better. For IT and business leaders whose key concern with the mainframe is the platform costs and lean operations - the CA Mainframe Resource Intelligene reveals multiple sources of hidden mainframe costs and operational inefficiencies along with actionable recommendations.View this slideshare to understand how this new SaaS offering from CA brings together automation, speed, analytics and mainframe expertise of 40+ years. CA Mainframe Resource Intelligence reports answer your CIO’s toughest questions about mainframe optimization and potential for digital transformation.

For more information, please contact your account director or mainframe specialist at:
http://ow.ly/PALG50htHgF

Published in: Technology
  • CA Mainframe Resource Intelligence acts like an MRI for your mainframe environment; helping you assess where you are today on your optimization journey and prescribes tools, automation and best practices, ultimately delivering actionable insights and practical reports to guide business results. Get started - https://www.ca.com/us/contact/mainframe-mri.html
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CA Mainframe Resource Intelligence

  1. 1. CA Mainframe Resource Intelligence
  2. 2. CIO Questions and Desired Outcomes Free Up Resources to Invest in the Journey Towards Digital Enterprise 2 What is my current state of process speed and agility to build services as quickly and cost-effectively as on the cloud? What is the state of skills, apps and systems performance to allow data and AI to lower MTTR? What is the level of systems automation to get 99.999% uptime and availability How secure is our data and how compliant are we with GDPR and other regulations? What is the current level of SW and HW resources utilization and can we free up resources to self-fund digital initiatives? Economics
  3. 3. Understanding Where You are vs. Desired Outcomes? 3 In Medicine Patient – initial symptom Run scan and interpret based on years of training, tests, reports, benchmarks and best practices Get medical report Get a Diagnoses For better health outcomes Define the area/domain to scan (economics, security etc.) Run scan and upload data Get report CA Recommendations for Better business outcomes 1 2 3 4 In Mainframe Rx
  4. 4. Current State Mainframe Organizations are Dealing with these Challenges 4 ECONOMICS PROCESS 40%spend is SW 14%SW spend wasted in product redundancy 35%of spend is IBM MLC • Unplanned spikes • Inability to predict capacity • CPU wasted utilization – inefficient or incomplete use of platform advances SYSTEMS $150Moutage costs • High MTTR • Too much data to analyze Challenge: can’t find skills • Green screens • Diverse complex workloads 1BLines of COBOL • Large monolithic code base • 2-3 releases only - changes limited to maintenance windows • Waterfall process SECURITY 70%of corporate data on platform now accessible from anywhere $5Bin Ransomware • Unknown, data not covered by typical audits
  5. 5. Goal Apply Best Practices to Drive Business Outcomes 5  Dynamically manage capacity  Leverage Specialty Engines  Software Consolidation OPTIMIZE PLATFORM ECONOMICS MLC Reduction CPU Reduction SW license cost reduction  Adopt open modern tools  Automate to shift “ops” left to enable continuous delivery  Everything as a service IMPLEMENT AN AGILE DEVOPS TOOLCHAIN  Augment people with machine Intelligence  Automatic remediation  Modern UX and Visual analytics  Leverage experts to train AI/Machine Learning algorithms CREATE A SELF DRIVING DATACENTER MTTR decrease SLA prediction Release velocity increase Defect reduction  Discover and protect sensitive data  Implement multi-factor authentication  Reduce risk by Trusted user management ENABLE DATA & USER CENTRIC SECURITY Compliance fulfillment (GDPR, STIGS, PCI) BESTPRACTICESOUTCOME KPITO IMPACT ECONOMICS PROCESSSYSTEMSSECURITY
  6. 6. Introducing CA Mainframe Resource Intelligence Automated Assessment SaaS Offering to Help you Reduce Cost and Guide you on Digital Transformation 6 Scan Upload all your mainframe operational data in one spot to get a handle on current performance. Assess Leverage CA’s automation, AI, machine learning and 30+ years best practices expertise to analyze and understand possible savings and improvements. Report Easy to use reports are generated in 2 weeks, not months. Gain actionable recommendations to guide next steps.
  7. 7. Let’s Delight Your CFO Run an Economics Assessment 7 How can you simplify what you have.. ..and continuously Iterate and Optimize to reduce both CAPEX and OPEX? FTE CAPACITY CURRENT DESIRED SOFTWARE TOOLS ECONOMICS ASSESSMENT
  8. 8. Predicting Capacity Mainframe Economics Challenge 8 ECONOMICS ASSESSMENT ~ 35%of Mainframe Spend Situation • Capacity spikes • Missed SLAs • Over-provisioning • Modest but periodic MLC price increases add up $$$MMs
  9. 9. Under-utilization of Tools Mainframe Economics Concern Source: https://diginomica.com/2017/07/20/mainframe-still-matters-skills-crisis-attached/ 9 ECONOMICS ASSESSMENT ~ 25%of Spend Situation • Retiring specialists leading to skill gaps • Tools under-utilization • Higher probability of outage or degradation • Inadvertent redundant purchases • Lack of awareness of upgrades and specialty engine exploitation
  10. 10. Software Costs Mainframe Economics Concern 10 ECONOMICS ASSESSMENT ~ 40%of Mainframe Spend Situation • Redundant Capabilities • Higher vendor management burden • Higher maintenance cost • Different skills to maintain for different tools • Need to modernize – same toolset across mainframe and rest of your datacenter Vendor 1 • Xxxxx • Xxxxx • xxxxx Vendor 2 • Xxxxx • Xxxxx • xxxxx Vendor 3 • Xxxxx • Xxxxx • xxxxx
  11. 11. Here are the Best Practices to Optimize the Platform • Optimize capacity • Leverage Specialty Engines and product health-checks • Discover all your software ECONOMICS ASSESSMENT
  12. 12. See How CA Mainframe Resource Intelligence Works and Delivers Economics Assessments
  13. 13. CA Mainframe Resource Intelligence Capabilities 13 Scan Upload all your mainframe operational data in one spot to get a handle on current performance. Assess Leverage CA’s automation, AI, machine learning and 30+ years best practices expertise to analyze and understand possible savings and improvements. Report Easy to use reports are generated in 2 weeks, not months. Gain actionable recommendations to guide next steps.
  14. 14. CA Mainframe Resource Intelligence Portal Easy navigation to get started, obtain assessments and reports 14
  15. 15. Scan All Your Data in One Easy Step Goodbye to • CSV files • Emails • Questionnaires 15
  16. 16. Discover and Assess What You Have Hardware Configuration Base Assessment Physical Mainframe – Manufacturer, user- assigned hardware name, family (type of processor), model, physical memory (central storage), MIPs, and MSUs Processors – Serial number, type (such as zIIP and zAAP), and WLM Configuration – LPARs defined within a SYSPLEX and processor allocation per LPAR Peripherals – Type of peripheral, such as tape, DASD, TAPE, or CTC, and the number of each Other Attributes – Attributes such as HyperPav enablement and GDPS 16
  17. 17. Discover and Assess What You Have Software Base Assessment Operating Systems – SYSPLEX, LPARs, operating system version, and JES (job entry subsystem) Subsystems – SYSPLEX, LPAR, vendor, subsystem, release, and instance Registered Products – LPAR, vendor, product, feature, version, and software ID Vendor Software – Vendor and products 17
  18. 18. Health Check Assessment Exception Information – IBM Health Checks consolidated by LPAR and categorized by owner, type of check, and severity level (high, medium, and low) 18
  19. 19. Capacity Optimization Report CPC Overview – Min/Max MSU, R4HA, C4HA, Capped% Findings – Machine, Analyst, and AI (future) Generated Recommendations – Machine, Analyst, and AI (future) Generated Examples – potential MLC reduction, shifting workloads, Pricing Models, etc. 19 REPORT REVEALS 8-10% Expected 8-10% baseline savings against total MLC $200K Up to $200K savings per LPAR
  20. 20. Specialty Engines Report zIIP Overview – R4HA%, Min/Max zIIP, zIIP on CP Findings – Machine, Analyst, and AI (future) Generated Recommendations – Machine, Analyst, and AI (future) Generated Examples – offload efficiency, tuning, configuration, etc. 20 REPORT REVEALS 55% - 65% expected offload of workload to specialty processors saving MLC
  21. 21. Software Discovery Report Vendor Consolidation – “As Is” and “To Be” states by vendor/product Findings – Machine, Analyst, and AI (future) Generated Recommendations – Machine, Analyst, and AI (future) Generated Examples – potential software savings, eliminate software redundancy, identify software usage 21 REPORT REVEALS 24% Discover 24% approximate tool reduction due to removal of redundancy
  22. 22. CA’s Dynamic Capacity forecasting is a win –win for us. It provides automated and predictable capacity management so we can optimize system resources to the most critical business needs CHALLENGE: Needed to monitor thresholds that were relevant for pricing predictions in real-time. Take timely and appropriate actions against unplanned peaks in usage and costs to maximize ROI. German Insurance Company German insurance giant needed to reduce cost in their data center 22 10% software cost reduction Across mainframe operations Reduced manpower involved in capacity management Prioritized MSU capacity based on workload priorities across LPAR The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous. “
  23. 23. CHALLENGE: Reduce Mainframe HW and SW licensing cost while maintaining “5 9’s of availability. Key delivery applications run on CA’s highly resilient CA Datacom database technologies. DHL Is a global logistics company specializing in packaging, courier and express delivery with a network of operations spanning 220 countries and territories. 23 CA provides mobile-to- mainframe visibility and machine learning intelligence for a better customer experience 55% of workloads offloaded to specialty engines Higher throughput at reduced licensing fees Lower TCO The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous. “
  24. 24. CA’s approach is way ahead of other intelligence engines which aren’t real time CHALLENGE: Multiple tools, multiple vendors in their mainframe environment built over years resulted in redundant capabilities, costly shelf-ware costs as well as unnecessary licenses & maintenance costs Leading Insurance Company An insurance giant serving 90% of the Fortune Global 500 needed to leverage their valuable mainframe data and support a variety of new business initiatives 24 45% product reduction 14% vendor reduction 50% Software License cost savings Conversion duration: 4 months from start to production The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous. “
  25. 25. • Tell your CA Account Director • Tell us about your concerns and overall business challenge CONTACT US! • Provide a list of your vendors, tools, & current capacity status • Jointly determine the type of review for maximum near term benefit PARTNERING FOR SUCCESS • Get your saving assessment from CA • Determine next steps for implementation • Feel confident that CA’s there for you today and tomorrow CELEBRATE

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