1. DriveScale End User Sales Presentation
Software Defined Infrastructure for Hadoop and Big Data
DriveScale End User Sales Presentation
April 24, 2017

2. Presentation Overview
The Market Problem
How DriveScale Solves the Problem
SDI = Software Defined Infrastructure for Big Data
Benefits of Software Defined Infrastructure
Solution Overview & Components
©2017 DriveScale Inc. All Rights Reserved.

3. Example Meeting Agenda
Presenter
Role
Topic
Time
John Doe
Jane X
Customer - VP Infrastructure
VAR – Account Manager
Meeting Kickoff 10
Ryan Shorter
Jeff Chesson
Howard Doherty
DriveScale – Director of Sales Eastern US
DriveScale – Director of Sales Central US
DriveScale – VP Sales
DriveScale Exec Summary and Key Benefits 20
Chris Munford
Salah Chaou
DriveScale - VP Field Operations
DriveScale – Principal Solution Architecut
DriveScale Solution Overview
All
Q&A
©2017 DriveScale Inc. All Rights Reserved.

4. Executive Summary: DriveScale
DriveScale is Software Defined Infrastructure for Hadoop and Big Data
E.g. Spark, Cassandra, NO SQL and other webscale apps
enables the most efficient & agile infrastructure for Private & Hybrid Clouds
Economical– Save up to 60% vs DAS, Centralized NAS/SAN, or Public Cloud. DriveScale brings HyperScale Hadoop Architecture to Enterprise
Efficient – Get more compute and storage from your HW investment. Up to 3x improvement by pooling resources across clusters
Easy – Uses same servers & drives; No changes to SW stack; Managed by Cloudera Director and HWX Cloudbreak; Improved performance vs alternatives – maintains data locality
Ryan to mention that our founders invented Cisco UCS when talking about this slide.

5. The Big Data Market Problem
©2017 DriveScale Inc. All Rights Reserved.

6. The Big Data Market Problem:
How to deploy in a private or hybrid cloud efficiently?
So, in order to alleviate these issues, you decide to move it all in-house and build your own Big Data infrastructure.

7. How to right-size your Big Data Infrastructure?
How Many Clusters?
How Many Server Nodes in each Cluster?
For each Server Node:
How much CPU/cores?
Memory?
Storage/Drives?
How can you change the cluster balance as workloads change?

8. The Problem: You must choose infrastructure FIRST
… before your applications are written (or deployed or scaled or evolved)
Infrastructure
Application
These decisions will determine the success (and cost) of your Big Data plans

9. = = $20,000 The default approach…
Choose a “one size fits all” Server Node
and buy many of them => = =
$20,000
2U servers: The minivans of computing – versatile, but not the best at anything

10. But, One Size Does _not_ Fit All…
Each type of cluster “wants” a different amount of disk per server
Hadoop Data Lake
Dev/Test
Hbase
Kafka
Cassandra …
Fixed silos per cluster type lead to madness
No resource sharing
No elasticity
Too many server types / SKUs

11. You want Choice AND Adaptability
4/256GB
sportscar
cargo plane
CPU/RAM per rack unit
minivan
1/8GB
moped
cargo truck
If you are going to buy a lot of infrastructure, it would be nice to have a mix of choices rather than just minivans.
Sometimes you want all performance and no storage, like a motorcycle
Sometimes you want a lot of performance and just a little storage, like a sportscar
Sometimes you want a balance of performance and storage, like a minvan.
500GB
STORAGE
8 PB 11

12. The RIGHT Solution is Software Defined Infrastructure
Dynamically change your infrastructure to match your application workflow needs
# of clusters
# of server nodes per cluster
# CPUs per server
amount of RAM per server
# disks per server
DriveScale SDI allows you to
Right-Size your Big Data Infrastructure
“You can be wrong and still be right”

13. DriveScale Software Defined Infrastructure Solution Overview
©2017 DriveScale Inc. All Rights Reserved.

14. Software Defined Infrastructure for Big Data
Requires 2 actions:
1) Server Disaggregation, separate servers into
“compute” servers = diskless compute servers
JBODs (just a bunch of drives) = ‘compute-less’ storage servers
2) Logical Server Composition
Join “Compute” with “Storage” to create “logical” servers & clusters
over Ethernet/IP top of rack switch
dynamically change as needs change

15. Step #1: Disaggregate the Servers
Stop buying 2RU Servers with storage
(NOTE: you can still use your existing servers)
2 RU
2 RU
2) Instead, start to buy (a) high density commodity compute servers and (b) JBODs for drive storage
2 RU
1 RU
12 RU
1 RU
2 RU
8 RU
1 RU
2 RU
5 RU
JBOD
(Just A Bunch of Drives)
2 RU
The magic of DriveScale happens in two steps. The first part involves the separation of compute from storage wherein, you can purchase diskless or disk lite servers and simple JBOD’s.
You can now buy compute when you need compute, and storage when you need storage.

16. Step #2: Compose Logical Server Nodes and Clusters
Cluster 1 - Performance - Spark
Node 1
Node 2
Node 3
Node 4
Node 5
Cluster 2 – Storage – Data Lake
Node 1
Node 2
Node 3
Physical Compute Servers
Physical JBODs
(Just a Bunch of Disks)
Then, using DriveScale’s system, you put the lady back together by re-composing the compute with drives in any measures of each as you need for your particular workloads and clusters
“Logical” Server Nodes and Clusters
Right-sized for Big Data / Hadoop

17. Adapt over time as workloads change
Cluster 1 - Performance - Spark
--- Add or Remove Nodes ---
Node 1
Add
Storage
to nodes
Node 2
Node 3
Node 4
Node 5
Cluster 2 – Storage – Data Lake
--- Return Storage to pool ---
Node 1
Node 2
Node 3
Physical Compute Servers
Physical JBODs
(Just a Bunch of Disks)
Then, using DriveScale’s system, you put the lady back together by re-composing the compute with drives in any measures of each as you need for your particular workloads and clusters
“Logical” Server Nodes and Clusters
Right-sized for Big Data / Hadoop

18. Shown another way… Create a third Cluster Z Expand Cluster X
Create a Cluster X
Create another Cluster Y
Shown another way…
So you can create a cluster for one workload…
Then create another for a different workload…
Then expand the first cluster with additional compute and storage resources to accommodate changing workloads..
And Create a third cluster…..and so on.

19. DriveScale scales to 1000s of nodes+ … keep JBOD storage local in each rack
DriveScale Adapter
DriveScale Adapter
DriveScale Adapter
DriveScale Adapter
DriveScale Adapter
Cluster 1
“Balanced”
compute
DriveScale Adapter
DriveScale Adapter
Cluster 2
Storage focus
JBOD
storage
Cluster 3
Compute focus
For small deployments, a cluster can remain in one rack.
For large deployments, you can stripe clusters horizontally across racks, and grow a cluster to thousands of nodes.
In either case, each node has its disk in the same rack and uses untapped top-of-rack switching resources.

20. You just built a private cloud
Now you have a Private Cloud
All hardware resources are shared
DriveScale makes your private data center operate like a public cloud for Hadoop
When you achieve this separation and re-composition capability, nothing in this infrastructure is fixed any more. Every component is part of a truly elastic infrastructure, building blocks waiting for you to put together in any configuration of your choosing. This means that you now have a true ‘Private Cloud’ where all the hardware resources are shared and can be deployed at will.
Your Infrastructure is Highly Elastic

21. Hadoop Storage Options3
Good 2
Fair 1
Poor
Storage Type
DAS
(Direct Attached Storage)
DriveScale
SW Defined
Infrastructure
Centralized
storage
NAS or SAN
Comments
Cost
5-10x
Buy disks, instead of proprietary ‘appliances’, which are 5x to 10x the cost. Don’t waste money on storage features Hadoop doesn’t need (dedup, RAID, erasure encoding, etc.)
Performance
1/2 - 1/4
Give Hadoop nodes direct access to rack local disks, not shared or centralized file systems with limited IO Bandwidth
Utilization
30-50%
Buy only the disks you need, pooled local to the rack. This allows better storage utilization and re-balancing disks across nodes in a cluster gives better CPU utilization, putting more servers to work.
Adaptability
(ability to change node storage)
none
Re-define your server and storage infrastructure as application needs change.
Scalability
anti-hadoop
Give nodes direct access to their own disks. Don’t share file systems (“nothing shared”). 2 3 1 3 3 1 1 3 3 1 3 2 3 3 1

22. Benefits of Software Defined Infrastructure
©2017 DriveScale Inc. All Rights Reserved.

23. DriveScale Target Customers
Big Data Applications – Hadoop, Spark, Cassandra, NoSQL, etc
On-Premise Applications – Private and Hybrid Public Cloud
Concerned about infrastructure costs & wasted spend
Application profiles are dynamic – where infrastructure requirements are hard to predict and always changing
Approaching Power / Rack Space Limits
Want to share infrastructure across multiple applications
Want to buy storage and compute independently (storage or compute bound)

24. DriveScale Target Customers – Common questions/statements
How can I buy compute separate from storage?
I just want to buy more compute, or
I just want to buy more storage
I want to virtualize Hadoop
like AWS does…
How can I increase my utilization?
I want to share storage among server nodes with an NAS (i.e. Isilon)
I need to lower my infrastructure costs
Compared to status quo… Compared to NAS… Compared to Cloud…

25. Benefits of Software Defined Infrastructure to Hadoop Operators#
Benefit
Details 1
Lower Capital Costs
Reduced server costs (don’t have to buy disks)
Buy Less Storage (higher utilization)
Less Rack space needed (more dense CPU and Storage)
Lower Disk cost (3.5” disks cost less than 2.5”) 2
Lower Operational Cost
Add storage without physical labor
Replace failed drives without labor
Less equipment = reduced power 3
Speed up Big Data Deployments
Faster Time to Value
Create new clusters and nodes in minutes instead of weeks
Integrated with Cloudera Director and Horton CloudBreak
Share resources among multiple applications and clusters
The benefits of this system are obvious.
You save significantly in capital expenditure when you look at a 5 year horizon of server+disk purchases. Today, when you refresh your servers, you have to move all the data in them off to some other location, which is a time consuming process. With the DriveScale system, this is no longer necessary.
You have all the levers and knobs you need to move resources to the workloads. Underutilized resources can be taken away from clusters and moved elsewhere. This also therefore means that you need less total hardware than if you were building discrete silos of equipment. That results in costs savings, rack space savings and power savings.
Finally, the tools we provide help you provision clusters in minutes instead of days.

26. (Direct Attached Storage)
Benefits of Software Defined Infrastructure $ Lower Server Costs - Example
before
with DriveScale
2RU Server with DAS
(Direct Attached Storage)
1RU diskless Server
System/CPU/MoBo/NICs
RAM
DISK
$3,065
$1,142
$12,832
$2,063
$1,246
$172
System/CPU/MoBo/NICs
RAM
DISK (1TB for OS)
79.5% savings + +
TOTAL
$17,039
$3,481
TOTAL
Save $13,558 per server node.
x 1000 nodes = $13M 26

27. Benefits of Software Defined Infrastructure $ Lower Disk Costs - Example
before
with DriveScale
2.5” drive DAS
3.5” drive in JBOD
48% savings
$ per 2.5” drive = $0.45/GB
$ per 3.5” drive = $0.22/GB
Save $385 per drive.
Save $192,000 per PetaByte
Also note, the sweet spot for 3.5” drives is 8TB. Dell sells these for their JBOD for $794.40, which is only $0.09/GB,  (8TB 7.2K RPM NLSAS 12Gbps 512e 3.5in Hot-plug Hard Drive [$794.40]) 27 27

28. Per Rack Cost; Commodity Server MFG with and without DriveScale (higher drive utilization)
with DriveScale
2 x
48 port 10GbE switches (ON-4940S)
2 x
48 port 10GbE switches (ON-4940S)
43% Savings
20 x
R730 2RU Servers w/20
2/5” 1.2TB drives each
20 x
R430 1RU Servers
$346,410
Day 1 Cost
(only 2 JBODs)
$198,504
Open RackSpace for more servers
2 x
DriveScale Adaptor
2 x
JBOD w/60
3.5” 2.0TB drives each
240 Terabytes Storage

29. Per Rack Cost; Commodity Server MFG with and without DriveScale (equal storage)
with DriveScale
2 x
48 port 10GbE switches (ON-4940S)
2 x
48 port 10GbE switches (ON-4940S)
20 x
R730 2RU Servers w/20
2/5” 1.2TB drives each
20 x
R430 1RU Servers
$692,820
4-year Cost
(server refresh)
$452,208
35% Savings
4 x
DriveScale Adaptor
4 x
JBOD w/60
3.5” 2.0TB drives each

30. DriveScale Deployment Scenarios Preserve your existing investment
Greenfield
Start off on the right foot with DriveScale Software Defined Infrastructure
Existing Hadoop – Need more storage on nodes (i.e storage bound)
Just add a JBOD and a DSA, and add disks to existing servers
Existing Hadoop – Rebalance Storage between Nodes and Clusters
Just add a JBOD and a DSA, pull unused disks from DAS servers to JBOD, and redistribute storage and nodes into new clusters.
Existing Hadoop – Need more compute nodes (i.e. compute bound)
Add a compute server, JBOD, and DSA. And you can add more nodes to your cluster without buying more DAS.
Existing Hadoop – Moving from Public to Private or Hybrid Cloud
Cloudera Director and HortonWorks CloudBreak deployed you to the cloud? They are both integrated with DriveScale to deploy your private cloud the same way. You can even have a single cluster span your private and public clouds (i.e. hybrid).

31. DriveScale Solution Components
©2017 DriveScale Inc. All Rights Reserved.

32. DriveScale Components shown in typical rack deployment
Cloud
Software
Hardware
Top of Rack Switches: port 10GbE
(Cisco, Arista, HPE, Dell, Quanta, etc)
DSC
DriveScale
Central
1 per customer
Customer Support
Remote upgrade
Remote licensing
DMS
DriveScale
Management System
1-3 per customer
Linux RPM
Runs on VMs
Inventory
Cluster config
Node config
Out-of-band Management Switch: 1GbE
Node Server Compute Pool
Rack Servers: 2U, 1U, 1/2U or 1/4U
Dell, HPE, Cisco, SuperMicro, Quanta, Foxconn, etc
DriveScale Adapter
Ethernet to SAS Bridge
1 per JBOD
DSN
DriveScale
Server Node Agent
1 on each node
Inventory discovery
Storage Pool – JBOD (Just a Bunch of Drives)
Dell, HPE, SuperMicro, Sanmina, Quanta, Foxconn, etc 32

33. The DriveScale System DriveScale Adapter (DSA)
Highly Automated Infrastructure Provisioning and Management
DriveScale Adapter (DSA)
DriveScale Agent
DriveScale Management System (DMS)
DriveScale Cloud Central (DSC)
DriveScale Agent
DriveScale Server Node (DSN)

34. DriveScale Software Management Architecture
The 4 principal Components:
1. DriveScale Management Server (DMS)
Data repository consists of:
Inventory (DMS’s, DS Adapters, Switches, JBOD Chassis, Disks, Server Nodes)
Configuration (Node Templates, Cluster Templates, Configured Clusters)
Typical deployment consists of 3 DMS Systems
DMS Database is used as a message bus to communicate with the end points
2. DriveScale Adapter (DSA)
DSA Agent Discovery provides inventory for hardware
Creates mappings for Server Nodes to consume disks
3. DriveScale Server Node (DSN)
DS Server Agent provides inventory for server hardware
Consumes mapped disks via DSA
4. DriveScale Central (DSC)
Cloud-based Portal where DriveScale repos are stored for software distribution to subscribers.

35. The DriveScale Adapter
Enables SAS connected drives to be mounted over Ethernet
4 DriveScale Ethernet to SAS Adapters in 1u Chassis
Dual Redundant Power Supplies
With 80 Gb throughput, a single chassis can comfortably support simultaneous access to 80 drives w/ equivalent performance to Direct Attached Storage
2x 10GbE Interfaces per Adapter
2x 12Gb 4 Lane SAS Interfaces per Adapter
The DriveScale system that performs the first part of the magic trick, is a 1U hardware appliance that contains four distinct and separate adapters that connect to servers on one side via 10GbE Ethernet ports, and to JBOD’s on the other side with standard SAS ports. The hardware is designed to be highly resilient with dual power supplies and a passive backplane. The adapters have out of band management ports as well and can comfortably support simultaneous access to 80 drives in JBODs with equivalent performance to direct-attached storage.

36. PoC Minimal HW Requirements (with resiliency)
1x DSA chassis (includes 4x DS Adapters)
1x JBOD to be loaded with the 60 drives
3 (minimum) x Servers (Data Nodes) with 1 direct attached drive each (4-12 drives will be remotely attached via DSA)
1x Server (Name Node) with 1 direct attached drive
1x Server (can be VM) for DMS and Ambari
2x 10GE switches for Data Flow
Management Switch (1GE)
DriveScale Proprietary Information © 2017