Learn how to simplify management and guarantee application performance through the unique combination of vSphere and SolidFire. - Consolidation of multiple mission critical applications on the same storage system - Integrated End-to-End Quality of Service allocation using VMware's SIOC settings to eliminate inconsistent performance - Eliminate VM sprawl and the need to over-provision storage, allowing you to deploy more VMs on the same infrastructure

2. VMware + SolidFire
Deliver Predictable Application Performance & Improve Infrastructure Efficiency
Aaron Delp, Cloud Solutions Architect

3. ▪ Intro to SolidFire (Short Version)
▪ Consolidation of Multiple Mission Critical Applications
▪ Integrated End-to-End Quality of Service (QoS)
▪ End-to-End QoS Demo
▪ Eliminate VM Sprawl & Wasted Resources
Agenda

4. Intro to SolidFire
(Short Version)

5. The SolidFire Solution
Scale-out high performance storage systems
designed for large scale infrastructure
 Most Scalable All-Flash storage system
 5 – 100 nodes, 60TB – 3.4PB, 7.5M IOPS
 Industry-standard hardware, 10 GigE iSCSI
 20X performance of traditional SANs
 Most complete enterprise feature set of any AFA
 10x reduction in operational cost
 Delivered below $3/GB

6.  Deploy new applications and capabilities faster
 Provide more agile and scalable infrastructure
 Increase application performance and predictability
 Enable automation and end-user self-service
 Raise operational efficiency and reduce cost
Enterprise IT
lacks storage
agility, and is
under significant
pressure

7.  Deploy new applications and capabilities faster
 Provide more agile and scalable infrastructure
 Increase application performance and predictability
 Enable automation and end-user self-service
 Raise operational efficiency and reduce cost
Other
all-flash arrays
only solve for
performance

8.  Deploy new applications and capabilities faster
 Provide more agile and scalable infrastructure
 Increase application performance and predictability
 Enable automation and end-user self-service
 Raise operational efficiency and reduce cost
SolidFire
solves for the
Next Generation
Data Center

9. Scale-Out Architecture
 New nodes are added as demand dictates
 Performance and capacity instantly available to all volumes
 Nodes added on the fly without down time
174 TB
207 TB
241 TB
275 TB
375,000 IOPS
450,000 IOPS
525,000 IOPS
600,000 IOPS
Performance
Capacity
Linear ScalabilityStarter 5 node SF9010 configuration
5, SF9010 Nodes
 174 TB
 375,000 IOPS

10. Scale-Out
Architecture

11. Scale beyond 100TB
In-line Data Reduction
Shared Nothing HA
Guaranteed Performance
Automated Management
All Flash Storage
All Flash Arrays Are
Not Created Equal…

12. Workload Consolidation
Multiple Mission Critical Applications on the Same Storage System

13. One of the major
problems we are
solving for…
Noisy Neighbors!
A few resource (IO)
hungry applications
negatively affect all
other’s performance
Traditional Multi-Tenant
Performance
Noisy Neighbor

14. Eliminating Noisy Neighbors with QoS
The Noisy Neighbor Effect
 Individual tenant impacts other applications
 Unsuitable for performance sensitive apps
SolidFire QoS in Practice
 Create fine-grained tiers of performance
 Application performance is isolated
 Performance SLAs enforced
Noisy Neighbor
Performance 0
Performance 1
Performance 2
Performance 3
Decreased
Performance

15. Performance Virtualization: Unified
global pools of capacity and performance
 Allocate: Storage performance
independent of capacity
 Manage: Performance real-time without
impacting other volumes
 Guarantee: Performance to every volume
with fine-grain QoS settings
Guaranteed Performance - QoS

16. Enabling Delivery of all Applications
from a Single Storage Infrastructure
Scale-Out Architecture
Guaranteed Performance
Fully automated
Below $3/GB
VDI

17. Integrated End-to-End QoS
VMware SIOC + SolidFire QoS = Predictable Performance

18. Hypervisor-based QoS? (SIOC)
Tries to achieve “fairness” between VMs
Addresses some of the performance
variability of VMs
But assumes that storage is
 consistent
 never fails
 is not used by anything else
An environment that depends on predictable performance demands a
more coordinated approach across host & storage resources

19. Lack of control A hypervisor can
 Throttle IO
 Prioritize IO in its own queue
But a hypervisor cannot
 Control or maintaining the total IO pool available or make
more IO available
 Force the storage system to deliver a specific level of
performance
Any OS or hypervisor will always be at the mercy of
the storage device abilities and state

20. Performance
Degradation
The hypervisor does not know the cause of
performance degradation. Is it:
 A noisy neighbor?
 A failure condition?
 A maintenance in process?
 Resources removed or added to the storage?
SIOC’s response is to turn up the volume (queue) on
high priority apps & drown out the noisy neighbor
 Could make the problem much worse
 Hopefully the degradation cause is not actually a higher
priority
 Hopefully two independent SIOC decisions are never made
As storage system utilization increases performance
degradation becomes a larger concern

21. Inability to set
and guarantee
minimum level of
performance
 It’s easy to cap or prioritize
performance
 But a lot can get lost in
translation?
 SIOC Priority? Shares?
 Apps and tenants need a
minimum level of
performance articulated in a
meaningful way
 IOPS, BW, and Latency

22. ▪ Consolidate all use cases (e.g. cloud infrastructure, VDI, virtualized apps) with confidence
▪ SIOC with storage enforced QoS ensures predictable performance to each VM
▪ Automated, dynamic performance allocation to every datastore
End-to-End QoS

23. VM QoSDatastore QoS (Tiering)Volume QoS
 QoS managed per
SolidFire Volume
 Non-SIOC enabled
environments
 QoS managed per
vSphere datastore
 Configure SIOC defaults
per datastore
 Manage hundred’s to
thousand’s of VM’s
without setting SIOC per
VM
 Storage vMotion to
change performance
 QoS managed per VM
 Configure SIOC per
VM
 Granular flexibility
regardless of
datastore location to
manage individual
VM’s
 Edit VM settings to
change performance
Flexible & Powerful Performance Control Options

24. End-to-End QoS Demo

25. Eliminate VM Sprawl &
Wasted Resources

26. Forced Over-
Provisioning
Trying to stay away from degradation many are
forced to massively over-provision
 Only way on most systems to ensure a large enough
IOPS pool with no contention
 Underutilization kills economics of shared storage
environment.
 What is your usable $/GB factoring in underutilization?
 Not uncommon to find SANs dedicated to an app

27. Always On,
In-Line Efficiency
 All data is compressed, de-duplicated
and thin provisioned
 Accomplished without any performance
impact
 Part of system architecture,
not bolt-on feature
 Operational Expense reduction in
addition to Capital Expense reduction
30TB 60TB 90TB 120TB
Provisioned
Purchase
15TB
Raw
15TB
Helix
DP
Thin Provisioning
Effective
Capacity
15TB
Helix
DP
Compression
Effective Capacity
15TB
Helix
DP
De-duplication
Effective Capacity
15TB
Helix
DP

28. Snapshots & Clones
Efficient versioning
 Deduplicated and compressed in-line
 Maximizing capacity
 Minimizing network traffic
Enhancing durability and availability
 Any snapshot can be cloned
 As a separate mountable, deduplicated volume
 As a real-time backup to another any Swift or S3
API compatible target

29. Operational Efficiency (compares 173TB of effective capacity)
 Reduce rack space
 Consume less power
 And increase performance
52,000 IOPS
375,000 IOPS

30. Questions?

31. ▪ Intro to SolidFire (Short Version)
▪ Consolidation of Multiple Mission Critical Applications
▪ Integrated End-to-End Quality of Service
▪ End-to-End QoS Demo
▪ Eliminate VM Sprawl & Wasted Resources
More Information: solidfire.com/vmware