Download pdf - (ARC302) Running Lean Architectures: How to Optimize for Cost Efficiency | AWS re:Invent 2014

November 13, 2014 | Las Vegas, NV

Mimi Jiang, Adobe

Constantin Gonzalez, AWS

• Speed, agility, and innovation

• Focus on your business

• Go global in minutes

Ecosystem

Global Footprint

New Features

New Services

More AWS

Usage

More

Infrastructure

Lower

Infrastructure

Costs

Reduced

Prices

More

CustomersInfrastructure

Innovation

45 price

reductions

since 2006Economies

of Scale

aws.amazon.com/premiumsupport/trustedadvisor/

Free with Business or Enterprise Support

Monday Friday End of Vacation Season35% saved

"LaunchConfig": {

"Type" : "AWS::AutoScaling::LaunchConfiguration",

"Metadata" : {

"AWS::CloudFormation::Init" : {

"config" : {

… packages, sources, files, services …

}

}

},

"Properties": {

"ImageId" : "ami-149f7863",

"InstanceType" : "m1.small",

"SecurityGroups" : [ {"Ref" : "WebServerSecurityGroup"} ],

"KeyName" : "MySSHKey",

"UserData" : { "Fn::Base64" : { "Fn::Join" : ["", [

"#!/bin/bash -v\n",

… your user data script …

]]}}

}

}

"WebServerGroup" : {

"Type" : "AWS::AutoScaling::AutoScalingGroup",

"Properties" : {

"AvailabilityZones" : [

"us-east-1a","us-east-1b","us-east-1c",

],

"LaunchConfigurationName" : { "Ref" : "LaunchConfig" },

"MinSize" : “3",

"MaxSize" : “6",

"DesiredCapacity" : “3",

"LoadBalancerNames" : [ { "Ref" : "ElasticLoadBalancer" } ]

}

}

{ adobe.io}Running Lean

Architectures

in AWSMimi Jiang | Performance & Reliability, adobe.io

© 2014 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.

New era of creativity

Adobe Creative SDK

Adobe Ink & Slide


API Gateway

API Management

Services

API Console

{ adobe.io }: Adobe’s API platform

3rd party apps

Adobe apps

{adobe.io}

API services


{ adobe.io }: AWS deployment architecture

API Consumers

Availability Zone 1

Private Subnet

Availability Zone 2

Public Subnet

Private Subnet

Auto Scaling Group

Auto Scaling Group

Region (US East, EU, AP, US West)

AmazonRoute

53

Public Subnet


Instance type sizing

Recommended steps:

Define application characteristics

Shortlist instance types

Analyze – performance, cost, & resiliency

Architect


{ adobe.io } use case

Application

characteristics

:

Instance

Type

On-Demand

Cost

vCPU Memory

(GB)

Storage

(GB)

Network

Performance

cc2.8xlarge $2.40 32 60.5 4x840 10 Gigabit *

m3.2xlarge $0.56 8 30 2x80 High

C3.2xlarge $0.42 8 15 2x80 High

CPU intensive traffic

Minimum 8 core CPU

Support for heavy payloads

Architect


19168 2165528037

2329230003 3191928357

3269938962

2000 users 4000 users 6000 users

CPU TestSingle node (requests/sec)

m3.2xlarge c3.2xlarge cc2.8xlarge

{ adobe.io } performance analysis

3539

113

Network TestSingle node (requests/sec)

cc2.8xlarge c3.2xlarge m3.2xlarge

CPU: 30%CPU: 90-95%

Architect

Total bandwidth

= Network In +

Network Out

5 4 1

3:1


{ adobe.io } cost analysis

$307.44

$409.92

$1,756.80

c3.2xlarge

m3.2xlarge

cc2.8xlarge

Monthly on-demand cost per node (US East)

$2.40/hr

$0.56/hr

$0.42/hr

Architect

0

500

1000

1500

2000

2500

3000

3500

4000

4500

30K req/sec 60K req/sec 100K req/sec 200K req/sec

Co

st

$/Month vs. Throughput

cc2.8xlarge

m3.2xlarge

c3.2xlarge30%

16%

30%


{ adobe.io } resiliency analysis

AZ1 AZ2Region

cc2.8xlarge

AZ1 AZ2Region

c3.2xlarge /

m3.2xlarge

VS

Architect


{ adobe.io } Decision & takeaways

Instance type selected: c3.2xlarge

What we learned• Match instance type with expected workload

• Smaller instance types provide better granularity

• Enhanced networking is available in c3, r3, & i2 instance

types

• Boot time varies between different instance types

• Amazon CloudWatch detailed monitoring gives better

granularity

• Instance type differs by region (cost, availability)

• Set a cadence to repeat

Architect


Scaling mechanisms

Event-based scaling• Overprovision for sharp traffic increase

** Prewarm your load balancer

• Observe traffic pattern & scale down

Schedule-based scaling• Match scaling with workload at different times

• Scale down dev & test environments

Architect


Auto Scaling

• Use for less steep traffic increase

• Scale up fast, scale down slow• ** Remember you are charged hourly

• Set triggers: CPU, network, memory

• Avoid multiple scaling triggers per Auto

Scaling group

Architect

Auto Scaling policy example:

Scale up: +2 instances if CPU utilization > 70% for 2 minutes

Scale down: -2 instances if CPU utilization <= 40% for 20

minutes

Cooldown: 300 seconds


Monitoring tips

• Tailor monitoring strategy to application

characteristics

• Monitor both cost & usage

• Tag your instances

• Establish thresholds/alerts

• Analyze & adjust resource usage often

• Tools make it easier

Architect


Open source—Netflix ICE

• Cost & usage reporting

• Uses AWS Programmatic Billing

Access

• Maintains knowledge of:

• Accounts, regions, services,

usage types, cost/usage

categories

https://github.com/Netflix/ice

Architect


Commercial tool—Cloudability

usage comparison

underutilized instances

daily summary

Architect


Wrap-up

• Cost, performance, & resiliency have equal

weight

• Embrace failure, architect for it

• Turn off unused capacity, automate it!

• Benefit from auto-scaling, but be careful!

• Monitor & frequently evolve your architectureCheck out these other sessions:• SDD402 – Amazon ElastiCache Deep Dive (Frank Wiebe, Principal Scientist,

Adobe)

• ENT207 – Creating a Culture of Cost Management in Your Organization (J.R.

Stoment, Chief Customer Officer, Cloudability)


Contact me: [email protected]

Thank You!

1y RI

Break even

3y RI

Break even

On-Demand:

$0.24

$0.028 (11.7%) $0.026 (10,8%)

$3.28

(1367%)

20%

64%

Caching/Optimization:

80% saved

Cache

flush

Dynamic

DynamoDB:

20% saved

Growth +

new features

Simple, more reliable, lower cost

http://bit.ly/awsevals

http://bit.ly/awsevals