A #Pink14 Presentation: Optimizing for the #SDDC

Optimizing the
Software Defined Data Center
Continuously operate at the intersection of Business Performance and IT Efficiency

David Wagner – TeamQuest Advocate

BOOTH #401
TeamQuest and the TeamQuest logo are registered trademarks in the US, EU and
elsewhere.
Copyright © 2014 TeamQuest Corporation. Allthe property of their respective owners.
All other trademarks and service marks are Rights Reserved.

Agenda
• 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

Copyright © 2014 TeamQuest Corporation. All Rights Reserved.

Today’s situation
• 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)

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

78%
81%
80%
79%

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

79%
79%
80%
77%
63%
63%
60%
61%

Automate the management of virtualized servers to
gain flexibility and resiliency
Build an internal private cloud operated by IT (not a
service provider)
Use cloud infrastructure-as-a-service (IaaS) at a
service provider

29%
23%

18%

36%

46%

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

35%
31%
28%

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”
Source: Forrsights Hardware Survey, Q3 2009, 2010, 2011, 2012
© 2013 Forrester Research, Inc. Reproduction Prohibited

4

Dynamism increasing
“What percentage of your total x86 servers OS instances are in each of the following
categories?”
Today (N=486)

In four years (N=476)

On physical servers not virtualized

42%

23%
32%
31%

On relatively static virtual servers
13%

On a dynamic private cloud pool of virtual servers

Traditional hosting offering
Hosted private cloud IaaS

Outsourced service provider
Public cloud IaaS

27%

5%
4%
3%
3%
4%
1%
3%

7%

In four years, enterprise respondents
expect to move about 20% of their
current physical servers into a private or
public cloud

Base: North American and European IT decision makers at enterprise firms using physical x86 servers
Source: Forrsights Hardware Survey, Q3 2012

The business values analytics…

Improve the use of data analytics to
improve business decision making


Challenges and Obstacles
• 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

Cloud, Virtualization and SDDC ->
Changing Demands on Enterprise
IT
Business Services/Applications

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….

Increasing Planning and
Optimization Challenges
Business Services/Applications

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….

Management is WAY more
than monitoring
• 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


“IT doesn’t analyze business
data because…”
• 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?


Negative consequences
of the current state
• 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

Desired State:
Fully Leverage Commoditization

Base: 1048 IT hardware decision makers at enterprises in North America and Europe
Source: Forrsights Hardware Survey, Q3 2012
© 2013 Forrester Research, Inc. Reproduction Prohibited

13

Desired state:
Continuous Optimization
• 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:
Answer the Questions!
“What is the health
of the
infrastructure?”
“What’s the risk
assessment?”

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

“How many of
those do we have?
Need? When?”

“What were the
exceptions? Do we
Care?”

“What’s the
capacity forecast?
What should/will it
cost?”

“Changes
compared to the
last reporting
period?”

Result:
Continuous IT Optimization
• 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


Methodology:
Aligned Business and IT Analytics
Big Data Collection
Underlying IT
Infrastructure

Outage
Management

Customer
Operations

Distribution
Automation

Asset
Management

Services

Enterprise IT
Optimization
• Correlate
business & IT
performance
• Insight into how
business process
changes impact IT

Applicatio
ns

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

Server/OS

Network

• Insight into
business
performance
across technology
stack

Storage

Business Intelligence

Aligned Business and IT Intelligence

17

Automated, Aligned IT Analytics
• Analyze - optimize decision making
• Integrate - with the business
• Automate – drive efficiency and repeatability


Federated 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


Automated, Predictive Analytics


20

Result:
Automated Financial Optimization
• Continuous Optimization
– Pre-purchase validation
– Re-purposing
– Consolidation

• Fully Automated, low cost
• Integrate with Risk and
Service Management
• Changed new VMware
Clusters from every 6
weeks to:
– None for 18+ months…
– Consolidated 1000’s of
VM’s (Saving $M)


Result:
IT Power Capacity 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:
Automated Root Cause Analytics
• 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:
Financial Optimization Reports
• 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:
IT Optimized... Future Assured
• 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


TeamQuest:
Insight Automated. Optimization Achieved

“I know what my
risks to
performance are
and will be!”
“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 the
performance and
costs of my
infrastructure!”

“I understand the
exceptions and their
importance!”

“I have a Capacity
and Financial
Plan!”

“I know what has
changed and why
from the last
period!”

Real Customers, Real
Results
• 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 exceptionoriented, 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, TSystems, Telefonica, Vodafone, Verizon, Visa, Wells Fargo, …


Summary and Recommended
Steps
• 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

28

A #Pink14 Presentation: Optimizing for the #SDDC

Recomendados

Recomendados

Mais conteúdo relacionado

Mais procurados

Mais procurados (19)

Semelhante a A #Pink14 Presentation: Optimizing for the #SDDC

Semelhante a A #Pink14 Presentation: Optimizing for the #SDDC (20)

Mais de TeamQuest Corporation

Mais de TeamQuest Corporation (12)

Último

Último (20)

A #Pink14 Presentation: Optimizing for the #SDDC

Notas do Editor