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Backing up the virtual datacentre
Charles Llewellyn and Matt Johnson
Eduserv in 3 slides
• Founded in 1999
• Part of the community since 1988
• SME (150 staff, £12m turnover)
• Not for profit & registered charity
What we do…
• Infrastructure services
• Cloud services
• Managed services
• Consultancy
• Web development
• Licence negotiation
• Identity & access management
Who we work with…
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
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
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
Terminology
• Consistency
• Crash consistent: does not provide guarantees of data
integrity
• File system consistency: guarantees file system state
• Application consistency: guarantees application
consistency
Understand your data
• Data structure
• Highly transactional/static content
Highly transactional
application
Backup server
Transactional data
Backup server
Static application
Static data
Understand your data
• Data structure
• Highly transactional/static content
• Large or small files
File
Metadata
Backup server
File Data
File
Metadata
File Data
File
Metadata
File Data
Small files
File
Metadata
Backup server
File Data
Large files
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
Requirements
• Why is the data backed up
• Recovery Time Objective
• Recovery Point Objective
• Retention period
• Offsite requirements
• Cost
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
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
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/
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
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
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
Resolutions to issues – disk to disk
• Enhanced parallelisation of jobs
• Reduced administrative overhead
• Improved restore time
• Reduced foot print
Resolution – move backups to the hypervisor
• No more agents :-)
• Change block tracking
Change Block Tracking
Resolution – move backups to the hypervisor
• No more agents :-)
• Change block tracking
• Single backup to provide file level and image level
restore
Virtual machine file make-up
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
Forever incremental
Reversed incremental
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
Overview of backup infrastructure
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
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!
Thank you – questions?
Charles Llewellyn and Matt Johnson

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Backing up Virtual Data with Change Block Tracking

  • 1. Backing up the virtual datacentre Charles Llewellyn and Matt Johnson
  • 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. What we do… • Infrastructure services • Cloud services • Managed services • Consultancy • Web development • Licence negotiation • Identity & access management
  • 4. Who we work with…
  • 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. 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. 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. Terminology • Consistency • Crash consistent: does not provide guarantees of data integrity • File system consistency: guarantees file system state • Application consistency: guarantees application consistency
  • 9. Understand your data • Data structure • Highly transactional/static content
  • 12. Understand your data • Data structure • Highly transactional/static content • Large or small files
  • 13. File Metadata Backup server File Data File Metadata File Data File Metadata File Data Small files
  • 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. Requirements • Why is the data backed up • Recovery Time Objective • Recovery Point Objective • Retention period • Offsite requirements • Cost
  • 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. 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. 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. 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. 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. 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. Resolutions to issues – disk to disk • Enhanced parallelisation of jobs • Reduced administrative overhead • Improved restore time • Reduced foot print
  • 24. Resolution – move backups to the hypervisor • No more agents :-) • Change block tracking
  • 26. Resolution – move backups to the hypervisor • No more agents :-) • Change block tracking • Single backup to provide file level and image level restore
  • 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
  • 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. Overview of backup infrastructure
  • 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. 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. Thank you – questions? Charles Llewellyn and Matt Johnson