Outgrowing your Data Center?

Look to the Cloud for Relief

About the Presenter

@madgreek65

mikekavis

madgreek65

VP/Principal Architect @ Cloud Technology Partners

Mike Kavis

Agile Development

madgreek65

Data Center Trends

Exponential Growth

Data center traffic will grow 4X by 2016 by 6.6 ZB annually

Majority of traffic is caused by datacenter and cloud workloads invisible to the end users

Source: Cisco Global Cloud Index: 2011-2016

Exponential Growth

Growth drives demand in physical infrastructure

Datacenters often growing at rates much faster than originally estimated

Driving demand for disk, servers, network infrastructure, bandwidth, cooling, floor space, etc.

Source: Cisco Global Cloud Index: 2011-2016

Exponential Growth

Source: http://irfansalam.wordpress.com/2012/08/21/zetabyte-era/

Green & Carbon Initiatives

Large infrastructure investments to get cleaner and greener

Apple, Google, Amazon, eBay are investing

Should companies whose core competency is not building datacenters be spending here? Proposed datacenter from Google & Duke

energy

Disaster Recovery Investments

Disaster Recovery Investments

Cost Reductions and Speed to Market

Cost Reductions and Speed to Market

Common Cloud Use Cases

Data Storage & Archiving

Data Storage & Archiving

Backup infrastructure is expensive and is not elastic

Data Storage & Archiving

Cloud Bursting

Cloud Bursting

Cloud Bursting

Bursting Strategies-Round Robin-All Peak Loads-Platinum Customers-Packet Size Oriented-API Oriented-SLA Oriented

Big Data

Data Sources

Extract

System

Extract

System

TransformSystem

TransformSystem

LoadSystemLoadSystem

Data Warehouse

Data Warehouse

Enterprise ETL Design*

Extract

System

Extract

System

TransformFunction

TransformFunction

LoadFunctio

n

LoadFunctio

n

* three distinct systems

Hadoop

Big Data ETL Design*** * two (or one?) distinct systems

Big Data

Data Sources

Extract

System

Extract

System

TransformSystem

TransformSystem

LoadSystemLoadSystem

Data Warehouse

Data Warehouse

Enterprise ETL Design

Extract

System

Extract

System

TransformFunction

TransformFunction

LoadFunctio

n

LoadFunctio

n

Hadoop

Big Data ETL DesignPrivate

DC/CloudPrivate

DC/Cloud

PublicCloudPublicCloud

Public or Private Cloud

Public or Private Cloud

Disaster Recovery

RTO (Recovery Time Objective) “Time to be back up & running”

RPO (Recovery Point Objective) “Maximum time in which data is lost”Value“How much money is recovery worth?”

Disaster Recovery Strategies

The “Gang of Three”

Disaster Recovery Strategies

Disaster Recovery Strategies

Disaster Recovery Strategies

Disaster Recovery Strategies

Dev & QA Environments

Dev QA Stage Production

One of the biggest time wasters is dealing with inconsistent target environments

“It worked on my laptop!”

Dev & QA Environments

Standard Environments- Devs get consistent, patched, secure images in all environments

Create self-service provisioning- Stop being the bottleneck and enable the development teamsAutomate everything-Application Deployments-Environment Provisioning-Test Data Provisioning-Acceptance Testing

Summary

Before building or expanding the next datacenter- Look to the cloud for hybrid use cases

Common Patterns-File Storage and Archiving-Cloud Bursting-Big Data-Disaster Recovery-Dev & QA Environments

Cloud Technology Partners can helpwww.cloudtp.com