Increasing Your AWS Cost Efficiency with Cloudability

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ccQXlxjSvJmw

Scott Ward Solution Architect

Amazon Web Services

J.R. Storment Co-Founder Cloudability

Introducing Andrew Midgley

Software Testing Lead REA Group

Overview of AWS tools for resource utilization management

Case study: REA Group’s journey toward AWS cost and usage control using

Cloudability

Demo of Cloudability’s cost management tools for AWS

Q&A

What We’ll Cover

One of the primary reason

businesses are moving so quickly

to AWS and the cloud is

increased agility.

Enterprises Can’t Afford to be Slow

Add New Dev Environment

Add New Prod Environment

Add New Environment in APAC

Add 1,000 Servers

Remove 1,000 Servers

Deploy 1 PB Data Warehouse

Shut down 1 PB Data Warehouse

AWS:

Infrastructure in Minutes Old World:

Infrastructure in Weeks

Global Services

* China (Beijing) Region-

EC2 Availability Zones: 1 Coming Soon

10 Regions*

26 Availability Zones*

51 Edge Locations

A Culture of Innovation

On-Premises

Experiment Infrequently

Failure is expensive

Less Innovation

Experiment Often

Fail quickly at a low cost

More Innovation

Cost Savings and

Flexibility

Source: IDC Whitepaper,

sponsored by Amazon, “The

Business Value of Amazon Web

Services Accelerates Over Time.”

December 2013

1

“Average of 400 servers

replaced per customer”

Replace up-front

capital expense with

low variable cost

2

42 Price

Reductions

Economies of scale

allow AWS to continually

lower costs

4

Save more money as

you grow bigger

Tiered Pricing

Volume Discounts

Custom Pricing

3

Pricing model choice

to support variable &

stable workloads

On-Demand

Reserved

Spot

Dedicated

How can you achieve lower TCO with AWS?

Pricing Models on AWS

On-Demand

Pay for compute capacity

by the hour with no long-

term commitments

For spiky workloads,

or to define needs

Reserved

Make a low, one-time

payment and receive a

significant discount on the

hourly charge

For committed utilization

Spot

Bid for unused capacity,

charged at a Spot Price

which fluctuates based on

supply and demand

Name: Andrew Midgley

Date: June 12, 2014

AWS Cost Optimization @ realestate.com.au

About REA Group

• REA Group is a $6 Billion Market Cap

online business based in Australia

• REA started an aggressive move to

AWS in 2010

• I’ve been involved as a core part of

that effort since the beginning

14

• Cloud adoption started in Dev/Test

• All of our business units shared the

same AWS account

• Costs were controlled by simply

adjusting AWS resources limits (such

as ec2 node counts)

Humble beginnings

15

• Resource limits created drama among

internal users

• Significant wins by optimizing EC2

type/size usage

• Biggest win was employing the

“Stopinator”

Ad hoc cost controls were needed

16

• Our cloud adoption grew, increasing

the need for detailed cost reporting

• We had no way to allocate costs

between four large business units

• We needed to better understand our

usage profile

We had to go further

17

• Tagging

• Mandatory “Business Unit” tag

• Recommended

environment/application tag

• “Tag or terminate”

• required to ensure that tagging was

system-wide

Step 1: Resource allocation

18

Then we introduced …

Step 2: Cost visibility

19

• Satisfied management’s need for

spending visibility

• Immediately found $5000 in savings

• Found a business unit that was actually

under utilizing AWS

• Cloudability quickly spread throughout

the organization via workshops and

intranet

Step 2: Cost visibility

Step 2: Cost visibility

• Saving/sharing interesting reports in

Cloudability

◆ Underutilized resources: What’s not

being used?

◆ Project specific reports on spending or

resource usage

• Dashboarding simple metrics using

Cloudability json API

Step 3: Making cost optimization “top of mind”

Costly habits could be clearly shown

in dev/test environments

◆ Unused nodes

◆ Underutilized nodes

◆ Unnecessarily expensive nodes

◆ Old nodes

◆ Excessive node uptimes

Step 4: The data made things clear

Midge’s Law

• Used Cloudability API data to

normalize dev/test environment

“health”

• Developed an algorithm to determine

health/sickness of any dev/test

environment

Step 5: Putting the data to work

avg hourly node cost ($)

X

avg node uptime (%)

X

sq rt of inverse of CPU utilization (%)

X

avg node running life (hrs)

X

avg daily unique nodes^1.3

Step 4: Learning from the data

Step 4: Learning from the data

• More sophisticated dashboarding with

d3 and JS

• Applying similar optimization

principles in production

• Further optimizing hourly rate with

EC2 Reserved Instances

Taking it to the next level

@cloudability

@cloudability

Improving TCO on

AWS:

5 Takeaways for

Savings

@cloudability

@cloudability

@cloudability

๏ @cloudab

ility

TCO Takeaways

Putting AWS cost efficiency into action

• Watch your AWS spending every day

• Find what you’re not using so you can stop paying for it

•Determine what “underutilized” means for various instance roles

•Buy Reserved Instances iteratively and often

@cloudability @cloudability

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