The document outlines best practices for optimizing costs on AWS at scale. It discusses five pillars of cost optimization: right-sizing instances, increasing elasticity, picking the right pricing model, leveraging the right services, and measuring/monitoring for optimization. An example from Expedia is provided, where establishing cost transparency and accountability as part of their DevOps culture helped optimize costs through increased reserved instance utilization, reduced hourly costs, and savings despite increased usage. The document emphasizes that cost optimization is an ongoing process.

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Optimizing Costs as You Scale
on AWS
R e b e k e r C h o i
S o l u t i o n s A r c h i t e c t
Level 200

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What you’ll get out of this session?
• Best practices on how to lower your AWS bill
• A more scalable, robust, dynamic architecture
• Real-world customer example

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AWS pricing philosophy
Ecosystem
Global footprint
New features
New services
Infrastructure
Innovation
63 price reductions
since 2006
More AWS
usage
More
infrastructure
Lower
infrastructure
costs
Reduced
prices
More
customers
Economies
of scale

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The Five Pillars of Cost Optimization
Right-sizing your
instances
Increase elasticity Pick the right
pricing model
Leverage the
right service
Measures and
monitors for
optimization

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Pillar 1: EC2 Right-Sizing

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Pillar 1: Right-Sizing
Right-sizing
• Selecting the instance available that best
meets your basic requirements
• Looking at CPU, RAM, storage, and network
utilization to identify potential instances that
can be downsized
• Leveraging Amazon CloudWatch metrics and
setting up custom RAM metrics
Rule of thumb:
Monitor -> Baseline -> Right-size

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Instance ID Instance
Type
On-Demand
cost pm
Instance Specs Utilization data from Amazon
CloudWatch
ABC-123 c3.xlarge $193.45 4 vCPU
7.5GiB RAM
80 SSD
Max vCPU: 35%
Max Disk IO: 20
Max NW: 302 Mbps
Instance ID Instance
Type
On-Demand
cost pm
Instance Specs Savings
ABC-123 m4.large $129.94 2 vCPU
8GiB RAM
EBS only
33% savings
right-size
to
Selecting appropriate instance type

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Pillar 2: Increase Elasticity

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Pillar 2: Increase Elasticity
Turn off non-production instances
• Look for dev/test, non-production instances that are not
required being always-on and turn them off
• AWS Lambda + Amazon CloudWatch = Automated Scheduling*
• https://aws.amazon.com/answers/infrastructure-management/ec2-scheduler/
• https://aws.amazon.com/premiumsupport/knowledge-center/start-stop-lambda-cloudwatch/
Auto-scale production
• Use Auto Scaling to scale up and down based on demand
and usage (for example, spikes)

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Utilization and Auto-Scaling: Granularity
small instances vs. large instances
43 instance hours
m4.xlarge @ $0.2/hr
= $8.6 / day
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

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Instance sizing
1x - m4.4xlarge
16 vcpu, 64GB
RAM
2x - m4.2xlarge
8 vpcu, 32GB RAM
8 vpcu, 32GB RAM
4 vpcu, 16GB RAM
4 vpcu, 16GB RAM
4 vpcu, 16GB RAM
4 vpcu, 16GB RAM
2 vpcu, 8GB RAM
2 vpcu, 8GB RAM
2 vpcu, 8GB RAM
2 vpcu, 8GB RAM
2 vpcu, 8GB RAM
2 vpcu, 8GB RAM
2 vpcu, 8GB RAM
2 vpcu, 8GB RAM
≈
4x - m4.xlarge
≈
8x – m4.large
≈
total cost is the same!

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Utilization and Auto-Scaling: Granularity
small instances vs. large instances
43 instance hours
m4.xlarge @ $0.2/hr
= $8.6 / day
77 instance hours
m4.large @ $0.1/hr
= $7.7 / day
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
~10%
saving

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Pillar 3: Pick the Right Pricing Model

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On-Demand
Instances
Reserved
Instances
Spot
Instances
Pay as you go for computing
power
Flat hourly rate, no upfront
commitments
Pay an upfront fee for a capacity
reservation and a lower hourly
rate (up to 72% savings)
1-year or 3-year terms
EC2, RDS, Redshift, ElastiCache,
Aurora, DynamoDB
Pay what you want for spare
capacity: your instances run if your
bid exceeds the Spot price
Potential for large scale at low cost:
When they’re available, take
advantage of 1,000s of Spot
Instances
Short-term, spiky and
unpredictable Steady state Time or instance flexible
Pillar 3: Pick the Right Pricing Model

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Reserved Instances for Always-On Instances
43 instance hours
m4.xlarge @ $0.2/hr
= $8.6 / day
77 instance hours
m4.large @ $0.1/hr
= $7.7 / day
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
baseline
Reserved Instances
77 instance hours
m4.large OD @ $0.1/hr
m4.large RI @ $0.038/hr
= $6.212 / day
Baseline backed by Reserved Instances
Excess with On-Demand or Spot
~27.8%
saving

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Pillar 4: Leverage the Right Service

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Pillar 4: Right Service – Object Storage
Active data Archive dataInfrequently accessed & long-lived data
Standard
Hot
Standard - Infrequent Access
Warm
Amazon Glacier
Cold
$25 for 1TB data $20 for 1TB data
(20% saving)
$5 for 1TB data
(80% saving)

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Data Lifecycle Management capabilities in s3

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Continuous scalingNo servers to
manage
Never pay for idle
Auto Scaling
Automatic provisioning
No need to manage infrastructure
Just bring your code
100 ms payment granularity
Never pay for idle
Pillar 4: Right Service – Get rid of idle
time with AWS Lambda

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AWS Lambda
Consumers
Producer$0.02
per hour
(avg. calculated based on
consumption)
Producer
ConsumersEC2 instance
scheduler
$0.085
per hour
(small instance)
VS
Pillar 4: Lambda Example

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Pillar 4: Right Service - Offload popular traffic
to Amazon S3 and/or Amazon CloudFrontResponseTime
ServerLoad
Response
Time
Server
Load
Response
Time
Server
Load
No CDN CDN for Static
Content
CDN for Static
& Dynamic
Content

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Pillar 5: Measure and Monitor

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Tooling Options
AWS Options DIYAWS
Marketplace

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AWS Trusted Advisor
Helping Customers automate best practices (checks) across cost optimization,
security, fault tolerance, and performance improvement

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Idle test instances running in us-west-1

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…Or using an AWS Partner Tool…

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Measuring and Monitoring
How do you implement “continuous cost
optimization” at scale?

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E x p e d i a : R e v o l u t i o n i z i n g t r a v e l t h r o u g h t h e p o w e r o f t e c h n o l o g y
2 0 0 + $ 8 3 . 8 B i l l i o n 2 8 9 M
T r a v e l B o o k i n g S i t e s G r o s s B o o k i n g s R o o m N i g h t s
I n o v e r 7 5 c o u n t r i e s
Source: Stats are for the 12 months ended 6/30/17 from Expediainc.com
Our Finance Mission:
“Drive effective and then efficient use of cloud related resources while ensuring that we can
properly forecast, account, report and make financially intelligent decisions that are aligned
across brands.”

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H ere i s E xpedi a’s story … “C l ou d a nd th e Money S hi p”
Before...
After...

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How did we turn around the money ship?

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Started with Optimization: Small temporary team
to look at all the apps to minimize waste
That did not last long, not sustainable long term
We knew the longer-term solution was to have cost
awareness become part of our DevOps culture

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cost optimization cost transparency

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Cost Transparency
Enabled automation
• Fixed our automation
to tag all taggable
resources
• Built automation to
automatically remove
untagged resources
within minutes
Tooling
• Team has cost
awareness by using
the tools to develop
new insights on
potential cost
efficiencies
Cloud Portfolio Analyzer
(CPA)
Define success
• Establishing metrics and
tracking progress
• E.g.
• % RI utilization
• % of resources covered by
RIs
• $ of unallocated resources
due to missing tags
• $ monthly forecast vs actual

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A consequence of cost transparency at Expedia:
Cost awareness become part of our DevOps culture

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Reserved Instances pricing model is a key part of our strategy
Cover always-on resources with Standard Partial Upfront 1yr
RI with regional benefit
Smaller but more frequent RI purchases…
Every 5/6 months –> monthly -> weekly
Leveraged RIs for:
Amazon EC2
Amazon RDS
Amazon Redshift
Amazon ElastiCache
Cost Optimization
Measure, Monitor, Improve

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Cost awareness became part of our DevOps culture
Maintain >90% tagging of all taggable resources
Increased RI coverage from 40% to 70%
Reduced instance hourly unit cost by 22%
Fivefold increase in savings
Even instance hourly usage increased by 250%
1 2 + m o n t h s l a t e r …
Results

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C ost Opti mi zati on P racti ces
Cost Transparency
• Tagging automation
• Visualization and monitoring tools
Monitor & measure
Cost Optimization
• Leveraged RI pricing
Cost Accountability
• Encouraged teams to share optimization best practices

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Summary
• 5 pillars
• Right-Sizing
• Elasticity
• Strike the balance between different pricing model
• Leverage the right service
• Monitor, Measure & Optimize
• Cost optimization is an on-going process
• Culture of cost accountability

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Thank you!
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