Kyle Bader, Solutions Architect, Red Hat

1. PERFORMANCE AND SIZING
SOFTWARE DEFINED STORAGE
Kyle Bader
Red Hat Storage Day, Los Angeles
August 2016

2. $> whois kyle bader
Senior Solution Architect
Red Hat

3. DATA CHALLENGES
Exponential growth in digital content increases pressure on
capacity, scalability, and cost.
The need for access to data from anywhere, anytime, on
any device requires unprecedented agility.
Modern services require the flexibility to store data on-
premises or in the cloud.
Growing content requires advanced data protection that
ensures integrity & high availability at very large scale.
1
2
3
4

4. Traditional Storage
Complex proprietary silos
Open, Software-Defined Storage
Standardized, unified, open platforms
Custom GUI
Proprietary Software
Proprietary
Hardware
Standard
Computers
and Disks
Standard
Hardware
OpenSource
Software
Ceph Gluster +++
Control Plane (API, GUI)
ADMIN USER
THE FUTURE OF STORAGE
ADMIN
USER
ADMIN
USER
ADMIN
USER
Custom GUI
Proprietary Software
Proprietary
Hardware
Custom GUI
Proprietary Software
Proprietary
Hardware

5. FLEXIBILITY IS CRUCIAL

6. Server-based storage uses software and standard hardware to provide services
traditionally provided by single-purpose storage appliances, providing increased
agility and efficiency.
DISTRIBUTED CLUSTER OF
SERVERS
MEDIA MEDIA MEDIA MEDIA MEDIA MEDIA MEDIA
APPLIANCE
MEDIA MEDIA
APPLIANCE
MEDIA MEDIA
APPLIANCE
MEDIA MEDIA
USER USER USER
SERVER-BASED STORAGE
USER USER USER

7. STORAGE APPLIANCE
COMPUTE
NODE + + + +
+
STORAGE
NODE
COMPUTE
NODE + + + +
+ + + +
+
+
+
+
+
+
+
+
VIRTUALIZED STORAGE SCALES BETTER

8. STANDARD SAN/NAS IS ON THE DECLINE
Server-based storage is “will account for over 60%
of shipments long term.”
“By 2016, server-based storage solutions will lower
storage hardware costs by 50% or more.”
Gartner: “IT Leaders Can Benefit From Disruptive Innovation in the Storage Industry”
Credit Suisse Storage Update, September 3, 2015
Changing workloads drive the need for
flexible, economical server-based storage.
WW DEPLOYED CAPACITY (TB)
2010 2011 2012 2013 2014 2015
(est)
2016
(est)
Source: IDC
0%
60%
20%
40%
80%
100
%
Internal CapacityExternal
Capacity

9. STORAGE ORCHESTRATION
Storage orchestration is the ability to provision, grow, shrink, and decommission
storage resources on-demand and programmatically, providing increased control
and integration of storage into a software-defined data center.
WEB CONSOLE
A browser interface designed for
managing distributed storage
API
A full API for automation and
integration with outside systems
COMMAND LINE
A robust, scriptable command-line
interface for expert operators
PROVISION INSTALL CONFIGURE TUNE MONITOR
Full lifecycle management for distributed, software-defined data services

10. A RISING TIDE
“By 2020, between 70-80% of unstructured data will
be held on lower-cost storage managed by SDS”
“By 2019, 70% of existing storage array products
will also be available as software only versions”
Innovation Insight: Separating Hype From Hope for Software-Defined Storage
Innovation Insight: Separating Hype From Hope for Software-Defined Storage
2013 2014 2015 2016 2017 2018 2019
$1,349M
$1,195
M
$1,029M
$859M
$706M
$592M
SDS-P MARKET SIZE BY SEGMENT
$457M
Block Storage
File Storage
Object Storage
Hyperconverged
Source: IDC
Software-Defined Storage is leading a
shift in the global storage industry, with
far-reaching effects.

11. THE BALANCE
Inflexible
Expensive at large scale
Durable
Convenient
Flexible
Economical at large scale
Durable
Powerful
Appliances are suitable for small-
scale, workloads, but they do not scale
economically.
Software-defined storage has a
learning curve, but bring performance
and economy at petabyte scale.

12. THE ROBUSTNESS OF SOFTWARE
Software is more flexible than hardware
Software can do things hardware appliances can’t. SDS brings the
flexibility of software to the enterprise storage world.
• Can be deployed on bare metal, inside containers, inside VMs, or
in the public cloud.
• Can deploy on a single server, or thousands, and can be
upgraded and reconfigured on the fly.
• Grows and shrinks programmatically to meet changing demands

13. BUILDING ON PROVEN HARDWARE
Hardware is hard, and we got you covered
Tested software defined storage solutions, for repeatable success.
• Ceph Hardware Configuration Guide
• Ceph Hardware Selection Guide
• Ceph Performance and Sizing Guide - Supermicro
• Ceph Performance and Sizing Guide - Quanta QCT

14. OPTIMIZATION CRITERIA
IOPS
Optimized
Throughput
Optimized
Capacity
Optimized
• Lowest cost per IO
• Highest IOPS
• Meet minimum fault domain
requirement
• Lowest cost per unit of throughput
• Highest throughput
• Highest throughput per watt/BTU
• Meet minimum fault domain
requirement
• Lowest cost per TB
• Lowest watt/BTU per TB
• Meet minimum fault domain
requirement
• Typically block storage
• Replication
• MySQL for OpenStack tenants
• Block and object storage
• Replication or erasure coded
• Active performance storage for video,
audio, and images
• Streaming media
• Typically object storage
• Erasure coding dominant
• Media archives
• Data lake

17. • Shared, elastic storage pool
• Dynamic DB placement
• Flexible volume resizing
• Live instance migration
• Backup to object pool
• Read replicas via copy-on-write snapshots
MySQL ON CEPH STORAGE CLOUD
OPS EFFICIENCY

18. MYSQL-ON-CEPH PRIVATE CLOUD
FIDELITY TO A MYSQL-ON-AWS EXPERIENCE
• Hybrid cloud requires public/private cloud commonalities
• Developers want DevOps consistency
• Elastic block storage, Ceph RBD vs. AWS EBS
• Elastic object storage, Ceph RGW vs. AWS S3
• Users want deterministic performance

19. HEAD-TO-HEAD
PERFORMANCE
30 IOPS/GB: AWS EBS P-IOPS TARGET

20. HEAD-TO-HEAD LAB
TEST ENVIRONMENTS
• EC2 r3.2xlarge and m4.4xlarge
• EBS Provisioned IOPS and GPSSD
• Percona Server
• Supermicro servers
• Red Hat Ceph Storage RBD
• Percona Server

21. OSD Storage Server Systems
5x SuperStorage SSG-6028R-OSDXXX
Dual Intel Xeon E5-2650v3 (10x core)
32GB SDRAM DDR3
2x 80GB boot drives
4x 800GB Intel DC P3700 (hot-swap U.2 NVMe)
1x dual port 10GbE network adaptors AOC-STGN-i2S
8x Seagate 6TB 7200 RPM SAS (unused in this lab)
Mellanox 40GbE network adaptor(unused in this lab)
MySQL Client Systems
12x Super Server 2UTwin2 nodes
Dual Intel Xeon E5-2670v2
(cpuset limited to 8 or 16 vCPUs)
64GB SDRAM DDR3
Storage Server Software:
Red Hat Ceph Storage 1.3.2
Red Hat Enterprise Linux 7.2
Percona Server
5x OSD Nodes 12x Client Nodes
Shared10GSFP+Networking
Monitor Nodes
SUPERMICRO CEPH
LAB ENVIRONMENT

22. 7996 7956
950
1680 1687
267
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
P-IOPS
m4.4xl
P-IOPS
r3.2xl
GP-SSD
r3.2xl
100% Read
100% Write
SYSBENCH BASELINE ON AWS EC2 + EBS

23. 7996
67144
40031
1680
5677
1258
20053
4752
0
10000
20000
30000
40000
50000
60000
70000
80000
P-IOPS
m4.4xl
Ceph cluster
1x "m4.4xl"
(14% capacity)
Ceph cluster
6x "m4.4xl"
(87% capacity)
100% Read
100% write
70/30 RW
SYSBENCH REQUESTS PER MYSQL INSTANCE

24. CONVERTING SYSBENCH REQUESTS TO
IOPS READ PATH
X% FROM INNODB BUFFER POOL
IOPS = (READ REQUESTS – X%)
SYSBENCH READ

25. CONVERTING SYSBENCH REQUESTS TO
IOPS WRITE PATH
SYSBENCH WRITE
1X READ
X% FROM INNODB BUFFER POOL
IOPS = (READ REQ – X%)
LOG, DOUBLE WRITE BUFFER
IOPS = (WRITE REQ * 2.3)
1X WRITE

26. 30.0 29.8
3.6
25.6 25.7
4.1
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
P-IOPS
m4.4xl
P-IOPS
r3.2xl
GP-SSD
r3.2xl
100% Read
100% Write
AWS IOPS/GB BASELINE: ~ AS ADVERTISED!

27. IOPS/GB PER MYSQL INSTANCE
30
252
150
26
78
19
0
50
100
150
200
250
300
P-IOPS
m4.4xl
Ceph cluster
1x "m4.4xl"
(14% capacity)
Ceph cluster
6x "m4.4xl"
(87% capacity)
MySQL IOPS/GB Reads
MySQL IOPS/GB Writes

28. FOCUSING ON WRITE IOPS/GB
AWS THROTTLE WATERMARK FOR DETERMINISTIC PERFORMANCE
26
78
19
0
10
20
30
40
50
60
70
80
90
P-IOPS
m4.4xl
Ceph cluster
1x "m4.4xl"
(14% capacity)
Ceph cluster
6x "m4.4xl"
(87% capacity)

29. A NOTE ON WRITE AMPLIFICATION
MYSQL ON CEPH – WRITE PATH
INNODB DOUBLE
WRITE BUFFER
CEPH REPLICATION
OSD JOURNALING
MYSQL
INSERT
X2
X2
X2

30. EFFECT OF CEPH CLUSTER LOADING ON
IOPS/GB
78
37
25
19
134
72
37 36
0
20
40
60
80
100
120
140
160
Ceph cluster
(14% capacity)
Ceph cluster
(36% capacity)
Ceph cluster
(72% capacity)
Ceph cluster
(87% capacity)
IOPS/GB
100% Write
70/30 RW

31. 18
18
19
6
34 34
36
8
0
5
10
15
20
25
30
35
40
Ceph cluster
80 cores
8 NVMe
(87% capacity)
Ceph cluster
40 cores
4 NVMe
(87% capacity)
Ceph cluster
80 cores
4 NVMe
(87% capacity)
Ceph cluster
80 cores
12 NVMe
(84% capacity)
IOPS/GB
100% Write
70/30 RW
CONSIDERING CORE-TO-FLASH RATIO

32. HEAD-TO-HEAD
PERFORMANCE
30 IOPS/GB: AWS EBS P-IOPS TARGET
25 IOPS/GB: CEPH 72% CLUSTER CAPACITY (WRITES)
78 IOPS/GB: CEPH 14% CLUSTER CAPACITY (WRITES)

34. HEAD-TO-HEAD
PRICE/PERFORMANCE
$2.50: TARGET AWS EBS P-IOPS STORAGE PER IOP

35. IOPS/GB ON VARIOUS CONFIGS
31
18 18
78
-
10
20
30
40
50
60
70
80
90
IOPS/GB
(SysbenchWrite)
AWS EBS Provisioned-IOPS
Ceph on Supermicro FatTwin 72% Capacity
Ceph on Supermicro MicroCloud 87% Capacity
Ceph on Supermicro MicroCloud 14% Capacity

36. $/STORAGE-IOP ON THE SAME CONFIGS
$2.40
$0.80 $0.78
$1.06
$-
$0.50
$1.00
$1.50
$2.00
$2.50
$3.00
Storage$/IOP
(SysbenchWrite)
AWS EBS Provisioned-IOPS
Ceph on Supermicro FatTwin 72% Capacity
Ceph on Supermicro MicroCloud 87% Capacity
Ceph on Supermicro MicroCloud 14% Capacity

37. HEAD-TO-HEAD
PRICE/PERFORMANCE
$2.50: TARGET AWS P-IOPS $/IOP (EBS ONLY)
$0.78: CEPH ON SUPERMICRO MICRO CLOUD CLUSTER

39. 8x Nodes in 3U chassis
Model:
SYS-5038MR-OSDXXXP
Per Node Configuration:
CPU: Single Intel Xeon E5-2630 v4
Memory: 32GB
NVMe Storage: Single 800GB Intel P3700
Networking: 1x dual-port 10G SFP+
+ +
1x CPU + 1x NVMe + 1x SFP
SUPERMICRO MICRO CLOUD
CEPH MYSQL PERFORMANCE SKU