Bringing Your Applications to the Fast Lane (CPN203) | AWS re:Invent 2013

Bringing Your Applications to the Fast Lane
Deepak Singh - Amazon Web Services
Christos Kalantzis - Netflix
Steven Jones - Amazon Web Services
November 15, 2013

© 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
Friday, November 15, 13

Hello!

Instance Types


Performance


Generations


Many instance types


Building Blocks


General Purpose
Compute-optimized
Memory-optimized
Storage-optimized
GPU
Micro


M1, M3
C1, CC2
M2, CR1
HI1, HS1
CG1, G2
Micro

Workload optimized


Compute-optimized


2.6 GHz Intel Xeon E5-2670


16 cores/32 vCPU


10 Gbps cluster networking


High Performance Linpack


Cores


max
R

240.09

peak
R

cc2.8xlarge

17024

354.12

HI1 instances


High random I/O performance


Netflix and HI1
Christos Kalantzis


Advantages of using hi1.4xlarge with C*
• Higher application speed
• Efficient operations & better data quality
• Cost savings


Higher Application Speeds
• Compared m2.4xlarge & hi1.xlarge
• 6 node C* cluster with 250 GB data on each node
• Used following Cassandra Stress tool & Options
from three m2.4xlarge clients:
– cassandra-stress -d [server-list] -t 25 -r -p 7102 -n 1000000000 -k -o
READ



C*

Cassandra-stress

Cassandra-stress

Cassandra-stress


C*

C*

C*
C*

C*

m2.4xlarge results
Throughput


Speed

hi1.4xlarge results
Throughput


Speed

• 40X throughput
• Better Latencies
– ~37X AVG
– ~109X 95th %ile
– ~110X 99th %ile


Efficient C* Operations & Better Data Quality
• Cassandra => “benefit now, pay later”
– Immutable SSTABLES need to be compacted
– Can compact faster & with less impact

• Eventual Consistency
– Repairs run more often
– Increased Consistency without higher CL calls


Cost Savings
• Can now have multi-tenant clusters
– Savings immediate on the second application
– m2.4xlarge is $1.640 per hour
– hi1.4xlarge is $3.100 per hour
C*
App A

C*
App A

C*
App A

C*
App A

C*
App A


C*
App B

C*
App A

C*
App
A&B

C*
App B

C*
App B

C*
App B

C*
App B

C*
App B

C*
App
A&B

C*
App
A&B

C*
App
A&B

C*
App
A&B

C*
App
A&B

Cost Savings
• Use Less Nodes
– Data : Memory ratio can now be bigger
– Cluster size doesn’t need to be doubled as often


Cost Savings
• Smaller Operational Footprint
– Less clusters
– Smaller operational teams
– Less fire-fighting
– Team can focus on automation


hi1.4xlarge caveats
• 10 Gbps not attained (in our model)
– Need to be part of the same Cluster Placement Group
– Netflix cross-zone availability model excludes CPG

• Not same as bare metal SSD running on Linux
– Virtualization obfuscates some SSD advantages


Memory-optimized


244 GiB of RAM


2.6 GHz Intel Xeon E5 2670


In-memory distributed analytics


e.g. SAP HANA


Steven Jones
Amazon Web Services


SAP


ERP

SAP


ERP

BI

Aggregates

SAP


ERP

BI

Aggregates

SAP


ERP

Pre-Defined
Queries

BI

Pre-Defined
Queries

Aggregates

SAP


ERP

BI

BWA

TREX

Magnetic Disk
SSD/Flash
Latency
RAM
CPU Cache
CPU Register
Storage Type

Magnetic Disk
RAM is up to 100,000
x Faster

SSD/Flash
Latency
RAM

CPU Cache
CPU Register
Storage Type

SAP HANA
High Performance Analytic Appliance
aka In-Memory Database Platform

http://tinyurl.com/hana-perf

SAP


ERP

BI
HANA

SAP


ERP
HANA

EC2 Cluster Compute instances
cc2.8xlarge

cr1.8xlarge

2 x Intel Xeon E5-2670 processors
32 vCPUs with hyperthreading
64-bit
60.5 GB RAM
10 Gigabit Network

2 x Intel Xeon E5-2670 processors
32 vCPUs with hyperthreading
64-bit
244 GB RAM
10 Gigabit Network
NUMA and Turbo Support New

All c* instances support high-performance (10 gigabit) networking to Elastic Block Storage volumes (EBS)

SAP HANA on AWS
1,776 Core HANA Cluster on AWS
60B Rows | 8M Rows/s | 3M Queries/h | 330ms


Where to go for HANA
SAP Developer Center
http://bit.ly/aws-hana-dev
Free SAP license

AWS Marketplacehttp://bit.ly/
aws-hana-one
99¢ / hr SAP License

SAP HANA Marketplace
http://bit.ly/aws-hana-byol
BYOL


New generations


Latest Generation
Hardware


Hardware features,
e.g. AVX


Enhanced Networking


Better priceperformance


Best raw compute capacity


2.8 GHz Intel Xeon E5-2680v2
(Ivy Bridge)


Clustering as a “feature”


Cores


max
R

484.18

peak
R

c3.8xlarge

26496

593.87

Rmax%
600"

500"

400"

300"

200"

100"

0"
CC1"


CC2"

C3"

Cores


max
R

163.9

peak
R

c3.8xlarge

8192

183.5

Coming Soon


Best Price for IOPS


More sizes


More SSD


More IOPS


More memory


350,000+ random read IOPS
320,000+ random write IOPS
i2.8xlarge


175,000+ random read IOPS
160,000+ random write IOPS
i2.4xlarge


Enhanced Networking
Low latency
Low jitter
Very high PPS performance


Latency

cc2.8xlarge+

c3.8xlarge+

c3.8xlarge+(enhanced)+

PPS

cc2.8xlarge+


c3.8xlarge+

c3.8xlarge+(enhanced)+

p50$
p90$
p999$
p100$

Low network jitter


General Purpose
Compute-optimized
Memory-optimized
Storage-optimized
GPU
Micro


M1, M3
C1, CC2, C3
M2, CR1
HI1, I2, HS1
CG1, G2
Micro

More to come


Please give us your feedback on this
presentation

CPN203
As a thank you, we will select prize
winners daily for completed surveys!


Thank You

Bringing Your Applications to the Fast Lane (CPN203) | AWS re:Invent 2013

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