A #Pink14 Presentation: Optimizing for the #SDDC

Copyright © 2014 TeamQuest Corporation. All Rights Reserved.

TeamQuest and the TeamQuest logo are registered trademarks in the US, EU and elsewhere. All other trademarks and service marks are the property of their respective owners.

Optimizing theSoftware Defined Data

CenterContinuously operate at the intersection of Business Performance and IT

Efficiency

David Wagner – TeamQuest Advocate

BOOTH #401


• Today’s technology situation: challenges, goals & benefits

– Virtual Everything– Dynamism– Analytics

• Continuous IT Financial Optimization– Challenges and risks of inaction– Desired state and results– Approach: Aligning Business and IT Analytics– Examples/Results

Agenda


• Virtualization of Servers – maturing

• Virtualization of Storage – ramping rapidly

• Virtualization of Desktops – coming on strong

• Virtualization of Networks – growing

• Cloud(s) growing in importance…

• Increasingly called the Software Defined Data Center (SDDC)

Today’s situation

Copyright © 2014 TeamQuest Corporation. All Rights Reserved.© 2013 Forrester Research, Inc. Reproduction Prohibited 4

Source: Forrsights Hardware Survey, Q3 2009, 2010, 2011, 2012

Virtualization and Cloud

“Which of the following initiatives are likely to be your firm’s/organization’s top hardware/IT infrastructure priorities over the next 12 months?” (Percentage of respondents who answered “critical” or “high” priority)

Use cloud infrastructure-as-a-service (IaaS) at a service provider

Build an internal private cloud operated by IT (not a service provider)

Automate the management of virtualized servers to gain flexibility and resiliency

Maintain or implement broad use of server virtualization as the standard server deployment model

Consolidate IT infrastructure via server consolidation, data center consolidation, or server virtualization

18%

23%

61%

77%

79%

28%

29%

60%

80%

80%

31%

36%

63%

79%

81%

35%

46%

63%

79%

78%

2012 (N=1,036)2011 (N=1,240)2010* (N=1,037)2009* (N=1,020)

Base: North American and European IT decision makers at enterprise firms with 1,000 or more employees

*Question wording in 2009 and 2010 referred to IaaS as “virtual-server-as-a-service”


Dynamism increasing

Public cloud IaaS

Outsourced service provider

Hosted private cloud IaaS

Traditional hosting offering

On a dynamic private cloud pool of virtual servers

On relatively static virtual servers

On physical servers not virtualized

3%

4%

7%

4%

27%

31%

23%

1%

3%

3%

5%

13%

32%

42%

Today (N=486) In four years (N=476)

“What percentage of your total x86 servers OS instances are in each of the following categories?”

Base: North American and European IT decision makers at enterprise firms using physical x86 servers

In four years, enterprise respondents expect to move about 20% of their

current physical servers into a private or public cloud

Source: Forrsights Hardware Survey, Q3 2012


The business values analytics…

Improve the use of data analytics to improve business decision making

19% 40%


• Inclusion of legacy or non-virtualized hardware resources?

• Interoperability of multiple vendors’ converged infrastructure systems?

• Management remains a mystery– Lack of real time data– Lack of global optimization strategies

Forrester content

Challenges and Obstacles


SDDC• Asset Management• Smart Devices• Virtualized Storage• Virtualized Servers• Virtualized NW• VDI• Etc….

Customer• Call Center Operations• POS Optimization• Demand Response• Campaign Management• Credit & Collections• Billing• Etc….

Busi

ness

Ser

vice

s/Ap

plic

ation

s

Cloud, Virtualization and SDDC -> Changing Demands on

Enterprise IT


Increasing Planning and Optimization Challenges

Busi

ness

Ser

vice

s/Ap

plic

ation

s

SDDC• Asset Management• Smart Devices• Virtualized Storage• Virtualized Servers• Virtualized NW• VDI• Etc….

Customer• Call Center Operations• POS Optimization• Demand Response• Campaign Management• Credit & Collections• Billing• Etc….


• SDDC management will place a premium on new management models

– Real time data collections– Embedded Analytics– Ability to span multiple data source domains

intelligently

• Analytics will have different goals – efficiency, cost, root cause analysis

• Goals include workload-centric optimization, global cost and energy efficiency, global availability … very tough challenges for traditional management vendors

Source: Forrester Research, September 2013

Management is WAY more

than monitoring


• Existing tools don’t accept it– ETL into acceptable format(s) is a lot of work, cost– Manual efforts cannot scale– Don’t adapt to dynamic, virtual everything realities

• IT has no expertise in business data– It isn’t easily presented or understood– We’ve never had the time to deal with it

• What can we really DO with it?– Where do we start?– What is the value?

“IT doesn’t analyze business data because…”


• Lack of understanding of relationship of dynamic technology to services

– Over and under provisioning – High Costs– Service risks– Market risks

• Too many disparate tools and processes– Expensive and in silos– Error prone impacting service delivery

• Vendor dependence and “lock in”– High costs– Reduced agility

Negative consequences of the current state

Copyright © 2014 TeamQuest Corporation. All Rights Reserved.© 2013 Forrester Research, Inc. Reproduction Prohibited 13

Base: 1048 IT hardware decision makers at enterprises in North America and Europe

Source: Forrsights Hardware Survey, Q3 2012

Desired State: Fully Leverage

Commoditization


• Continuously financially optimized IT environment

– Always know where and when performance problems will affect the bottom line

– Identify cost and performance inefficiencies in support of business processes and eliminate them

• Continuously optimized customer experience

– Understand when, where and why customer experiences fail

– Resolve, predict and prevent customer dissatisfaction issues

Desired state: Continuous Optimization


“What is the health of the

infrastructure?”

“How efficiently are we using the infrastructure? What does it

cost?”

“How many of those do we have? Need?

When?”

“Changes compared to the

last reporting period?”

“What’s the capacity

forecast? What should/will it

cost?”

“What were the exceptions? Do

we Care?”

“What’s the risk

assessment?”

Desired State: Answer the Questions!


• Significantly Reduce initial CapEx, and ongoing OpEx– Make, and keep making, more money!

• Optimize resources for systems of customer engagement

• Deploy and refresh new applications faster– E.g Retailers need to capture their share of mobile

commerce as it grows from $6 to $31b (2016)

• Respond faster to business spikes

• Prevent business impacting outages and slowdowns

Result: Continuous IT Optimization


Underlying IT

Infrastructure

Outage Manageme

nt

Customer Operations

Distribution Automation

Asset Manageme

nt

17

Services

Applications

Server/OS

Big Data Collection

Business Intelligence

Aligned Business and IT Intelligence

Enterprise IT Optimization

• Correlate business & IT performance

• Insight into how business process changes impact IT

• Understand and optimize IT costs by business unit/process and technology

• Insight into business performance across technology stack

Network

Storage

Methodology: Aligned Business and IT

Analytics


• Analyze - optimize decision making

• Integrate - with the business

• Automate – drive efficiency and repeatability

Automated, Aligned IT Analytics


• Federates existing data into purpose-designed optimization process

– Technology data (e.g. server, network, storage, etc.)

– Service data (catalog, metrics, tickets, etc.)– Financial data– Business data (Analytics, KPIs, plans, TXNs,

etc.)

• Automates analytics across all data sources

– Flexible and adaptive to dynamic SDDC environments

– Raw (commodity) data -> actionable information for IT

• Single-pane-of-glass IT Optimization

Federated IT Analytics


20

Automated, Predictive Analytics


• Continuous Optimization

– Pre-purchase validation– Re-purposing– Consolidation

• Fully Automated, low cost

• Integrate with Risk and Service Management

• Changed new VMwareClusters from every 6 weeks to:

– None for 18+ months…– Consolidated 1000’s of

VM’s (Saving $M)

Result: Automated Financial

Optimization


• Proactive Power Optimization

– Actual versus DC Limits– Power by Application/Service– Project Savings via

optimization efforts

• Data Sources– Server/Virtual Server

performance– Power Consumption from

DCIM power management– Service Catalog and CMDB– Asset Database

Result: IT Power Capacity Optimization


• Service Level RCA– Measured versus SLA– Span Servers, Virtual

Servers, Network, Storage, etc

• Data Sources– TeamQuest CMIS (VMware)– TeamQuest CMIS for

Storage– Application RT tools– Service Catalog and CMDB

Result: Automated Root Cause

Analytics


• Automatically Balance– Current and Future Costs– Performance– Capacity

• Data Sources– Server/Virtual Server

performance– Asset Costing (CapEx/OpEx)– Service Catalog and CMDB– Power Costing Database

Result: Financial Optimization Reports


• Continuous IT Optimization– Peak IT Performance– Ideal Resource Capacity– Optimized Resource Costs

• Automated IT Analytics– Predictive– Federated

• Aligned IT and Business Management– Performance– Capacity– Financial

Result: IT Optimized... Future Assured


“I know the performance

and costs of my infrastructure!”

“I know how efficient my IT environment is and can be and what it will cost”

“I know what we have, what we need, and when we need

it!”

“I know what has changed and why from

the last period!”

“I have a Capacity and

Financial Plan!”

“I understand the exceptions

and their importance!”

“I know what my risks to

performance are and will

be!”

TeamQuest: Insight Automated. Optimization

Achieved


• Fortune 200 Financial Services Provider– Saved $7Million in first year– Saved $15 Million in second year, significant power cost

reduction– Eliminated new server spend for 24 months, all new projects

continued

• Top 5 US Financial Services Provider– 70% of ALL operational analysis automatically delivered in

exception-oriented, human readable fashion – 95% reduced staff time per analysis 4x more staff

productivity– Avoided purchase of 100’s of physical servers,

simultaneously virtualizing thousands of servers in 2013 alone, saving $Millions

• Leading Banks, Telecoms, Retailers, and many more…– Bank of America, Barclays, gkv Informatik, HSBC, Safeway, T-

Systems, Telefonica, Vodafone, Verizon, Visa, Wells Fargo, …

Real Customers, Real Results


28

• Inventory IT processes and ALL your tools– Data collection?– Data storage?– Capacity Analysis/Reporting?

• Inventory your business KPIs, factor your BI analytic initiatives

• Identify “low hanging fruit”– By Service?– By BU?– By Platform?– By Technology/silo?

• Get started bringing it together, don’t wait

Summary and Recommended Steps

A #Pink14 Presentation: Optimizing for the #SDDC

Technology

Transcript of A #Pink14 Presentation: Optimizing for the #SDDC