the science behind choosing aws reserved instances

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The Science Behind Choosing Reserved Instances

@cloudability

Today’s TopicsIntroduction

1. Purchasing Pitfalls

2. Understanding Reservations

3. How to calculate RIs

4. Recommended RI purchase approach

Toban Zolman VP of Product Development

TODAY’S SPEAKER

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WARNING: Math ahead.

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Infrastructure analytics for scaled web businesses and enterprises.

Cloud Infrastructure AnalyticsAbout Us

650M+ in tracked cloud costs. 8,000+ Users

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Our SolutionHow It Works

1 2 3

4 5

Spend Management Spending visibility via monthly forecasts, dash-board, budget alerts, and daily email digests.

Cost Analytics Dig into your operating costs with detailed costs by tag, service, and usage type. !

EC2 Usage Analytics Spot under-utilized resources w/ instance level usage metrics. !!

RI Purchase Analytics Understand the exact combination of Reserved Instances that will maximize your savings. !

Enterprise Enablement Organizational group views/filtering/rollups, multi-user access. !

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We Collect We pull data directly from public cloud provider APIs.

We Store We warehouse your historical data.

You Access You log into cloudability.com to access analytics. !

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Purchasing Pitfalls

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Is your company currently purchasing AWS reservations?

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Most companies over simplify reservation purchasing

What we’ve learned:

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RESULT: RI purchases misalign to your needs reducing ROI

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Go all in on 1 or 2 large buys each year

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Result: Large cliffs in reservation levels

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How frequently are you purchasing reservations?

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Understanding Reservations

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COMPUTE

Amazon EC2

DATABASE

DynamoDB

RDS

Redshift

Elasticache

CDN

CloudFront

What is a reservation?Understanding Reservations

Reservations allow you to reserve resources/capacity for one or three years in a particular availability zone in exchange for a lower overall unit price.

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Why make reservations?Understanding Reservations

1. Lower the cost of resources you are already usingReservations provide substantial cost savings versus “on-demand” pricing.

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RI Cost Savings vs. On-DemandUnderstanding Reservations

There are 2,000+ different reservation types each with their own “break-even” points.

LINUX m1.xlarge instance - over 3 years

Annual Utilization Rate Light RI Savings Rate Medium RI Savings Rate Heavy RI Savings Rate

20% 25% -7% -77%

40% 40% 33% 11%

60% 45% 46% 41%

80% 48% 52% 56%

100% 49% 59% 65%

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Why make reservations?Understanding Reservations

1. Lower the cost of resources you are already usingReservations provide substantial cost savings versus “on-demand” pricing.

2. Lock-in future capacity in the same Availability Zone Very useful if you experience bursts/spikes in usage

3. Reserve capacity in another region just in case...Outages could cause a run on capacity. Reservations ensure you get seat at the table.

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Why are you purchasing reserved instances?

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Reserved Instance Pricing Components

Reservation Type Upfront Fee Hourly Usage Fee Minimum Usage Level

Light Yes YesNone If the instance is not used during the hour, there is no charge.

Medium Yes YesNone If the instance is not used during the hour, there is no charge.

Heavy Yes YesYes Billed a full month’s worth of hours at the start of each month.

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How are reservations applied?

• Reserved Instances are purchased for an instance type (m1.xlarge) with a specified OS (LINUX) 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.


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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


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Changing Instance Type

Instance Size Normalization Factor

small 1

medium 2

large 4

xlarge 8

2xlarge 16

4xlarge 32

8xlarge 64


1 xlarge g 2 large 1 large g 4 small

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Instance types without a family

• t1.micro !

• cc1.4xlarge !

• cc2.8xlarge !

• cg1.8xlarge !

• cr1.8xlarge !

• hi1.4xlarge !

• hs1.8xlarge


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The Fine Print

• Transfers do not happen automatically

• Transfers are not guaranteed and are based on available capacity


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A Simplified RI Calculation

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Overall utilization can be misleadingA Simplified RI Calculation

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m1.large linux us-east-1a A tale of three instances

30% 30% 30%

30% is greater than the break even point for a light reservation

1 2 3

3 Light

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When were the instances running?A tale of three instances

Remember: Reservations are applied every hour

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Instances running at the same time

If the instances are running at the same time you need multiple RIs

Sun Mon Tue Wed Thu Fri Sat

1 2 3 4 5 6 7

8 9 10 11 12 13 14

15 16 17 18 19 20 21

22 23 24 26 27 28 29

30

A tale of three instances

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3 Light reservations cost savingsA tale of three instances

On-demand hourly cost $0.240

RI hourly cost $0.136

RI upfront fee $243

Effective hourly rate @ 30% utilization $0.228

Hourly Savings $0.011

Total Savings for this example $90.93

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4.8%

SAVINGS RATE

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Instances running at different times

Sun Mon Tue Wed Thu Fri Sat

1 2 3 4 5 6 7

8 9 10 11 12 13 14

15 16 17 18 19 20 21

22 23 24 26 27 28 29

30

A tale of three instances

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Instances running at different timesA tale of three instances

Collectively the 3 instances cover 90% of the hours of the month

21

3

Heavy

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1 Heavy reservation cost savingsA tale of three instances

On-demand hourly cost $0.240

RI upfront fee $676

RI hourly cost $0.056

Effective hourly rate @ 90% utilization $0.141

Hourly Savings $0.098

Total Savings for this example $774.65

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41%

SAVINGS RATE

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1 Heavy vs. 3 LightsA tale of three instances

1 Heavy 3 Lights

Total Savings $774.65 $90.93

Total upfront fees $676 $729

Buying 3 lights would have wasted $486 in upfront fees

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You have to understand how many instances are running each hour to know how many RIs to purchase

Applying what we’ve learned:

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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 the month)

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Hourly Frequency Distribution of Instance Levels

Running Instance Count Frequency of Occurrence Frequency %

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

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Put it into practice!(demo time)

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Purchasing Recommendations

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Implications for savings

• Base purchase decisions on hourly instance counts of each instance type per Availability Zone (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

Purchasing Recommendations

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Thank You

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