VMware + SolidFireDeliver Predictable Application Performance & Improve Infrastructure Efficiency

Aaron Delp, Cloud Solutions Architect

▪ 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

Intro to SolidFire(Short Version)

The SolidFire SolutionScale-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

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

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

Otherall-flash arrays

only solve for performance

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

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

Cap

acity

Linear ScalabilityStarter 5 node SF9010 configuration

5, SF9010 Nodes 174 TB 375,000 IOPS

Scale-Out Architecture

Scale beyond 100TB

In-line Data Reduction

Shared Nothing HA

Guaranteed Performance

Automated Management

All Flash Storage

All Flash Arrays Are Not Created Equal…

Workload ConsolidationMultiple Mission Critical Applications on the Same Storage System

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

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

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

Enabling Delivery of all Applications from a Single Storage Infrastructure

Scale-Out ArchitectureGuaranteed PerformanceFully automatedBelow $3/GB

VDI

Integrated End-to-End QoSVMware SIOC + SolidFire QoS = Predictable Performance

Hypervisor-based QoS? (SIOC)

Tries to achieve “fairness” between VMsAddresses 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

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

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

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

▪ 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

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

End-to-End QoS Demo

Eliminate VM Sprawl & Wasted Resources

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

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

15TBRaw

15TBHelix DP

Thin Provisioning

Effective Capacity

15TBHelix DP

Compression

Effective Capacity15TBHelix DP

De-duplication

Effective Capacity15TBHelix DP

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

Operational Efficiency (compares 173TB of effective capacity)

Reduce rack space Consume less power And increase performance

52,000 IOPS

375,000 IOPS

Questions?

▪ 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