This document discusses running tier 1 applications in the cloud. It begins with introductions of the presenters, Mark Thomas from Databarracks and Dave Wright from SolidFire. Common issues with running tier 1 apps in cloud include lack of vendor support, performance concerns, unknown storage impacts, and security perceptions. Solutions discussed include reserving compute and storage resources through techniques like ring fencing, disk reservation, and auto tiering. The document advocates re-engineering apps for cloud and leveraging a provider like Databarracks that uses SolidFire storage, which guarantees performance through quality of service functions at a per-volume level. This allows dedicating resources on a per-client basis to address noisy neighbor effects and provide visibility into input/output

1. How to run tier 1 applications in the cloud
Cloud Expo Europe 2013
Slides @ http://www.slideshare.net/SolidFireInc
Mark Thomas - Solutions Architect
Dave Wright – Founder / CEO
@jungledave

2. Introduction
Mark Thomas, Solutions Architect, Databarracks
 IT Consultant for 14 years
 Working with virtualisation since 2002 (ESX 1.5)
 Working with cloud services since 2009
 Worked for VirtualizeIT for 10 years – Consultant / Manager / Director
 One of first VAC partners in UK
 Production systems primarily from day one
 Worked for Virtustream for 3 ½ years – Manager and Director
 One of first specific cloud providers formed for that purpose
 Gartner Magic Quadrant for IaaS
Dave Wright, Founder / CEO, SolidFire
• Left Stanford University in 1998 to help start GameSpy Industries
• GameSpy merged with IGN Entertainment as Chief Architect
• Founded Jungle Disk in 2007, sold to Rackspace in 2008
• Founded SolidFire in 2009 after experiencing the difficulties of high-
performance cloud storage

3. About Databarracks
 A decade of experience in cloud computing
 True managed services
 Focussed on security and support
 Certified
 Backup to disaster recovery to Infrastructure as a Service
 Cloud Integrators
 Cloud Industry Forum Members

4. Our customers

5. Our customers
Brazil
USA
Peru
RSA
Canada
Australia
India
China
Russia
Norway
Poland
Singapore
Italy
UK
UAE
Spain
Germany
Thailand
Hong Kong
SWZ
Greece

6. The problems

7. Common issues for tier 1 applications
 Vendor / ISV support
 Vendors say they don’t support virtual /cloud systems
 Providers struggle to understand the complexities of tier 1 applications in these environments
 Perception that performance is worse in a consolidated / multi-tenant
environment
 Assumptions that hypervisors add an overhead and don’t perform as well as physical
 Assumes all systems are many-to-one
 Lack of understanding of cloud about resource SLA’s
 Storage is an ‘unknown’ at provider and is key
 WAN impact on performance
 Moving systems away from local introduces latency to sensitive systems
 Cost and reliability of links
 It’s not secure enough
 View that multi-tenant clouds are not secure enough to host tier 1 data

8. The noisy neighbour
 A VM or VMs consuming all the resource
OVER TIME
RESOURCESCONSUMED
BASELINE CAPACITY
BEYOND CAPACITY
x
x
x
x
VM operate within configured resources. Actual
physical resource allocated by virtualisation
administrator
As total of all VM resources grows above the
total physical capacity. Additional resources
are required to satisfy demand or adjusting
VM setting to compensate. Performance
issues potentially but easy to manage
100%
0%
100%100%100%
0%0%0%
50%
100%
OVER TIME
CLIENT A

9. The noisy neighbour: worse in multi-tenancy?
 Same as before but now with multiple customers, whose VMs get adjusted?
OVER TIME
RESOURCESCONSUMED
BASELINE CAPACITY
BEYOND CAPACITY
x
x
x
x
VMs operate within configured
resources. Actual physical resource
allocated by service provider service
and clients commitment
Service provider managed maximum physical
resources. Service provider dictates
potentially how conflict situations are
resolved. Not always visible to clients
100%
0%
100%100%100%
0%0%0%
50%
100%
CLIENT A CLIENT B

10. The common solutions

11. Compute ring-fencing
 Reserving compute
 Ensure application profiling identifies resource requirements and sensitivity
 Treat as you would a physical system / your own virtualisation
 Ensure your service provider understands your environment and has associated services to
support your migration
 Dedicating physical compute
 For things that don’t fit the provider’s shared platform
 Not as efficient, pay for all physical resources
 Customer owned or fully managed?

12. Storage disk reservation
 Dedicating disk to provide write IO performance
 Cost of IO / capacity is a problem
 Not really cloud storage
Physical Disks
Physical SAN
Client Volumes
Client DClients A-C
Clients A-C
share a set of
disks. Client D
has dedicated
Both disk pools
have the same
number and
type of disks.
Same IO but
different usage

13. Storage auto tiering
 Hides IO issues with SSD / fast disk for hot blocks
 Hard to control who uses what and charge back
Physical Disks
Physical SAN
Client Volumes
Blocks move
as accessed
Disk pool with
two or more
types of disk.
Normally less in
fast Tier
Standard TierFast Tier
A B C
A B C
A B C
A B C
Blocks

14. Re-engineer for the cloud
 Businesses should evaluate the benefits of doing things differently
 Applications that can be web enabled should be
 Consider re-developing applications using cloud platforms for scalability and performance
 Running applications from remote data centres is not new, architect the same way
 Look at changing data access to optimise the traffic (move all services together, move client
desktops close to servers)
 Leverage good service provider’s knowledge
 Should have good SLA’s for resources
 Should be able to understand Enterprise applications not just web scale
 Should have options for optimising your environment (resource reallocation, tiers)
 Should offer complimentary services such as WAN optimization / remote desktops etc. to
support the re-architecture

15. Databarracks and SolidFire
address the key IO issue

16. How we address the IO Issue
 Storage for tier 1 applications can be placed on
SolidFire storage for IO SLA’s
 Each client has their own logical volume
separation for performance monitoring and
security segregation
 Each client has their own dedicated datastores to
leverage hypervisor level IO optimisations if
required

17. Customer IO visibility for tier 1
 Price per capacity (included IOPS per GB), IO increase (priced per IO)
 Customers can see volume IO setting via the Databarracks Service Portal
 Customers can specify IOP requirements in the portal

18. The Noisy
Neighbor Effect
• Few resource hungry
applications
negatively affect all
other volume
performance
Traditional Multi-Tenant
Performance
Noisy Neighbor

19. The Cloud
Needs Better
Storage
Performance
• Unable to manage performance independent of
capacity
• Can not guarantee storage performance
Efficiency
• Low and inefficient utilization rates
• Lack of high performance in-line data reduction
Management
• Complex, manual, lacks automation
Scale
• Limited scalability of both capacity and
performance
• Manage multiple islands of storage

20. Key Differentiators
Cloud
Scalability
Simultaneous scaling of both
capacity and performance
Guaranteed Quality
of Service (QoS)
Fine-grain performance
management on a per volume
basis
In-line
efficiency
In-line data reduction and
85% utilization requires less
purchased capacity
Complete
automation
REST-based API for
complete control

21. SolidFire QoS
in Practice
• Applications allocated
into performance tiers
• Changes are immediate
can be made on the fly
Traditional Multi-Tenant
Performance
Application of SolidFire
QoS controls

22. Key
Requirements
for running all
Tier 1 apps in
the cloud.
• All-SSD Architecture
• Quality of Service functionality that
guarantees application storage
performance
• Firm performance based SLAs

23. Questions?
Mark.Thomas@databarracks.com
@databarracks.com
www.databarracks.com
Dave@solidfire.com
@jungledave
www.solidfire.com