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
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. 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. 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. 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. 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. 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
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. 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. 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. See How CA
Mainframe Resource
Intelligence Works and
Delivers Economics
Assessments
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.
15. Scan All Your
Data in One
Easy Step
Goodbye to
• CSV files
• Emails
• Questionnaires
15
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. 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
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. 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. 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. 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. 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. 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. • 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
Hinweis der Redaktion
Find the low-hanging opportunities first and then tackle the more complex transformations
Identify and eliminate redundant tools and shelf-ware
Establish culture of proactive planning – avoid last minute surprises that lead to capacity buys
Look for ways to increase productivity – by tapping new capabilities, automation
Introduce modern tooling to avoid reduce reliance on specialized skills
Find the low-hanging opportunities first and then tackle the more complex transformations
Identify and eliminate redundant tools and shelf-ware
Establish culture of proactive planning – avoid last minute surprises that lead to capacity buys
Look for ways to increase productivity – by tapping new capabilities, automation
Introduce modern tooling to avoid reduce reliance on specialized skills
CIO challenge on MF – free resources now to make mainframe a viable and sustaining platform for digital transformation today and for the future. These questions apply to mainframe and any platform
What resources can I free up to fund new growth?
How secure and compliant is our org. data?
What is the state of systems, apps – can we guarantee 99.99 availability and a superior experience?
How can we build apps as fast as those for cloud services?
How do we build trust in every interaction?
In medicine, the doctor patient gets a diagnosis and then goes for a deeper exam like an MRI scan. MRI report is based on years of best practices, clinical experience to come up with a deeper recommendation and then a prescription for better health outcomes. The same process can be applied to your MF environment.
Under the covers – we have built this as an on-prem or cloud assessment solution. Our clients can pick their MRI scan from a service catalog. All the data collected is in a data lake so over time, we can perform pt in time scans and develop benchmarks or tracking reports of performance.
CA’s clients have succeeded on their optimization and transformation journey by taking a best practices approach to deliver 6 outcomes. We call this an MRI
Customers who adopt these 15 best practices succeed with the Mainframe optimization to transformation journey – everything from dynamic workload mgmt. to Machine learning to modern agile practices.
What if you had a MRI based on best practices for your IT environment
The answer to the challenges laid out.. What if Head of MF had an automated concierge to guide him to the answers.. That’s what this assessment solution is
The tool that aids and ultimately crunches the business case with intelligence of which initiatives to prioritize
Offers automation - let AI, data, do heavy lifting instead of ppl… we can codify best practices into SW
Time to value – today the process takes weeks.. Instead the automation drives faster time to value. Get a recommendation 2-3 weeks not months
Find the low-hanging opportunities first and then tackle the more complex transformations
Identify and eliminate redundant tools and shelf-ware
Establish culture of proactive planning – avoid last minute surprises that lead to capacity buys
Look for ways to increase productivity – by tapping new capabilities, automation
Introduce modern tooling to avoid reduce reliance on specialized skills
Find the low-hanging opportunities first and then tackle the more complex transformations
Identify and eliminate redundant tools and shelf-ware
Establish culture of proactive planning – avoid last minute surprises that lead to capacity buys
Look for ways to increase productivity – by tapping new capabilities, automation
Introduce modern tooling to avoid reduce reliance on specialized skills
The answer to the challenges laid out.. What if Head of MF had an automated concierge to guide him to the answers.. That’s what this assessment solution is
The tool that aids and ultimately crunches the business case with intelligence of which initiatives to prioritize
Offers automation - let AI, data, do heavy lifting instead of ppl… we can codify best practices into SW
Time to value – today the process takes weeks.. Instead the automation drives faster time to value. Get a recommendation 2-3 weeks not months
The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous.
Protect data privacy
Zions Bank – CAW Presentation
https://www.youtube.com/watch?v=mr9wpgjICGY&list=PLO7SodxCJyn6OXtHI1kPoLkKmfDKIxDdt&index=81
CA Data Content Discovery Customer Use Case
CA Data Content Discovery scans the mainframe data infrastructure to identify the location of sensitive data, and classifies the data based on sensitivity level so the appropriate business decisions can be made to secure, encrypt, archive or delete the data identified.
One of the first customers for CA DCD was a large Western US National Bank who originally purchased the solution to discover Payment Card Industry data (PCI DSS) on their mainframe – which as a bank has a lot of. They needed to meet audit and compliance requirements quickly, protect their customers highly sensitive data, and keep their operations running smoothly.
In their first 100 scans, the customer surprisingly found that over 5% of their scanned datasets contained Payment Card Industry data and Personally Identifiable Information in places not expected. And once the bank knew the location of the PCI and PII data in their mainframe infrastructure, they were able to take the second action and secure it appropriately.
With the initial success of the solution, the bank has since found a variety of other search uses for the tool:
The customer is executing DCD in development and scanning production data to have proactive insights sooner
They are currently running scans against user datasets
The customer is leveraging customer classifiers with scan info that is customized to their business to find PCI/PII data
The customer is automating the scans by setting up jobs in batch and scheduling them, to combine effective security and business agility
Increased risk assessment through automated non-manual efforts
Improved business agility by automating and scheduling scans
Complete flexibility by customizing classifiers
Additional Data Content Discovery Customers:
EOY FY17 – 34 customers licensed, 1 installed
Additional DCD customers (yet to install)
Broadridge
Morgan Stanley
Department of Justice
Department of Education
Metlife
Licensed EMEA DCD customers (yet to install)
AXA
DWP Bank
Lufthansa Airplus & Technik
Raiffeisen e-force GmbH
The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous.
Protect data privacy
Zions Bank – CAW Presentation
https://www.youtube.com/watch?v=mr9wpgjICGY&list=PLO7SodxCJyn6OXtHI1kPoLkKmfDKIxDdt&index=81
CA Data Content Discovery Customer Use Case
CA Data Content Discovery scans the mainframe data infrastructure to identify the location of sensitive data, and classifies the data based on sensitivity level so the appropriate business decisions can be made to secure, encrypt, archive or delete the data identified.
One of the first customers for CA DCD was a large Western US National Bank who originally purchased the solution to discover Payment Card Industry data (PCI DSS) on their mainframe – which as a bank has a lot of. They needed to meet audit and compliance requirements quickly, protect their customers highly sensitive data, and keep their operations running smoothly.
In their first 100 scans, the customer surprisingly found that over 5% of their scanned datasets contained Payment Card Industry data and Personally Identifiable Information in places not expected. And once the bank knew the location of the PCI and PII data in their mainframe infrastructure, they were able to take the second action and secure it appropriately.
With the initial success of the solution, the bank has since found a variety of other search uses for the tool:
The customer is executing DCD in development and scanning production data to have proactive insights sooner
They are currently running scans against user datasets
The customer is leveraging customer classifiers with scan info that is customized to their business to find PCI/PII data
The customer is automating the scans by setting up jobs in batch and scheduling them, to combine effective security and business agility
Increased risk assessment through automated non-manual efforts
Improved business agility by automating and scheduling scans
Complete flexibility by customizing classifiers
Additional Data Content Discovery Customers:
EOY FY17 – 34 customers licensed, 1 installed
Additional DCD customers (yet to install)
Broadridge
Morgan Stanley
Department of Justice
Department of Education
Metlife
Licensed EMEA DCD customers (yet to install)
AXA
DWP Bank
Lufthansa Airplus & Technik
Raiffeisen e-force GmbH
The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous.
Protect data privacy
Zions Bank – CAW Presentation
https://www.youtube.com/watch?v=mr9wpgjICGY&list=PLO7SodxCJyn6OXtHI1kPoLkKmfDKIxDdt&index=81
CA Data Content Discovery Customer Use Case
CA Data Content Discovery scans the mainframe data infrastructure to identify the location of sensitive data, and classifies the data based on sensitivity level so the appropriate business decisions can be made to secure, encrypt, archive or delete the data identified.
One of the first customers for CA DCD was a large Western US National Bank who originally purchased the solution to discover Payment Card Industry data (PCI DSS) on their mainframe – which as a bank has a lot of. They needed to meet audit and compliance requirements quickly, protect their customers highly sensitive data, and keep their operations running smoothly.
In their first 100 scans, the customer surprisingly found that over 5% of their scanned datasets contained Payment Card Industry data and Personally Identifiable Information in places not expected. And once the bank knew the location of the PCI and PII data in their mainframe infrastructure, they were able to take the second action and secure it appropriately.
With the initial success of the solution, the bank has since found a variety of other search uses for the tool:
The customer is executing DCD in development and scanning production data to have proactive insights sooner
They are currently running scans against user datasets
The customer is leveraging customer classifiers with scan info that is customized to their business to find PCI/PII data
The customer is automating the scans by setting up jobs in batch and scheduling them, to combine effective security and business agility
Increased risk assessment through automated non-manual efforts
Improved business agility by automating and scheduling scans
Complete flexibility by customizing classifiers
Additional Data Content Discovery Customers:
EOY FY17 – 34 customers licensed, 1 installed
Additional DCD customers (yet to install)
Broadridge
Morgan Stanley
Department of Justice
Department of Education
Metlife
Licensed EMEA DCD customers (yet to install)
AXA
DWP Bank
Lufthansa Airplus & Technik
Raiffeisen e-force GmbH