ITPG-CTG CYQ1 QBR

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ITPG-CTG CYQ1 QBR

Scale-out Object Store for PB/hr
Backups and Long Term Archive
April 24, 2014
Gideon Senderov
Director, Advanced Storage Products
NEC Corporation of America
Long-Term Data in the Data Center
Consumption of Enterprise
Disk Capacity by Type
(EB)
CAGR
140
120
100
46.0%
80
60
83%
47.5%
40
20
28.8%
22.5%
0
2011
2012
2013
Content Depots & Cloud
Unstructured data
Replicated data
Structured data
Page 2
© NEC Corporation of America 2014
2014
2015
2016
Source: IDC, November 2012
PBBA Market Forecast (CY2012 - CY2017)
Market is growing fast.
(Source: IDC)
Page 3
Archive Market Trend
▌ Expected rapid growth in disk based archive market due to wide usage of active archive,
growing with CAGR 35%, and reach $5.7B WW in 2016
▌ File- and Object-Based Storage (FOBS) market exceeding $23B in 2013, projected to grow
with CAGR 25% and reach $38B WW in 2017 (IDC, August 2013)
WW Disk based Archive sales forecast
6,000
Sales revenue ($M)
5,000
4,000
3,000
2,000
1,000
CAGR
35%
0
2010 2011 2012 2013 2014 2015 2016
Source: IDC, June 2013
Page 4
Storage Infrastructure Spending
Page 5
Scale-out Object Storage
▐ Object Storage
 A storage architecture that manages data as objects, as opposed to other
storage architectures like file systems which manages data as a file
hierarchy and block storage which manages data as blocks within sectors
and tracks
 Object storage systems allow relatively inexpensive, scalable and selfhealing retention of massive amounts of unstructured data.
Source: Wikipedia, April 2014
Page 6
Legacy Solutions – Scalability Limitations
▐ Inadequate scalability of
capacity & performance
 Cannot scale performance to
keep up with data growth
 Multiple products with different
architectures
 More siloed capacity to manage
▐ Limited deduplication scope
 Limited scalability proliferates
duplicate data across appliances
 Lower deduplication ratio for
large environments
Page 7
Local vs. Global Deduplication
▐ Single deduplication repository across entire solution
▐ Data deduplication across ALL data from ALL node
 Cross-node deduplication for greater efficiency
 Cross application deduplication leveraging application-aware deduplication
Page 8
Legacy Solutions – Resiliency Limitations
Day 1: Full
Day 2:
Day 3:
Incremental Incremental
…Day 7: Full
1 7 1 4
1 6
5 1
1 6 1 4
4 6
6 3
4 7
1 6 7 8
2 1
Q: What data
can be restored
if block #1 lost?
A: NONE!
1 2 3 4
5 6 7 8
Traditional RAID is not sufficient for deduplicated data
Page 9
Scale-out Scalable Grid Storage Architecture
Community of Smart Nodes
Nodes
• Industry-standard servers
Accelerator Nodes
Hybrid Nodes
• Multiple types allowed
• Heterogeneous & open
Storage Nodes
Unrestricted Scalability
Intelligent Management SW
• Fully distributed system
• PERFORMANCE SCALABILITY
• CAPACITY SCALABILITY
Page 10
• Self-aware & self-organizing
• Data management services
• Virtualizes hardware platform
Adaptive Grid Storage For Long-Term Data
Online Upgrade/Expansion with Multi-generation Nodes
Non-disruptive
Remove
Non-disruptive Add/Upgrade
V2 Grid
+
V3
+
V4
+
Vx
= 1 System
▐ Enable in-place technology refresh with no data migration
▐ Ever greener storage with faster, denser components
▐ Enable continuous data availability
▐ Reduce CapEx and OpEx with deduplication
▐ Non-disruptive scaling from dynamic auto provisioning storage
Page 11
Hands-Free Management
▐ Simple, fast deployment
 < 45 minutes to backup & archive
▐ Self-discovering capacity
 No storage provisioning
 No tape emulation tasks
▐ Self-tuning and Resource Management
 Optimized performance & capacity
▐ Self-healing
 Automatic recovery across resources
▐ Web-browser GUI
 Monitoring and Planning
Page 12
Advanced Erasure-Coded Data Resiliency
▐ “User dialable” disk/node protection
 Default protection against 3 concurrent failures
 Dynamically allocated Intermix of multiple
resiliency levels (1-6) for different applications
▐ Greater protection with lower overhead
 Default setting: 25% capacity overhead
 1.5x greater protection than traditional RAID 6
with lower overhead and faster recovery
 No idle spare drives
▐ Faster self-healing with less performance
degradation
 Only data is reconstructed rather than entire drive
 Data is reconstructed across multiple spindles
Page 13
Lab Benchmark Test
Page 14
Scale-out vs. Scale-up Data Deduplication
Controller
Shelf
Page 15
Shelf
Shelf
AN
AN
Shelf
SN
SN
SN
SN
▐ Single or Multi-Controller
▐ Modular scale-out front-end
▐ Fixed maximum throughput
▐ Scalable maximum throughput
▐ Scalability limited by controller
physical capabilities
▐ Scalability independent of physical
capabilities with linear performance
Scale-out Inline Global Data Deduplication
▐ Distributed Two-Tier Architecture
 Independent linear scalability of
performance & capacity
AN
AN
▐ Global Deduplication
 Data deduplication across ALL
data from ALL nodes
SN
SN
SN
▐ Distributed Hash Table
 Data routed to responsible
Storage Node
 Deduplication & hash table
processing scales linearly with
Storage Nodes
Prevents silos of deduped data
Page 16
SN
Linear Performance Scalability
Page 17
Scale-out Deduplication Performance
Page 18
Application Metadata Impact
Clients’ Files
Agent Operation
File Aggregation (tar)
Blocking
Backup Server
Storage Media
Metadata
Filtering
▐ Application metadata makes user data appear different
▐ Inserted metadata reduces deduplication efficiency
Page 19
Application-Aware Deduplication
Capacity Optimization through Enhanced Deduplication
Data (Bytes)
Generic
Dedupe
Application-Aware
Dedupe
Time (Weeks)
Original Data
Generic Dedupe
Application-Aware Dedupe
▐ Application-aware deduplication leverages format awareness to filter metadata
inserted by the application and deduplicate the data payload separately
▐ Application-Awareness can increase Reduction Ratio by 130% or more
Page 20
Disaster Recovery and Cloud
WAN-optimized Replication
Site A
Geo-Distributed Grid
Site B
Replication
Site A
Site C
Site B
Page
21 21
WAN-Optimized Replication
Accelerator Nodes
Storage Nodes
Many to one replication
Many to many replication
▐ Asynchronous grid-to-grid WAN-optimized replication for DR
▐ Deduplication across all replicated HYDRAstor grids
 Minimizes network bandwidth requirements
 Minimizes DR site capacity requirements
▐ Policy-based data selection – File System Granularity
▐ In-flight encryption
Page 22
Customer Configuration Example
▐ Replication across primary and secondary datacenter grid systems
▐ Replication from remote sites within the U.S., and across the Atlantic
and the Pacific
Page 23
HYDRAstor Gen-4 Family
Performance
Grid Model
HS3-410
802TB/hr, 1,040TB/hr (OST)
7,920TB Raw
103PB Effective
9.7TB/hr, 12.6TB/hr (OST)
192TB Raw
HS8-4006-720
2.5PB Effective
96TB Raw
1.2PB Effective
720TB Raw
9.4PB Effective
HS8-4002-96
Single Node
Model
HS8-4002-192
HS8-4165-7920
HS8-4001
Node Building Blocks
12-48TB Raw
156-624TB Effective
8-24TB Raw
104-312TB Effective
Hybrid Node
Storage Node
HS8-4001-96
96TB Raw
1.2PB Effective
Page 24
Capacity
Common Code Base and Functionality
▐ Common code/features and modular scalability across models
▐ Intermix of multi-generation nodes in the same grids
▐ All Software Features supported for entire product line









DRD™ protection – Advanced erasure-coded data resiliency
DataRedux™ – Inline application-aware global data deduplication and compression
Cloning/Snapshot – Instant fully deduplicated file system or file R/W copy
Dynamic Data Shredding – Data shredding for deleted classified data
AN Failover – Front-end failover for High Availability
RepliGrid™ (Option) – WAN-optimized replication with in-flight encryption
HYDRAlock™ (Option) – WORM file system functionality
Encryption at Rest (Option) – Encryption to protect data at rest
HYDRAstor OpenStorage Suite (Options)
•
•
•
•
Page 25
Express I/O – Lightweight data transport for high throughput
Dynamic I/O – Adaptive I/O load balancing across nodes
Optimized Copy – WAN-optimized copy services
Optimized Synthetics – Storage-synthesized full backups
Scale-out Storage for Long-Term Data
1 PB/hr
Page 26
100 PB
Performance
Potential Enhancement Directions
Functionality
Page
Page27
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ITPG-CTG CYQ1 QBR

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