(Presented by Cloudability) Amazon EC2 Reserved Instances (RIs) are a great way for many customers to save money on AWS, particularly because the break-even point is well inside of their term. But for some customers the analysis and selection process is not well understood and can prevent them from making a decision that could save them money. In this talk, Cloudability VP of Product Development Toban Zolman walks you through the most common scenarios for RIs, shows you how to make the best possible decisions for RI purchases, and how to significantly reduce the time needed to make those decisions.

1. The Science Behind Choosing
Reserved Instances
Toban Zolman, Cloudability
November 13, 2013

2. Introduction
• Understanding reservations
• Simplifying Reserved Instance purchases while
maximizing ROI
• Recommended approach to purchasing
reservations

3. 8000+ Companies • $600M+ managed cloud spending

4. Our Solution

5. The Science of Purchasing Reservations

6. Is your company currently purchasing
AWS reservations?

7. Most people over-simplify reservation purchasing

8. RESULT: Reserved Instance purchases
misalign to your needs reducing ROI

9. Go all in on 1 or 2 large buys each year

10. Result: Large cliffs in
reservation levels

11. How frequently are you purchasing reservations?

12. Reservations 101

13. What is a reservation?
Reservations allow you to reserve resources/capacity for one or three years in
a particular region in exchange for a lower overall unit price.
Compute
Amazon EC2
Database
Amazon DynamoDB
Amazon RDS
Amazon Redshift
Amazon ElastiCache
CDN
Amazon CloudFront

14. Why make reservations?
1. Lower the cost of resources you are already using
Reservations provide substantial cost savings versus “on-demand” pricing.

15. Cost Savings vs On-Demand Comparison
There are 2,000+ different reservation types each with their own breakeven points.
LINUX m1.xlarge instance – over 3 years
Annual Utilization Rate
Light Utilization RI
Medium Utilization RI
Heavy Utilization RI
20%
25%
-7%
-77%
40%
40%
33%
11%
60%
45%
46%
41%
80%
48%
52%
56%
100%
49%
59%
65%

16. Why make reservations?
1. Lower the cost of resources you are already using
Reservations provide substantial cost savings versus “on-demand” pricing.
2. Lock-in future capacity in same region/Availability Zone
Very useful if you experience bursts/spikes in usage
3. Reserve capacity in another region just in case...
Demand can cause a run on capacity. Reservations ensure you get seat at
the table.

17. Why are you currently purchasing
Reserved Instances?

18. Reserved Instance Pricing Components
Reservation Type
Light
Upfront Fee
Yes
Hourly Usage Fee
Yes
Minimum Usage Level
None
If the instance is not used during
the hour, there is no charge.
Medium
Yes
Yes
None
If the instance is not used during
the hour, there is no charge.
Heavy
Yes
Yes
Yes
Billed a full month’s worth of
hours at the start of each month.

19. How are reservations applied
• Reserved Instances are purchased for an instance type
(m1.xlarge) in a particular Availability Zone (us-east-1a)
• Reservations are applied each hour.
• If an instance is running in a “linked account”, it can inherit an
unused reservation from a different linked account under the
consolidated billing payer account
• Capacity reservation stays with the linked account.

20. Modifying Reserved Instances
• Amazon allows companies to apply to transfer a
reservation from one Availability Zone to another
• Trade-in existing Reserved Instances for a different size
in the same family
• The fine print:
Transfers do not happen automatically
Transfers are not guaranteed and are based on available capacity

21. A Simplified Example of Calculating
Reservation Needs

22. Running Instances by Hour of the Month
(example assumes 10 hours in month)
Hour of month
Running Instances
1
4
2
6
3
0
4
5
5
7
6
8
7
5
8
3
9
12
10
3

23. Hourly Frequency Distribution of Instance Levels
Running Instance Count
Frequency of Occurrence
Freq. %
0
1
10%
1
9
90%
2
9
90%
3
9
90%
4
7
70%
5
6
60%
6
5
50%
7
4
40%
Break even point for Medium
8
2
20%
Break even point for Light
9
1
10%
10
1
10%
11
1
10%
12
1
10%
Break even point for Heavy

24. It’s not enough to look at utilization rate over a
period of time

29. Recommendation is based on 40 instances
running 30.32% of the hours in the report
period which is between 1-year break even
point of 26.76% and 40.66% for a m1.small
LINUX in us-east-1b.

30. Recommended Approaches to Purchasing
Reservations
• Base purchase decisions on hourly instance counts of each
instance type per AZ (not aggregate data).
• Frequent reservation purchases help maximize cost
efficiency.
• Don’t over purchase heavy reservations. Utilize Light and
Medium reservations to handle volatility.
• If capacity reservations are important, utilize light reservations
to hold capacity in specific Availability Zones.

31. Thank You!
continue the conversation:
booth 414
web
cloudability.com
email toban@cloudability.com

32. We are sincerely eager to hear
your feedback on this
presentation and on re:Invent.
Please fill out an evaluation form
when you have a chance.