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Data Deduplication in Virtualized Environments Marc Crespi, ExaGrid Systems

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Presentation on theme: "Data Deduplication in Virtualized Environments Marc Crespi, ExaGrid Systems"— Presentation transcript:

1 Data Deduplication in Virtualized Environments Marc Crespi, ExaGrid Systems http://blog.exagrid.com Twitter: @ExaGrid

2 About the speaker  Marc has over 20 years of software and hardware experience in the high technology sector  He is part of the ExaGrid team that drives product strategy and execution and is responsible for managing product operations.  Prior to joining the company, Marc was director of product management for security management products at Altiris.

3 Objective of This Program What is Deduplication? Why Use Deduplication in Backup and Recovery? Challenges of Deduplication in Virtualized Environments Deduplication approaches (two camps) Summary ‒ Deduplication’s Role in Data Protection and Disaster Recovery

4  Enhanced Speed/Performance ●Faster backup times due to lower volume of data to be backed up ●Data lands faster because it is targeted at disk  Dramatic Savings in Disk Costs ●20:1 Reduction in amount of disk space required to store backups  Scalability ●Backup higher data volumes while maintaining backup window  Offsite Disaster Recovery ●Efficient use of bandwidth via WAN-efficient replication Why Use Deduplication in Backup and Recovery?

5 VM Reduced storage footprint with deduplication  Reduce total amount of storage by as much as 1000:1  Store only the bytes that change in your VMware virtual servers  Eliminate redundancy of typical VMware backups  Restore quickly from most recent VMware backup  Each virtual server image gets backed up in its entirety  Large amount of storage consumed  Deduplicate backups to changed bytes  Dramatic savings in disk and bandwidth  Integrated Replication Eliminate Redundancies for More Efficient Virtual Server Backups VM

6 Specific Challenges of Backups/Restores in Virtualized Environments  Management of backups ●Growing number of virtual machines/ sprawl ●Inability to monitor backups on individual virtual machines  Handling the volume of backup data efficiently ●More data to store as virtual machines proliferate ●Each change means entire virtual server is backed up These challenges are driving a need for better tools to more reliably and easily back up and restore virtual machines Example: 10 guest OS instances x 50GB = 500GB of backed-up virtual images daily

7 How Dedupe Works: Store Only Changed Bytes Standard Disk Total 500GB Total 3.4GB 2.5GB 100MB Oldest Backup Most Recent Backup 50GB Oldest Backup Most Recent Backup Stored Optimized for Read 100MB Data Deduplication 50GB VM 500GB 3.4GB

8  2011 ExaGrid Systems, Inc. Where to Deploy Deduplication PROS  Reduces impact on VM  Shortens BU window/less data  Reduced bandwidth needed to the backup target  Reduction in storage usage CONS  Can be slower for large (multiple TB) amounts of data  Increased workload on servers PROS  Shortens BU window/less data  Reduced replication bandwidth  Reduction in storage usage CONS  Must transfer the entire dataset to the device  Don’t get reduced bandwidth needed to the backup target Target Based Data Reduction Removes data redundancies after transmission to the backup target Source Based Data Reduction Removes data redundancies before transmission to the backup target

9  2011 ExaGrid Systems, Inc.  Achieves an additional 80% data reduction (98% total) ●Further reduction in bandwidth ●Further reduction in storage usage ●Further reduction in backup window  Integrated replication of virtual servers Source Based PLUS Target Based Data Deduplication Removes data redundancies before and after transmission to the backup target Using Both Deduplication Techniques Provides Complementary Benefits

10  2011 ExaGrid Systems, Inc. Architectural Considerations Scalable GRID Architecture Multiple Deduplication Engines Legacy Architecture - Single Controller One Deduplication Engine Backup Window X TB/hr 20 TB 30 TB 40 TB 50 TB 60 TB Disks Deduplication Engine X TB/hr 2X TB/hr 3X TB/hr 4X TB/hr 5X TB/hr 6X TB/hr 20 TB 30 TB 40 TB 50 TB 60 TB 10 TB Deduplication Engine Backup Window

11  2011 ExaGrid Systems, Inc. Architectural Considerations Scalable GRID Architecture Multiple Deduplication Engines Legacy Architecture – Single Controller Legacy Architecture – Appliance Sprawl One Deduplication Engine  Linear performance as data grows, stable backup window  Capacity is virtualized across nodes  Deduplication is shared across nodes  Simplified management through single UI  System can be right-sized to current data size  Avoids forklift upgrades Scalable GRID Features Individual appliances Deduplication Engine

12 Benefits  One-time division of data during installation (15 to 30 minutes)  GRID software manages placement of data  Revisit only during expansion (additional 15 to 30 minutes)  Eliminates the challenges of monolithic, primary storage like architectures GRID Architecture for Deduplication Performance Backup Servers Wire Speed Node 1 – System Capacity – RAID6 Landing Zone Node 2 – System Capacity – RAID6 Repository Landing Zone Deduplication Process Load Balancing Backup Job VM

13 What We Covered What is Deduplication? Why Use Deduplication in Backup and Recovery? Challenges of Deduplication in Virtualized Environments Overview Diagram of Major Components Deduplication approaches (two camps) Summary ‒ Deduplication’s Role in Data Protection and Disaster Recovery

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