Outgrowing your-datacenter

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When your datacenter starts reaching capacity, before building the next datacenter look to cloud computing for options.

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Outgrowing your-datacenter

  1. 1. Outgrowing your Data Center? Look to the Cloud for Relief
  2. 2. About the Presenter @madgreek65 mikekavis madgreek65 VP/Principal Architect @ Cloud Technology Partners Mike Kavis Agile Development madgreek65
  3. 3. Data Center Trends
  4. 4. 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
  5. 5. 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
  6. 6. Exponential Growth Source: http://irfansalam.wordpress.com/2012/08/21/zetabyte-era/
  7. 7. 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
  8. 8. Disaster Recovery Investments
  9. 9. Disaster Recovery Investments
  10. 10. Cost Reductions and Speed to Market
  11. 11. Cost Reductions and Speed to Market
  12. 12. Common Cloud Use Cases
  13. 13. Data Storage & Archiving
  14. 14. Data Storage & Archiving Backup infrastructure is expensive and is not elastic
  15. 15. Data Storage & Archiving
  16. 16. Cloud Bursting
  17. 17. Cloud Bursting
  18. 18. Cloud Bursting Bursting Strategies -Round Robin -All Peak Loads -Platinum Customers -Packet Size Oriented -API Oriented -SLA Oriented
  19. 19. Big Data Data Sources Extract System Extract System Transform System Transform System Load System Load System Data Warehouse Data Warehouse Enterprise ETL Design* Extract System Extract System Transform Function Transform Function Load Function Load Function * three distinct systems Hadoop Big Data ETL Design** * * two (or one?) distinct systems
  20. 20. Big Data Data Sources Extract System Extract System Transform System Transform System Load System Load System Data Warehouse Data Warehouse Enterprise ETL Design Extract System Extract System Transform Function Transform Function Load Function Load Function Hadoop Big Data ETL Design Private DC/Cloud Private DC/Cloud Public Cloud Public Cloud Public or Private Cloud Public or Private Cloud
  21. 21. 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?”
  22. 22. Disaster Recovery Strategies The “Gang of Three”
  23. 23. Disaster Recovery Strategies
  24. 24. Disaster Recovery Strategies
  25. 25. Disaster Recovery Strategies
  26. 26. Disaster Recovery Strategies
  27. 27. Dev & QA Environments Dev QA Stage Production One of the biggest time wasters is dealing with inconsistent target environments “It worked on my laptop!”
  28. 28. 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 teams Automate everything -Application Deployments -Environment Provisioning -Test Data Provisioning -Acceptance Testing
  29. 29. 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 help www.cloudtp.com

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