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
Contacts and Q&A Contacts: Cloudability Info: https://cloudability.com/ AWS Contact: aws.amazon.com/contact-us
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