copyright © 2012 teamquest corporation. all rights reserved. teamquest and the teamquest logo are...

Copyright © 2012 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.

Virtualization, Cloud and Big Data

IT Operational Analytics to Cost optimize the “Virtual Everything” IT Universe

David Wagner – TeamQuest Advocate


• Presentation is an adaptation of recent TeamQuest and Forrester Research Webinars:– “Business AND IT Analytics: You need both to optimize

Business”• James Staten, Vice President and Principal Analyst, Forrester Research• David Wagner, Advocate, TeamQuest• September 12, 2013

– “Beyond Virtualization: Accelerating the Road to Software Defined Computing”

• Richard Fichera, Vice President and Principal Analyst, Forrester Research• David Wagner, Advocate, TeamQuest• August 15, 2013

• Recordings of both Webinars available: www.teamquest.com

All Forrester content with permission and noting attribution

Background

http://www.teamquest.com/


• What is a Software Defined Data Center?– Definition, evolution, capabilities , approaches…

• Business Analytics with IT data– Definition, evolution, capabilities, approaches…

• Cost Optimization: – Or… “The corner of Business Analytics, IT Analytics and SDDC

meet the discipline of Performance Analysis and Capacity Management”

Agenda



Software Defined Data Center

Rich Fichera, VP and Principal Analyst, Forrester Research


• An integrated abstraction layer that presents computing infrastructure as pools of virtual and physical resources, allowing users to dynamically compose them into Services– Rich Fichera: Forrester, September 2013

• Forrester, VMware, and others (e.g. Bernd Harzog, The Virtualization Practice) call this the “Software Defined Data Center”

Software defined computing

Copyright © 2012 TeamQuest Corporation. All Rights Reserved.© 2013 Forrester Research, Inc. Reproduction Prohibited 6

Enterprises will deploy their new virtual servers in dynamic pools

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


New data center technologies focused on reducing manual

assembly & config

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

Source: Forrsights Hardware Survey, Q3 2012


• Respond faster to business spikes– USAA’s mobile app created 10x the transaction volume than it

expected

• Deploy and refresh new applications faster– Retailers need to capture their share of mobile commerce as

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

• Reduce upfront capital outlays and system operating expense

• Optimize resources for systems of engagement• This is not the end of the road

Forrester content

So, enterprises see the benefit of data center abstraction


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

Virtualization remains highest IT infrastructure priority, but cloud gaining

“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”


• Inclusion of legacy or non-virtualized hardware resources?

• Interoperability of multiple vendors’ converged infrastructure systems?

• Software-defined networking approach – SDN vs. OpenFlow vs. Cisco

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

Forrester content

Architectural challenges for SDDC


• SDDC management will place a premium on new management models– Real time data collection– 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 management vendors

Forrester content

Management is more than monitoring


• The term is largely unheard of, but infrastructure leaders generally understand or can guess what this implies

• More senior leaders think of consolidated data centers of the past

– But many are “wait and see”– “Sounds nice, but how do we get there?”

• Skepticism that one company can do servers, storage and network well

– That impression might be different when speaking to established converged infrastructure customers (UCS/VCE/FlexPod/Pure customers)

• Server virtualization is seen as much more advance than SDN or software defined storage

• Buy-in on the concept will require cross-silo strategy and collaboration and threaten established centers of power in the data center

Forrester content

Software defined data center - Considerations



Business Analytics with IT Data

James Staten, VP and Principal Analyst, Forrester Research


• It’s a mess• It isn’t standardized• Value isn’t intrinsically measurable• Systems can’t talk to each other• It isn’t easily presented or understood

“We don’t Leverage IT Data because…”

© 2013 Forrester Research, Inc. Reproduction Prohibited 15

Pop quiz:What is the businessmore worried about?

Adjusting to what we know is changing in our

market

Adjusting to what wedon’t know


True business visibilityis limited

What they know:

› Sales growth

› Seasonality

› Customer feedback

What they don’t:

› How well services are performing

› Why customer experiences are poor

› What IT knows

Intelligence—not data—will be the difference between success and failure.

Source: Forrsights Strategy Spotlight: Business Intelligence And Big Data, Q4 2012

2.7 Zettabytes

1.2 yrs

$600B


› It’s a mess

› Isn’t standardized

› Value isn’t intrinsically measurable

› Systems can’t talk to each other

› Isn’t easily presented & understood

We don’t leverage IT data because . . .


But the business values this over all else

Source: Forrsights Business Decision-Makers Survey, Q4 2012; Base: 1,170 EMEA business decision-makers

Improve the use of data analytics to improve business decision making 19% 40%


What IT data can tell the business

1. When & where customer experience breaks down

2. Where inefficiencies lie in key business processes

3. When & where performance problems really affect the bottom line

4. When legal issues arise (and how to prevent them)

5. Find root causes that result in customer dissatisfaction

6. Find and see past false indicators

The Most Popular Types Of IT Analytics, How They Work, And Their Value

December 2012 Forrester Report: “Turn Big Data Inward With IT Analytics”

Topological Relationships Help Map Cause-E ect Phenomenaff


Statistical Analytics Uncovers Performance Patterns


Configuration Analytics Spots Changes And Policy Violations



What you can do about it

1. Unify IT data• Centralize the analysis – views by role

2. Map the business to IT systems• Then you can map business efficiency

3. Show the business what you find• Then let them at the tool for their own analysis



Business AND IT AnalyticsUsing both to optimize the business in a

“virtualized everything” worldDavid Wagner - TeamQuest


• “You have what the business wants”• “Map to business to IT

systems, then you canmap business efficiency”– James Staten (9/12/13)

• “The business already has what you NEED”

• “Map IT to the business, then you can map IT efficiency”– Dave Wagner (10/04/13)


• Our existing tools don’t accept it– ETL into acceptable format(s) is a lot of

work, cost– Manual efforts won’t scale

• We have 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?

“We don’t use business data because…”


• Software Defined Data Center• Business Analytics and IT

– Revolutionary new business technologies ->

Data growth– Analytics for business, fed by IT

• IT changes: Cloud, Virtual, SDDC…• IT performance & capacity management

impact– Challenges– An analytic approach

Topics


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

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

usi

ne

ss S

erv

ice

s/A

pp

lica

tion

s

Cloud, Virtualization and SDDC -> Changing Demands on Enterprise IT


Increasing Planning and Optimization Challenges

Bu

sin

ess

Se

rvic

es/

Ap

plic

atio

ns

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

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


Underlying IT Infrastructure

Outage Management

Customer Operations

Distribution Automation

Asset Management

32

Requirement: Align IT performance/capacity and business across technologies

Services

Applications

Server/OS

Big Data Collection

Business Intelligence

Aligned Business and IT Intelligence

Enterprise Performance & Capacity Mgt.

• Correlate business process & IT performance

• Insight into how business process changes impact IT

• Understand IT costs by business unit/process

• Insight into business process performance all the way down to storage components

Network

Storage


Needing answers…

“What is the health of the

infrastructure?”

“How efficiently are we using

the infrastructure?

”

“How many of those do we have? Need?

When?”

“Changes compared to the

last reporting period?”

“What’s the capacity

forecast?”

“What were the exceptions? Do we

Care?”“What’s the risk assessment?”


• Analytics– Monitoring technology performance utilization trends,

statistics– “Siloed” problem analysis– Planning focus: optimizing server cost versus performance

• Extremely technology-centric – in isolation– Servers and mainframes: physical and virtual– Storage and network: physical and virtual

• Big value and return, but also a big effort– Requires highly trained staff; domain expertise– Requires building a central, long-term repository (CMIS or

PMDB)– Problems with scalability of staff and tools … Politics!

Capacity management:Today’s IT optimization tradition


• Build on traditional value– Optimize more resources– Amplify– Accelerate

• Increase business relevance– Valuable predictive analytics in business and service context– Optimize efficiency

• Virtualization and cloud SDDC: scale everything– Many-to-many interrelationships; capacity more critical– Back end performance now more critical– Front-end devices -> performance and capacity

New capacity management goals


• Continuous DevOps, consolidation, repurposing, re-hosting, etc.– Least used (servers, virtual servers, storage, etc.)– Most power (consumption, carbon footprint, etc.)– Most expensive (total OpEx)– By application, over time… and many more

• Financial optimization – not utilization anymore!– Under-used doesn’t necessarily mean wasteful!– Over-used doesn’t necessarily mean lost

revenue/profit

• Goal: eliminate true waste, ensure performance

Infrastructure optimization


• Asset database– Server CapEx, OpEx and licensing costs

• Service catalog– Mapping of applications to servers/virtual servers

• Power consumption and cost– kWh per server– cost per kWh over time, versus dynamic demand,

etc.

• Resource utilization, events, etc…– By server, virtual server and application, storage,

network…

Infrastructure optimization data sources (some)


• Build a huge “data mart” (i.e. PMDB) Complexity = (data ETL) x (# sources) x (maint. effort) x (SDDC variability/dynamism) x … + Compliance: Data duplication, privacy, audit, etc… + Lock in” = Very costly and time-consuming

• Apply general purpose BI analytics– Not focused on IT Resource optimization,

performance

• Agility? Core competence?

A Sub-optimal Approach:BI-type IT Data Warehousing


INTRODUCING A “BIG DATA” TYPE ANALYTIC APPROACH

A Better Solution

39


• Federate existing data into purpose-designed performance/capacity process – Technology data (e.g. server, network, storage,

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

TXNs, etc.)

• Automate analytics across all data sources– Flexible and adaptive to dynamic SDDC

environments– Raw (commodity) data -> actionable information

for IT• Latency & throughput, not simple utilization rates or

availability

• Single-pane-of-glass management

A “Big Data” type analytic approach


SOME EXAMPLESA “Big Data” Analytic Approach

41


• Business, service, asset and power – Continuous financial optimization

• Service tickets and performance/capacity– Risk management

• Spanning pure technology silo challenges– Improve availability and speed MTTR

• Risk prediction – by latency/use

Analytic examples: Multi-data types


Financial optimization report


Risk: Service desk and capacity


Virtualized Servers AND storage - together


Servers AND storage — together


Servers AND storage - together

Huge

Value

for

Virtual/Cloud

Environments:

Cross the Chasm!


TEAMQUEST PERFORMANCE INDICATOR

Managing Performance that Matters

48


TeamQuest Performance Indicator:Automating proactive latency

analytics


Automated, exception-based analytics


Automated queuing RCA


Latency holistic RCA:Server, workload, VM *and*

storage


53

• Large Insurance– Multi-year transition to dynamic grid and virtualization– Improved resource utilization by over 400%– Saved $25M over 3 years – expense deferral while

maintaining SLAs

• Large Finance– Deferred massive, planned data center build out by 18

months and counting ($20M+ to-date)– Reduced service risks, lowered operational costs, expanded

staff scope/reach

• Cloud AAS Provider– Sped MTTR for client-facing services by several fold

• Telecommunications– Sped client-facing infrastructure MTTR, cost-reduction, right-

sizing

Results


NEW! TEAMQUEST RISK PREDICTOR

Assuring Peak Performance

54


55

TeamQuest Risk Predictor

• Know how long you've got until response time will suffer

• Rules by TPI, utilization, percent change in response time


56

Exception-based latency prediction:

by workload, VM, system…


57

Auto-predicted queuing analytics:By workload, VM, system…

• Continuous, Rolling Prediction• Automated Re-baselining• Complete Components of Response Time (latency)


• Federation maps virtually all sources… but not all– Low effort– Rapid time to value

• Any chosen analytics must handle– Multiple, disparate sources– Modularly, combinatorial

• You will want rule-based automation of analytics– Flexible, easy to modify– Only way to “human scale” in dynamic, large IT environments

• Pick “low hanging fruit” for first project(s)!– Use existing data sources instead of boiling the ocean– Build from your wins

Additional analytic considerations


59

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

• Inventory business KPIs, factor 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


TeamQuest: Insight Gained

“I know the performance of my

infrastructure!”

“I know how efficient my IT environment is and can be!”

“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 Plan!”

“I understand the exceptions and

their importance!”

“I know what my risks to

performance are and will be!”


61

• Peak Performance

• Ideal Capacity

• Optimized Costs

TeamQuest: Assuring your Future!


62

Questions?

copyright © 2012 teamquest corporation. all rights reserved. teamquest and the teamquest logo are...

Documents

teamquest corporation

teamquest logo

forrester research slide

adaptation of recent

forrester research webinars

computing slide

forrester content

data definition