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(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.
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The Science Behind Choosing Reserved Instances
Toban Zolman, Cloudability
November 13, 2013
Introduction
• Understanding reservations
• Simplifying Reserved Instance purchases while maximizing ROI
• Recommended approach to purchasing reservations
8000+ Companies • $600M+ managed cloud spending
Our Solution
The Science of Purchasing Reservations
Is your company currently purchasing AWS reservations?
Most people over-simplify reservation purchasing
RESULT: Reserved Instance purchases misalign to your needs reducing ROI
Go all in on 1 or 2 large buys each year
Result: Large cliffs in reservation levels
How frequently are you purchasing reservations?
Reservations 101
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 Database CDN
Amazon DynamoDB
Amazon RDS
Amazon Redshift
Amazon ElastiCache
Amazon EC2 Amazon CloudFront
Why make reservations?
1. Lower the cost of resources you are already using Reservations provide substantial cost savings versus “on-demand” pricing.
Cost Savings vs On-Demand Comparison
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%
There are 2,000+ different reservation types each with their own breakeven points.
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.
Why are you currently purchasing Reserved Instances?
Reserved Instance Pricing Components
Reservation Type Upfront Fee Hourly Usage Fee Minimum Usage Level
Light Yes Yes 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.
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.
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
A Simplified Example of Calculating Reservation Needs
Running Instances by Hour of the 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
(example assumes 10 hours in month)
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%
8 2 20%
9 1 10%
10 1 10%
11 1 10%
12 1 10%
Break even point for Heavy
Break even point for Medium
Break even point for Light
It’s not enough to look at utilization rate over a period of time
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.
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.
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.
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