From Early Adopter to Enterprise Virtualization Evolution

From Early Adopter to Enterprise Private Cloud: One Company’s

Virtualization Evolution

Ken Peck Director of IT

DaVita

Agenda

• Introduction

• About DaVita

• DaVita’s Virtualization History

• Where we are today

• What’s on the horizon

• Insights

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

• 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

• Interesting facts

– 4,200 Servers (2,200 distributed in clinics)

– 1 PB of SAN Storage

– 2 main data centers

Virtual, Cloud, Public, Private…

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

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

• 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

Assessment Results – CPU Util

11

Better Utilization of Resources

12

Before Virtualization After

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

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

• 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)

Discovery & CMDB

Network & Server Automation

Operations Orchestration

Monitoring: OpenView

Business Service Management

• Business Service Management (BSM)

• Service Level Monitor (SLM)

• Business Process Monitor (BPM)

• Real User Monitor (RUM)

• Diagnostics

Service Intelligence

• Service Health Reporter

• Service Health Optimizer

• Service Health Analyzer

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

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



• Diagnostics


– Service Intelligence

• Service Health Reporter (SHR)

• Service Health Analyzer (SHA)

• Service Health Optimizer (SHO

HP Tools Summary Automation

• Configuration



• Automation




• Monitoring







• Diagnostics






HP Tools Summary Monitoring

• Configuration



• Automation




• Monitoring







• Diagnostics






HP Tools Summary

• Configuration



• Automation




• Monitoring







• Diagnostics





• Service Health Optimizer (SHO)

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

Q&A

• Appendix following

From Early Adopter to Enterprise Virtualization Evolution

Documents

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