Flash storage solves the problem of application I/O wait time; Pepperl+Fuchs consolidates applications and databases on a single flash storage platform

1. What is the real cost of User IO Wait?
Rob Bloemendal, Director Consultancy Engineering EMEA
November 20th, 2012
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2. Agenda
 Violin Memory company overview
 Why did Pepperl+Fuchs chose Violin Memory
 The real cost of application user I/O wait – Flash Storage
 Other real user case of application I/O wait
 Q&A
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3. The Violin Memory Company
• Founded 2005, first flash product in 2009
• 200+ top tier customers
• Toshiba investor/ Strategic Supply &
Roadmap Agreement
• Global Presence
– WW HQ in Silicon Valley USA, Offices in North
America, EMEA and APAC
– 450+ employees
• August 2011 - awarded Silicon Valley
„Company of the Year‟
– Previous winners –
Google, Salesforce.com, YouTube, Twitter, MySQL
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4. Run your business faster & more efficiently with Violin
• Accelerate your business critical applications
– 5x – 10x improvement in performance and latency
– 2x – 10x more users for the same infrastructure
– Survive business spikes without disruptions
• Lower your infrastructure and operational costs
– Physical consolidation of 10:1
– Software licensing reduction up to 50%
– Sub 12-month ROI
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6. Pepperl+Fuchs
 Applications: Siebel CRM & Witron SCM
 Challenge: Performance (Traditional Storage Systems)
 Requirement:
‒ Application Acceleration
‒ Consolidating applications and databases on one storage platform
‒ VMware virtualisation without impacting the performance of other applications
 Strategy:
‒ Being able to do more without falling in the same trap
‒ Scalability and Performance issues in the next couple of years to be avoided
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7. Pepperl+Fuchs options:
 Exadata:
‒ Pricing very high
‒ Alternative required
 Violin Memory:
‒ Chosen alternative
 Approach:
‒ Proof of Concept with both products
‒ Rule: no database or application tuning
‒ Result: Violin Memory best on price versus performance ratio
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8. Current infrastructure
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9. Why Violin Memory?
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10. What if you could have so much resource…
It was more than you could actually use?
It was no longer constrained?
What if I/O were free?
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11. Tuning Techniques Used
Time Consuming Expensive Short Term
Application I/O wait times are still high
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12. Disk Storage – Constant Constraint
• To avoid disk performance
Underneath, it’s still strategies
issues, mitigation a disk…
must be used, such as:
– Short Stroking
– RAID (100‟s of options)
– Over Provisioning
– Quality of Service policies
– Resource Management
– Storage Tiering (Automatic!)
– Complex Buffering and Caching Algorithms
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13. Flash Application Goals
• Increase Agility
– Real Time Data
– React faster Less Less
– Increase productivity Cost Risk
More
• Reduce Cost Agility
– Do more with existing infrastructure
– Lower operational costs
– Reduce software licensing costs
• Reduce Risk
– Exceed SLAs
– Meet exceptional demands
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14. The Flash Application Journey
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15. The Technology Language Barrier
 In the I.T. industry each area of specialism has its own terminology
‒ Consider a simple performance issue:
Application User says “system is slow”
Database Database Administrator says “wait time is high”
Server OS Admin says system has “high IOWAIT”
Storage Storage Admin says “latency is high”
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16. Translating “Storage” Into “Application”
Application
Scalability
Application Batch
Acceleration Throughput
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17. Latency – The Application Stealth Tax
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18. Latency – The Application Stealth Tax
 Calls to and from storage require the calling application to wait
 The time spent waiting is the latency of the storage – it is lost time
CPU: BUSY I/O
WAIT BUSY I/O
WAIT BUSY
DISK:
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19. Lost Application Time
 This time is lost for every I/O call… for every user…
 Busy applications perform millions of I/Os per hour
CPU: BUSY WAIT BUSY WAIT BUSY
Lost Application Time
DISK: I/O I/O
Sum of Latency
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20. Flash Memory – Ultra Low Latency
 With flash memory I/O calls are orders of magnitude faster
 Time spent waiting for storage is dramatically reduced
W W
CPU: BUSY A
I
T
BUSY A
I
T
BUSY
Increased
CPU
Efficiency
I I
FLASH: /
O
/
O
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21. IOPS – The Application Ceiling
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22. IOPS – The Application Ceiling
 IOPS are needed for scaling applications
‒ Increasing users or volume of data, adding modules etc
 At higher IOPS, response times increase
‒ Legacy disk systems have unpredictable performance
In application language:
1. Storage systems have an upper limit
2. The busier the system, the slower the response
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23. Sustained Performance
14000
 Disk arrays behave 12000 Flash Disk
unpredictably under load 10000
Latency
 Disk latency increases
8000
6000
exponentially
4000
 Violin flash memory
2000
latency has a linear
0
increase under load 0 10,000 20,000 30,000 40,000
IOPS 50,000 60,000 70,000
Violin provides applications with predictable performance
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24. Flash versus Disk
 A typical 15k RPM SAS disk can service
around 200 IOPS
 A Violin 6616 flash memory array can
service 1,000,000 IOPS
 This is 5000x more in a single 3U unit
 The equivalent disk array would fill a data
centre and require huge amounts of power
and cooling
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25. Bandwidth – Application Throughput
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26. Application Throughput
 Bandwidth describes the volume
of data that can be delivered to
and from a storage system
 In the application world this is
critical for batch processing
 Applications which regularly process large amounts of data require
bandwidth in order to complete processing within the batch window
 As data volumes grow this becomes more difficult
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27. Batch Windows 8am Monday
Start of online day
Friday Saturday Sunday Monday
 Windows are used to schedule batch runs for times when users will not
be affected, e.g. nights, weekends etc
Why Reduce Batch Windows?
‒ Overrunning into the next window has serious consequences
‒ Users Protection from overrunning batchor batch job may have to be
Risk: could experience bad performance jobs
cancelled
‒ Processing could fall behindrun additional to become stale
Agility: Process more data, causing data jobs
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28. Some other examples
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29. With Disk Storage - SAP BW
 8 CPUs
 Oracle 11.2.0.2.0
 Non-ASM
 HDS Disk Storage
 20k SAP processes
 SVC - IBM
 VMWARE
 Sync Replication
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30. With Flash Storage - SAP BW
 20 CPUs
 Oracle 11.2.0.2.0
 Non-ASM
 40k SAP processes
 SVC - IBM
 VMWARE
 Sync Replication
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31. Before Violin - SAP SCM
 Oracle 11.2.0.2
 Non-ASM
 2 x HP XP12K SAN
 Avg. Random I/O 7ms
 Avg. Direct Path Reads 22ms
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32. Violin Final Test - SAP SCM
 Oracle Version: 11.2.0.2
 SAP BC/BC-
MID/PP/QM/Specifics
 Non-ASM
 2 x VMA 3205 (mirrored)
• Avg. Random I/O latency 500µs
• Avg. Direct Path Read I/O latency 1ms
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33. Summary
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34. Application Journey – The way forward
Legacy Accelerated Consolidated Virtualised
Constrained Unleashed Shared Private Cloud
• Isolated Applications • Simple To Deploy • Lower Operating Costs • Highest Cost Savings
• Complex and Slow • Increased Productivity • Reduced Complexity • Self-Service
• Disparate Platforms • Maximise ROI • Higher Service Levels • Increased Agility
• Difficult To Manage • Exceed SLAs • Reduced License Cost • Reduced Complexity
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35. What If………..
• You could remove the I/O constraint from
your infrastructure?
• You could reduce the application wait time
by 5x – 10x?
• You could accelerate the performance of
your mission critical IT applications by
5x – 10x?
• You could reduce the Total Cost of
Ownership by 70%?
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36. Customer Quote
Helmut Eckstein, Manager Global IT/SIS, Pepperl+Fuchs:
“This is a fast and stable system, we have been running it now for
more than a year and we haven’t had any disruption or any break.
The performance is still unbelievable”
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37. Thank you
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