cost effective it strategies to lead in a digital world - ibm€¦ · cost effective it strategies...

Cost Effective IT Strategies to Lead in a Digital World

Steve MillsSenior Vice President and Group ExecutiveIBM Software and Systems

October 7, 2013

© 2013 IBM Corporation

Smarter Planet Solutions Increasing Demands on IT

AT&T transfers about 30 Petabytes of data through its network daily

150 Exabytes global size of “Big Data” in Healthcare, growing between 1.2 and 2.4 EX / year

Facebook processes 500+ Terabytes of data daily

By 2016, annual Internet traffic will reach 1.3 Zettabytes

$155B Worldwide sensor market in 2011, forecasted to grow to $240B in 2016

450B Business transactions / day over the Internet by 2020

118B E-mails sent daily from a total of 3.4B e-mail accounts; volume growing to 168B in 2015

6B Mobile phones worldwide


Five Mega-trends are Accelerating the New Era of IT

The rapid adoption of cloud computing

Business advantages created through data and analytics

Increased focus on security

Consolidation and integration of IT infrastructure

Emergence of social and mobile


Shifting Trends in the IT Environment

From monolithic applications to dynamic servicesFrom static infrastructure to cloud services

From programmed systems to learning systems

From structured data at rest to unstructured data in motionFrom stable well-defined workloads to unpredictable workloads

From standard devices to a variety of devicesFrom proprietary standards to open innovation


The Evolution of Today’s Data Center is Based on Four Critical Actions and Enabling Capabilities

Better Business Economics

Accelerated Business Velocity

Physical Systems

…Simplified, Automated, ProactiveComplex, Skill Intensive, Reactive Monitoring…

Federated Processes


Workload Requirements Should Determine Which of the Available Deployment Options is Used to Maximize Business Success

Functional and Non-Functional Workload Attributes…

Deployment Speed and Agility Elasticity and Scaling Security and Compliance Reliability, Availability & Service Level Transactional Integrity Operational Cost and Efficiency Data Location Regulatory Items Resource availability Co-Location requirements Storage Access Operations Costs

Public

SaaS

Public or Private

PaaS

Public or Private

IaaS

Private

On Premise


IT Operating CostsThe Cost of Labor Outpaces New Investment

Source: IDC, 2013

Power and cooling costs

63%8%

29%

1996

$100 B

43%11%

46%

2001

$130 B

33%16%

51%

2006

$175 B20%12%

68%

2013

$249 B est.

New Server spending

Server management and admin costs

Worldwide Spending on Servers, Power, Cooling & Management

Administration


Increased Demands on IT Create Data Center Sprawl

Data centers have doubled their energy use in the past 5 years 18% increase in

data center energy costs projected

32.6 million servers worldwide 85% idle computer capacity 15% of servers run 24/7 without

being actively used on a daily basis

Internet connected devices growing 42% per year to 1 Trillion devices by 2017

Between 2000 and 2010 servers grew 6x storage grew 69x

Virtual machines growing 42% per year

Growing Cumulative Value of

Software Investments


Sprawl Drives Unsustainable Costs

Cost to Manage Growth of Inventory Consumes

IT Budget


IT Must Break Through Budget and Resource Barriers

Getting Up and Running 2-3 months to specify and procure 2-3 months to integrate, configure

and deploy

Development Operations 3-6 months to go from

development to production

Ongoing Effort1-3 months to troubleshoot and tuneOngoing effort and downtime to maintain, scale and upgrade

IT RealityBusiness Goals

Driving business innovation Make new markets Respond to competitive threats Enhance the customer

experience

Grow top and bottom line by:

Typical Results 23% of new IT projects (worldwide) deploy late 55% experience application downtime for major

infrastructure upgrades once deployed

Source: A commissioned study conducted by Forrester Consulting on behalf of IBM


Only 1 in 5 Can Allocate More than Half Their IT Budget to Innovation

More Effective Use of Technology86% first and fast technology adoption58% move virtual machines to meet desired outcomes93% use storage virtualization87% use a storage service catalog (tiered storage)

Less Effective Use of Technology43% first and fast technology adoption1% move virtual machines to meet desired outcomes

21% use storage virtualization3% use a storage service catalog (tiered storage)

Most Efficient IT OrganizationsLess Efficient IT Organizations

Maintaining existing infrastructure

65%

New projects

35%Maintaining existing infrastructure

47%

New projects

53%


How Do You Quantify IT Economics?

Workload Identified for

Analysis

Deployment Choices

Key Steps in Analysis

1. Establish Equivalent Configurations Needed to deliver workload

2. Compare Total Cost of Ownership TCO looks at different dimensions of cost

Deploy on other platformsDo Nothing Optimize current

environment

Application XYZ(Production, Development, QA)

Frontends

Databases

Other Components


Understanding “Total Cost of Ownership (TCO)”Four Dimensions of Cost Should Be Considered

Cost components

Environments

Time Factors

Non-Functional Requirements / Qualities of Service


Many Cost Components80:20 rule helps to achieve reasonable results in a short time

Hardware

Software

People

Network

Storage

Facilities

Components

Space, electricity, air cooling, infrastructure including UPS and generators, alternate site(s), bandwidth

ECKD, FBA, SAN, compressed, primary, secondary Disk (multiple vendors), tape, Virtual, SSD

Adapters, switches, routers, hubs Charges, allocated or apportioned, understood or clueless

FTE rate, in house versus contract

List versus Discounted Fully configured vs. basic, Production vs. Disaster Recovery Refresh / upgrade, Solution Edition…

IBM and ISV, OTC and annual maintenance (S&S) MLC, PVU, RVU, ELA, core, system


Environments Multiply Components

Production/Online Batch/Failover

Quality Assurance

Disaster RecoveryTestDevelopment

Hardware

Software

People

Network

Storage

Facilities

ComponentsEnvironments


Time Factors Drive Growth and Cost

Migration time and effort

Business organic growth and/or planned business changes affect capacity requirements

- e.g. Change of access channel or adding a new Internet accessible feature can double or triple a components workload

- Link a business metric (e.g. active customer accounts) to workload (e.g. daily transactions) and then use business inputs to drive the TCO case

Other periodic changes - hardware refresh or software remediation


Availability … Reliability …Security … Scalability …

Qualities of Service, Non-Functional Requirements


Quality Assurance


Hardware

Software

People

Network

Storage

Facilities


Time

Non-Functional Requirements Can Drive Additional Resource Requirements


Total Cost of Ownership - Understanding the Complete Story


Quality Assurance


Hardware

Software

People

Network

Storage

Facilities


Time“Qualities of Service” such as Availability,

Reliability, Security and Scalability


Scale-up AND Scale-out

Both valid Unit of work dynamics must be understood Data access patterns must be understood Sharing and isolation patterns must be understood

Scale out Scale out

Scale up

Scale down


Larger Servers with More Resources Make More Effective Consolidation Platforms

Most workloads experience variance in demand

When you consolidate workloads with variance on a virtualized server, the variance of the sum is less (statistical multiplexing)

The more workloads you can consolidate, the smaller is the variance of the sum

Consequently, bigger servers with capacity to run more workloads can be driven to higher average utilization levels without violating service level agreements, thereby reducing the cost per workload


Observations

There is a benefit to large scale servers- The headroom required to accommodate variability goes up only

by sqrt(n) when n workloads are pooled

- The larger the shared processor pool is, the more statistical benefit you get

- Large scale virtualization platforms are able to consolidate large numbers of virtual machines because of this

Servers with capacity to run more workloads can be driven to higher average utilization levels without violating service level agreements


A Single Workload Requires a Machine Capacity of 6x the Average Demand

Server Capacity Required

60/sec

Average Demand

m=10/sec

Assumes coefficient of variation = 2.5, required to meet 97.7% SLA

Server utilization = 17%

6x Peak To Average


Consolidation of 4 Workloads Requires Server Capacity of 3.5x Average Demand

Server Capacity Required 140/sec

Average Demand

4*m=40/sec

3.5x Peak To Average





Server Capacity Required 360/secAverage Demand

16*m=160/sec






Server Capacity Required 2,045/secAverage Demand 144*m=

1440/sec





Benefit of Statistical MultiplexingA single virtualized server with a large pool of shared processors can run more

workloads than several smaller servers with the same total number of processors

3xmore workloads 4.4x

more workloads

32 workloads1 per server



32 servers with 8 cores256 cores total1024 threads

4 servers 64 cores256 cores total1024 threads

1 server with 256 cores256 cores total1024 threads

Each workload is the largest that can fit on a

single 8 core server


zEnterprise EC12 Efficiency at ScaleWorld Record SAP Transaction Banking

2 x 22 DB cores2 x 7CF cores

DB2 for z/OSCompetitor DB on Intel

128 DB cores

Database

8x 3850 x5 with 16 cores (dual active clusters) zEC12 2-way data sharing Sysplex

DatabaseSAP

ApplicationsSAP

Applications

Database Unit Cost (5yr TCA)$ 0.30 / Postings per Hour

Database Unit Cost (5yr TCA)$ 0.15 / Postings per Hour

World record at half

the cost

Postings per Hour 59.1 M# of Accounts 150 MDB2 Solution Ed (Hdw+Sft) $ 7.49 MCapacity Backup $ 1.24 MTotal Cost $ 8.73 M

Postings per Hour 42.0 M# of Accounts 90 MHardware $ 0.63 MSoftware $ 11.98 MTotal Cost $ 12.61 M


zEnterprise EC12 Efficiency at ScaleConsolidated Oracle Database Workloads on zLinux

Three Database Workloads 3 Oracle RAC clusters 4 nodes per cluster Each node is a zLinux guest zEC12 with 27 IFLs*

$ 5.7 M (3yr. TCA)

Which platform provides the lowest TCA over 3 years?

Oracle DB Workload

3 Oracle RAC clusters 4 server nodes per cluster 12 total 16 core servers

(192 cores)

$ 13.2 M (3yr. TCA)

* Estimated values as of August 2012

TCA includes hardware, software, maintenance, support and subscription. Workload Equivalence derived from a proof-of-concept study conducted at a large Cooperative Bank.

Half the cost


Better Labor Productivity - U.S. Insurance CompanyLarge Systems with Centralized Management

$ 0.12 per claim

$ 0.79 per claim

Identical function Different platforms

Mainframe support staff has6.6x better

productivity

IBM System z CICS/DB2

MIPs used for commercial claims processing production / dev / test 945

Claims per year: 4,056,000

Competitor UNIX Servers + ISV

Claims per year: 327,652

Development/Test Servers 2 Large Enterprise-class Intel

Production Servers 2 Large Enterprise-class Intel


Data Duplication Wastes Storage and Processing Capacity

Systems of record

Local solutions for OLTP

DB

Appl

DB

Appl

DB

Appl

DB

Appl

DB

Appl

DB

Appl

IMSDB2

Oracle

A Large European Bank Proliferation of local solutions

- Applications + Databases 1,000 LPARs on 750 cores with

14,000 software titles 120 database images Heavy data movement

- Bulk data transfers (ETL) to local DB

ETL consumed 28% of distributed cores and 16% of MIPS

A Large Asian Bank ETL consumed 8% of total distributed core

and 18% of total MIPS


Optimize Server Utilization

Reduce Server Sprawl

Consolidate Servers Server Virtualization Reduce # of Data Centers Asset Management

Manage Workloads

Workload Optimized Systems …. Best Fit

Automate Processes

Automation Provisioning Workload Scheduling

Optimize Service Delivery

Integrated Service Mgmt. (ISM) Self-provisioned Cloud Services


Storage Efficiency and Best Practices

Stop Storing So Much

Data Compression Data Deduplication

Store More With What’s On the Floor

Storage Virtualization Thin Provisioning Consolidated Storage Management

Move Data to the Right Place

Automated Tiering Automated Data Migration Policy-based Management


Eliminate Redundant Software and Data

Applications Identify and Eliminate Redundant Systems & Applications Reuse of Common Services - SOA

Largest Cost Savings but Slower to Achieve

Data

Reduce Database Size - Data Compression Reduce Multiple Copies - Data De-duplication Information Integration - Master Data Management Data Governance - Archiving


Improve Service Delivery

Integrated Service Management (ISM) Visibility, Control, Automation

Transform to Private Cloud Delivery Model Self-service Automated Provisioning

and Workload Scheduling Elastic Capability to Expand Pay-as-you-go

Integrate with Public Clouds

Improves Labor Productivity and Flexibility

Integrated Service Management

Visibility AutomationControl


Workload Requirements Should Determine Which of the Available Deployment Options is Used to Maximize Business Success

Functional and Non-Functional Workload Attributes…

Deployment Speed and Agility Elasticity and Scaling Security and Compliance Reliability, Availability & Service Level Transactional Integrity Operational Cost and Efficiency Data Location Regulatory Items Resource availability Co-Location requirements Storage Access Operations Costs

Public

SaaS

Public or Private

PaaS

Public or Private

IaaS

Private

On Premise


On-Premise or Public Cloud: The Choice is Yours

On-Premise Public Cloud

Greater control More security Higher performance Deeper compliance Customizable

May be higher cost On-site maintenance Capacity ceiling

Simplicity and efficiency May be lower cost Reduced time No maintenance Pay-as-you-go model

Lack of control Scaling issues Lack of investment Perceived weaker security

Dis

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Public Cloud


Significant variation in demand for IT resources

- Exploit the differential and reduce operating costs by only matching supply to the level of demand

- Metered billing can allow resources to scale up/down to meet demand

To realize this benefit- Peak/average demand ratio must be greater than the cost ratio

of Public Cloud over On-Premise Hosting- Application must be able to scale horizontally- Existence of sufficient density of compute nodes to allow scaling

When Is Public Cloud Hosting Cost Effective


Calculating Comparative Costs CAPEX vs. OPEX Bulk of costs over the lifetime of an application are not related

to the purchase of physical infrastructure; therefore, Total Cost of Ownershipis more meaningful in comparing On-Premise versus Public Cloud costs

Tangible Assets- Server Hardware- Network Hardware- Storage Hardware

Intangible Assets- Hardware Maintenance Contracts- Software License Contracts- Software Support Contracts

Utilities

Real Estate

Human Labor- Data Center Operators / Administrators- Network and Storage Administrators- Systems Administrators- Software Developers / Architects- Help Desk Operatives- General & Administrative- Managerial

Downtime / Outages

Auditing / Compliance


Additional Intangible Costs Need to be Considered

Transformation costs in moving Application

Reliability and availability

Data Center and Operations quality

Extensibility

Security and Privacy

Scalability

Capacity


Cloud Economics

Cloud services are complex and varied and will continue to evolve

Cost savings from the use of Public Cloud services is highly dependent upon the type of application / workload, its suitability to Cloud, and the level(s) of efficiency and optimization of on-premise IT resources and operations

Evaluation of the costs associated with each application is required to gain a true understanding of the comparative costs

Transformation costs associated with migrating an application from on-premise to Cloud must be factored in the cost equation

The decision on the use of Public Cloud often comes down to cost versus control


Cost Effective IT

Do not confuse price with cost

Budgeting and charge back techniques can cause false economics

Technology is a tool, not a religion …… insist on fact based analysis

TCO cannot be overlooked but neither can agility and effectiveness

Elimination is the clearest path to saving money

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