VMUGIT User Conference 2014 A New Era of Server Side Storage Frank Denneman, PernixData

1. Frank Denneman
Tech Evangelist
A new era of server side
storage

2. Agenda
 History
 PernixData FVP
 Scaling your performance architecture
 Restructuring data flows
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3. PernixData
 Founded in 2012 by virtualization experts
 Poojan Kumar, Oracle Exadata Co-founder
 Satyam Vaghani, VMware VMFS, VAAI, PSA founder
 Strong virtualization and storage experience
 VMware, EMC, Google, NetApp and many others…
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4. A little bit of a personal history
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ESX
ESX
ESX
ESX
ESX Cluster
DBServer
DBServer
Ethernet
Switch
SAN
switch
Ethernet
Switch
SAN
switch
Ethernet
Switch
DB Server

5. Success! Virtual Machine sprawl
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ESX
ESX
ESX
ESX
ESX
ESX
ESX
ESX
ESX Cluster
Oracle
Standard
Cluster
Oracle
EnterpriseClusterStratixCluster
Ethernet
Switch
SAN
switch
Ethernet
Switch
SAN
switch
Ethernet
Switch
More
Bandwidth
More
Spindles
New SAN
Directors

6. Datacenter(1 Datacenter(2
Double the fun, twice the excitement!
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7. Every day felt like a star trek episode
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8. Problems are still present today
 Distance from workload to resource
 Shared environment
 Loss of VM identity
 Resulting in non-deterministic performance
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9. Flash – Saviour of the Universe
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10. Flash placement is context sensitive
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11. Location of flash
 Flash in array = better data services
 Flash in server = better performance
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12. Taking the scenic route
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Image courtesy of Chad Sakac

13. Static server side flash?
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14. PernixData FVP
Architecture overview
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15. Decouple storage performance from capacity
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VMVM VM VMVM VMVM
FVP
ESXi Host
Flash Device
ESXi Host
Flash Device
ESXi Host
Flash Device
Storage Array
VM VM
Performance
Capacity
+
Data services
Read & write acceleration of any VM workload

16. PernixData FVP clustered Platform
 Hypervisor-based non-disruptive data acceleration
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17. Supports mobility at scale
 Server flash aggregation into cluster-wide pool
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ESXi Host
Flash
Device
ESXi Host
Flash
Device
VM
Remote flash access
FVP
Migration VM
Read
Storage System
(DRS)
Data

18. Platform, not a point solution
 Fault tolerant write acceleration
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19. Tech Preview: Topology aware FVP
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 But how about failure domains?
Flash
Device
ESXi Host 1
Acceleration
Resource
ESXi Host 2 ESXi Host 4ESXi Host 3
FVP
Flash
Device
ESXi Host 2
Flash
Device
ESXi Host 3
Flash
Device
ESXi Host 4
vSphere cluster
VM
data RWD
Replica write data

20. Topology aware FVP
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 What if your vSphere cluster spans multiple blade centers?
 Or multiple sites?

21. Topology aware FVP
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 Align FVP clusters to fault domains with replica groups
 Control replica placement

22. Tech Preview: Hello, I am FVP with DFTM
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23. Distributed Fault Tolerant Memory
 Historic point: FVP fault tolerance makes volatile
memory part of storage for the first time ever
 Timing: Recent chipset advances make it right for most
workloads
 Other facts about FVP with DFTM:
 Supports all FVP features and workloads
 1TB RAM per host up to max vSphere cluster size
 A FVP Cluster can mix RAM, Flash, MCS, etc
 Ability to hot-expand and hot-shrink RAM usage per host
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24. Scaling your
performance
architecture
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25. Future proof scale out architecture
 Non disruptive performance scale out
 Linked Compute + Storage performance growth
 Future proof: new tech instantly usable
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26. Deterministic performance layer
 Using point to point connections of Ethernet network
 I/O remain in performance layer
 Reduced load on SAN beneficial to all workloads
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27. Tech Preview:
Adaptive network compression
 Narrows latency/throughput chasm between local and
remote FVP media
 Adaptive
 Real-time
 Low CPU cost
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64k, 2w*4oio, 100% seq wr

28. Penalty-less fault tolerance
 Independent of 1GbE or 10GbE
 Jetstress shows similar results
 32k DBR, 36k DBW, 11k logW, 256k background RW
 WB + 0 = 15048 transactional IOPS
 WB + 1, 1GbE compressed = 13548 transactional IOPS
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64k, 2w*4oio, 100% seq wr
WB + 0
2700 IOPS
WB + 1
1GbE
1700 IOPS
WB + 1
1GbE compressed
2700 IOPS

29. Customer success story
 Issue: 10 TB of space available, still suffering from poor
SQL performance
 PernixData FVP Results
 94% lower average latency (30ms to 1.7ms)
 12x more IOPS (compared to just storage array)
 25,000,000+ IOs offloaded from storage array in 2 days!
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30. Restructuring
Data flows
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31. Absorbing (write) I/O’s
 Managing I/O streams
 Be aware: FVP does not change amount of write Ios
 Changing I/O pattern to smooth out writes
 Time release I/O’s
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32. Say hello to your new worst-case scenario
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33. Next steps
 Get some flash
 Download the trial: pernixdata.com/trail
 Start accelerating workload
 No budget for flash or just want more?
Enter to win Kingston Enterprise drive
 pernixdata.com/flash
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34. Thanks!
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Follow us on twitter: @PernixData | @FrankDenneman