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Mainframe MRI from CA Technologies

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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. This is the only offering in the market that combines economic consulting services with proprietary utilities and automation technologies. View this SlideShare to understand the solution – how services, best practices and mainframe expertise of 40+ years from CA comes together to solve the CIO and CFO’s biggest challenge.

Call your account director or mainframe specialist.: https://www.ca.com/us/contact/mainframe-economic-consultant.html

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Mainframe MRI from CA Technologies

  1. 1. Mainframe Resource Intelligence by CA Technologies
  2. 2. CIO desired outcomes: Cost Imperative: Must Save Now to Invest in the Modernization Journey 2 What are the barriers to building a modern software factory including Mainframe to build and deliver mission critical services at the same speed as my cloud services? What is the state of my systems and skills to provide 99.999 availability and redundancy? How can I build Digital Trust to enable us to be a Digital Enterprise? How secure is our data and how compliant are we with GDPR and other regulations? What resources can I free up to self-fund digital initiatives? Economics
  3. 3. 3 Economics PROCESS MRI AGILITY/SPEED TOOLCHAIN ECONOMICS MRI CAPACITY COST SOFTWARE COSTS LABOR COSTS SYSTEMS MRI SLA’S SKILLS AUTOMATION Start with Mainframe Resource Intelligence (MRI) to assess your current state in the modern software factory Economics SECURITY MRI PRIVACY ACCESS
  4. 4. 4 Apply Best Practices with Mainframe Resource Intelligence Optimization to Modernization AI DRIVEN SELF DRIVING DATACENTER AGILE DEVOPS TOOLCHAIN ECONOMICS MRI DATA & USER CENTRIC SECURITY OPTIMIZE PLATFORM PROCESS MRI SECURITY MRISYSTEMS MRI • Dynamically manage capacity • Leverage Specialty Engine and Java • Software Standardization • Modern UX and Visual analytics • Leverage experts to train AI/ML algorithms • Augment people with machine Intelligence • Automatic remediation to create self driving datacenter • Adopt open modern tools familiar to next gen developers • Automate to shift “ops” left to enable continuous delivery • Provide everything as a service • Discover and protect sensitive data • Implement multi- factor authentication • Reduce risk by Trusted user management
  5. 5. An Economic MRI is the first step Seems Simple but it’s not.. 5 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 MRI
  6. 6. Mainframe Economics Challenge Predicting Capacity 6 ~ 35% of Mainframe Spend Situation • Capacity spikes • Missed SLAs • Over-provisioning • Modest but periodic MLC price increases add up $$$MMs ECONOMICS MRI
  7. 7. Mainframe Economics Concern Skills ~ 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 Source:https://diginomica.com/2017/07/20/mainframe-still-matters-skills-crisis-attached/ 7 ECONOMICS MRI
  8. 8. Vendor 1 • Xxxxx • Xxxxx • xxxxx Vendor 2 • Xxxxx • Xxxxx • xxxxx Vendor 3 • Xxxxx • Xxxxx • xxxxx Mainframe Economics Concern – Tool Proliferation 8 ~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 ECONOMICS MRI
  9. 9. 9 Solution? Here are the Best Practices to Optimize the platform o Optimize capacity o Leverage Specialty Engines and Java o Pursue software standardization ECONOMICS MRI
  10. 10. Don’t panic Let’s delight your CFO With an economics MRI that exposes hidden opportunities to save and invest wisely
  11. 11. 3 Ways to Optimize and Reduce Costs 11 Deploy tools to the fullest with feature & zIIP exploitation, upgrade analysis, best practices and configuration consultation Perform capping analysis and select the right workload candidates for tuning, shifting and load balancing to save MLC Discover redundant capabilities and systematically analyze consolidation and modernization to reduce license and skills costs Optimize Capacity Leverage specialty processors and Java Standardize Software ECONOMICS MRI
  12. 12. 12 A Economics MRI from CA based on Across 500+ Engagements 12 • 8-10% baseline savings against total MLC • Up to $200K savings per LPAR • 55% - 65% offload of workload to specialty processors saves MLC • 24% tool reduction due to removal of redundancy • Same development tools for distributed and Mainframe • Lower FTE costs due to common skills Optimize Capacity Standardize Software Leverage Specialty Engines & Java ECONOMICS MRI
  13. 13. Economics MRI Engagement Model Services, Best Practices & Technology Combined for Predictable Delivery 13 Discovery and Data Collection Cost analytics using proprietary utilities and data automation CA delivers findings Client decision Portfolio data DNA Scenarios of potential cost savings implement findings SMF 70, 72 X-Ray Ease vs. impact analysis Use of CA services & onversion utilities Product inventory In-built health-checks and metrics Estimation of customer effort Adopt new capabilities to realize business case goals. Business case objectives ANALYZE ASSESS RECOMMEND FOLLOW 2 weeks! Fast recommendation powered by analytics and automation
  14. 14. Economics MRI Engagement Model Automation and utilities minimizes your effort 14 • Tailor your own engagement: Pick one one, 2 or all three reviews • Least disruption to your team – CA services professionals guide the way. ANALYZE CA tools with Customer provided data Customer Level of Effort Optimize capacity “X-Ray” or Dynamic Capacity analyzer runs a 90-Day extract of SMF 70, 72 Low to moderate Leverage specialty engines Best practices and product health-checks with metrics & usage data Moderate Standardize software DNA automated discovery of customer installed portfolio Low APPROACH
  15. 15. Your peers are doing this..
  16. 16. 16 Automated Capacity Mgmt.: Depicts all LPAR usage, but most expensive LPAR had the highest usage Optimize Capacity
  17. 17. 17 Optimize Capacity: Identify peak usage Automated Capacity Mgmt.: Easily view peak real-time rolling four-hour (R4HA), Caps and MLC
  18. 18. 18 Optimize Capacity – Pricing scenarios Pricing Optimization View: Show scenarios of Advanced Workload License Chart usage vs. Country Multiplex Pricing
  19. 19. Optimize Capacity Recommendations include  Peak usage vs. Peak cost LPARs  Optimal Pricing model (e.g. CMP)  Time shifting – moving batches to night  White-space usage potential  Risk scenarios ECONOMICS MRI
  20. 20. CA’s Dynamic Capacity Intelligence 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 20 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. “
  21. 21. 21 Leverage specialty engines and Linux  Assessment of products and capabilities to leverage specialty processors  Cost avoidance or MIPs savings estimations  Product best practices  Configuration  Tuning  Installation and upgrade guidance
  22. 22. 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. 22 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