from early adopter to enterprise virtualization evolution
TRANSCRIPT
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From Early Adopter to Enterprise Private Cloud: One Company’s
Virtualization Evolution
Ken Peck Director of IT
DaVita
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Agenda
• Introduction
• About DaVita
• DaVita’s Virtualization History
• Where we are today
• What’s on the horizon
• Insights
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Introduction
• Ken Peck – Director of IT in the Office of the CTO
– 16+ years in IT
– Husband, father, grandfather
– Pilot & airplane builder
– Innovator
• Scott Siegfried – Infrastructure Principle Architect in the Office of the CTO
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• Fortune 500 Healthcare company
• Dialysis provider ~150,000 patients
• ~2,000 clinics
• Consistenly surpasses national averages for clinical outcomes and leads in multiple indicators
• Culture of Mission and Values
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• Interesting facts
– 4,200 Servers (2,200 distributed in clinics)
– 1 PB of SAN Storage
– 2 main data centers
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Virtual, Cloud, Public, Private…
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The Early Years (2002-2005)
• VM – a new shiny object – The good
• Worked right out of the box
• Very attractive value proposition
• Some success virtualizing systems
– The not so good • Complex licensing models
• Skill sets underdeveloped
• Operational tools inadequate
• Some systems not successfully virtualized
• Application owner resistance
– Result – early start which stalled
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The Middle Years (2005-2010)
• New business drivers – Unprecedented growth – servers & storage
– Absorb acquisition’s systems into data center
– Acquisition some new technology w/ businesses
– Power and space constraints
• The response – Solve data center constraints with virtualization
– Integrate acquired SAN virtualization technology
– Develop skill sets and process to leverage virtualization
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• Evaluated Citrix ZenServer, MS Hyper-V and VM Virtual Enterprise Infrastructure
• Conducted Infrastructure Assessment using VMware Capacity Planner tool – Onsite performance data collection April-May ‘08
– Targeted all production systems (331 servers)
– Peak CPU utilization avg 8%
– Avg CPU utilization 5%
• Resulting target approach – 253 Physical server consolidated to 9 (n+1)
Focus on Virtualization
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Assessment Results – CPU Util
11
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Better Utilization of Resources
12
Before Virtualization After
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Yesterday(2010 – 2012) • Status of virtualization
– Instituted Virtual First policy for servers – Deployed next generation of virtualization for Windows and Unix – DeployedvSphere/vCenter
• Benefits Realized – Quicker & chearper to deploy new servers – Quicker server recovery from hardware failures – Able to stay in existing data center w/ minimal changes – More storage flexibility – Application owners understand the WIFFM
• Challenges – Lower entry cost can drive virtual server sprawl – Staying ahead of the curve on disk space – Data center constraints are still there
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Today and Tomorrow (2013 and beyond)
• New business drivers
– SaaS product requires increased availability
– Expansion into new markets and lines of business
– Future business climate demands flexibility
– Mobile/Social/Big Data
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• So far…
– Opened second data center
– Purchased monitoring and automation tools
– Purchased new incident/problem managemt tool
– Implementation of both in progress
• Projected benefits
– Accommodate significant growth & flexibility
– Self-provisioning of servers
– Business service management
Today and Tomorrow (2013 and beyond)
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Discovery & CMDB
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Network & Server Automation
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Operations Orchestration
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Monitoring: OpenView
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Business Service Management
• Business Service Management (BSM)
• Service Level Monitor (SLM)
• Business Process Monitor (BPM)
• Real User Monitor (RUM)
• Diagnostics
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Service Intelligence
• Service Health Reporter
• Service Health Optimizer
• Service Health Analyzer
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Integration: Business Service
• Abstracted & Non-Technical info needed in Service-Now
• Discoverable / technical attributes sourced in uCMDB
• Key items synchronized across uCMDB, RTSM and Service-Now – Business Services
– Servers
– Databases
– Network Elements
• Process – Taxonomy
– Naming Conventions
– Granularity Definition
– Governance
– Source of Record
– Attributes
Databases
Servers
Network Elements
Business Service Instance
Business Service EHR
Falcon EHR Prod
Switch
Server1
DB1
Server2 Server3
DB2
Demographic
Owner
CM Approver
QA Contact
Technical SME
Support Tier
SOX
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HP Tools Summary Configuration
• Configuration
– Discovery & Dependency Mapping (DDM)
– Universal Configuration Management Database (uCMDB)
• Automation
– Server Automation (SA)
– Network Automation (NA)
– Operations Orchestration (OO)
• Monitoring
– HP Operations Manager (OM)
– Network Node Manager (NNM)
– Business Service Management (BSM)
• HP OMi & Topology Based Event Correlation
• Business Process Monitor (BPM)
• Real User Monitor (RUM)
• Diagnostics
• Service Level Monitor (SLM)
– Service Intelligence
• Service Health Reporter (SHR)
• Service Health Analyzer (SHA)
• Service Health Optimizer (SHO
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HP Tools Summary Automation
• Configuration
– Discovery & Dependency Mapping (DDM)
– Universal Configuration Management Database (uCMDB)
• Automation
– Server Automation (SA)
– Network Automation (NA)
– Operations Orchestration (OO)
• Monitoring
– HP Operations Manager (OM)
– Network Node Manager (NNM)
– Business Service Management (BSM)
• HP OMi & Topology Based Event Correlation
• Business Process Monitor (BPM)
• Real User Monitor (RUM)
• Diagnostics
• Service Level Monitor (SLM)
– Service Intelligence
• Service Health Reporter (SHR)
• Service Health Analyzer (SHA)
• Service Health Optimizer (SHO
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HP Tools Summary Monitoring
• Configuration
– Discovery & Dependency Mapping (DDM)
– Universal Configuration Management Database (uCMDB)
• Automation
– Server Automation (SA)
– Network Automation (NA)
– Operations Orchestration (OO)
• Monitoring
– HP Operations Manager (OM)
– Network Node Manager (NNM)
– Business Service Management (BSM)
• HP OMi & Topology Based Event Correlation
• Business Process Monitor (BPM)
• Real User Monitor (RUM)
• Diagnostics
• Service Level Monitor (SLM)
– Service Intelligence
• Service Health Reporter (SHR)
• Service Health Analyzer (SHA)
• Service Health Optimizer (SHO
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HP Tools Summary
• Configuration
– Discovery & Dependency Mapping (DDM)
– Universal Configuration Management Database (uCMDB)
• Automation
– Server Automation (SA)
– Network Automation (NA)
– Operations Orchestration (OO)
• Monitoring
– HP Operations Manager (OM)
– Network Node Manager (NNM)
– Business Service Management (BSM)
• HP OMi & Topology Based Event Correlation
• Business Process Monitor (BPM)
• Real User Monitor (RUM)
• Diagnostics
• Service Level Monitor (SLM)
– Service Intelligence
• Service Health Reporter (SHR)
• Service Health Analyzer (SHA)
• Service Health Optimizer (SHO)
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Insights
• Desired business outcomes should drive technology decisions
• The key factors are people, processes, technology, time and money
• You never reach the desired end state, just new current states
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Q&A
• Appendix following
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