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Backing up the virtual datacentre. Charlie Llewellyn and Andy Powell from Eduserv

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A talking about backing up virtual data centres delivered at the UCISA 'Big data, big backups?' conference on 11 June 2013.

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Backing up the virtual datacentre. Charlie Llewellyn and Andy Powell from Eduserv

  1. 1. Backing up the virtual datacentre Charles Llewellyn and Matt Johnson
  2. 2. Eduserv in 3 slides • Founded in 1999 • Part of the community since 1988 • SME (150 staff, £12m turnover) • Not for profit & registered charity
  3. 3. What we do… • Infrastructure services • Cloud services • Managed services • Consultancy • Web development • Licence negotiation • Identity & access management
  4. 4. Who we work with…
  5. 5. Agenda • Understanding your data • Defining backup requirements • Overview of Eduserv’s data and requirements • Problems with traditional backups in a virtual datacentre • Solutions to traditional backup issues
  6. 6. Terminology • Recovery Point objective • Oldest point the data stored on backups can be • Recovery Time Objective • Time allowed to restore the data • Backup window • Time which the backup window must complete in
  7. 7. Terminology • Backup/Archive/DR • Backup: used to recover data following loss/corruption • Achieve: used to store data long term • Disaster recovery: policy and process to provide service continuation in event of catastrophic failure
  8. 8. Terminology • Consistency • Crash consistent: does not provide guarantees of data integrity • File system consistency: guarantees file system state • Application consistency: guarantees application consistency
  9. 9. Understand your data • Data structure • Highly transactional/static content
  10. 10. Highly transactional application Backup server Transactional data
  11. 11. Backup server Static application Static data
  12. 12. Understand your data • Data structure • Highly transactional/static content • Large or small files
  13. 13. File Metadata Backup server File Data File Metadata File Data File Metadata File Data Small files
  14. 14. File Metadata Backup server File Data Large files
  15. 15. Understand your data • Data structure • Highly transactional/static content • Large or small files • Rate of duplication • Data use • Useful life of the data • Does the data need to be backed • Who controls the data
  16. 16. Requirements • Why is the data backed up • Recovery Time Objective • Recovery Point Objective • Retention period • Offsite requirements • Cost
  17. 17. Virtual server data • Large and small files • High percentage of duplicated data • Data change rate varies • Typically short data life • What we don’t backup • We don’t control the data
  18. 18. Virtual server backup requirements • Restores: recover from deletion/corruption • Backup service that is independent from the OS • Fast backup and restores with low overhead • Short retention period • Ability to restore entire VMs or individual files • Single site/dual site • Self service backups • Scalability • Low cost
  19. 19. A very…brief backup history • One to one relationship between servers and backup disks http://www.flickr.com/photos/sylvar/31436967/sizes/l/in/photostream/
  20. 20. A very…brief backup history • Central backup tape repository for backup storage • Accessed via a client side agent • Traditional approach was used initially for virtual machine backups
  21. 21. Problems with traditional backups in a virtual world • Processing • High consolidation ratios mean higher impact • Agent based backups require client resources • Streaming to tape • No parallelisation • High latency • Issues with long term incremental backups • High administrative overhead
  22. 22. Problems with traditional backups in a virtual world • Restore time • Slow to locate and load tapes, and to locate data on tape • Slow to restore entire VM as process is the same as physical server • Storage footprint • Large storage foot print required as de-dup etc. cannot easily be used • To improve restore time full backups taken weekly
  23. 23. Resolutions to issues – disk to disk • Enhanced parallelisation of jobs • Reduced administrative overhead • Improved restore time • Reduced foot print
  24. 24. Resolution – move backups to the hypervisor • No more agents :-) • Change block tracking
  25. 25. Change Block Tracking
  26. 26. Resolution – move backups to the hypervisor • No more agents :-) • Change block tracking • Single backup to provide file level and image level restore
  27. 27. Virtual machine file make-up
  28. 28. Resolution – move backups to the hypervisor • No more agents :-) • Change block tracking • Single backup to provide file level and image level restore • Forever/Reversed incremental
  29. 29. Forever incremental
  30. 30. Reversed incremental
  31. 31. Resolution – move backups to the hypervisor • No more agents :-) • Change block tracking • Single backup to provide file level and image level restore • Forever/Reversed incremental • Scale-out infrastructure
  32. 32. Overview of backup infrastructure
  33. 33. What does this mean? • 170GB machine with static data • Traditional backup: ~3 hours • Virtualised backup: ~2 minutes • ~230TB VM data • Virtualised backup: ~3 hour backup window • Continue meeting the backup window with horizontal scaling
  34. 34. Conclusion • Understand your data • Understand your requirements • For virtual backups • Look at disk to disk for virtual platforms • Make sure you take advantage of low processing overhead such as change block tracking and single backups for image and file level restores • Only backup what you need to!
  35. 35. Thank you – questions? Charles Llewellyn and Matt Johnson
  • udomsakc

    Aug. 3, 2013

A talking about backing up virtual data centres delivered at the UCISA 'Big data, big backups?' conference on 11 June 2013.

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