AWS 비용 이해정진 , 영업이사

Asia Pacific Sales and Business DevelopmentSep 26th, 2013

Top 4 TCO (Total Cost of Ownership) Questions

1. “My total cost of hardware is cheaper than AWS”

2. “Will AWS be expensive in a long run?”3. “Cloud is not cost-effective for steady state

workloads”4. “My administration costs are insignificant”

Make sure that we are including all the cost factors into consideration

PlacePowerPipesPeoplePatterns

We offer a service that includes everything in the price

Hardware Vendor Offering

ServerNetwork Hardware

Software OS +VMs

DC/ColoFloor Space

PoweringCooling

Internet Bandwidth

PersonnelAdmins

HWMaintenance

Storage Redundancy

Resource Mgmt SW

Automation

Fixed Cost Factors One-time Upfront Monthly

AWS Co-lo On-Site AWS Co-lo On-Site

Server Hardware 0 $$$ $$ $$ 0 0

Network Hardware 0 $$ $$ 0 0 0

Hardware Maintenance 0 $$ $$ 0 0 0

Software OS 0 $$ $$ $ 0 0

Power and Cooling and Data Center Efficiency

0 0 $$ 0 0 $

Data Center/co-lo Space 0 $$ $$ 0 0 0

Personnel (Administration) 0 $$ $$ $ $$ $$$

Storage and Redundancy 0 $$ $$ $ 0 0

Bandwidth $ $$ $ $$ $ $

Resource Management Software 0 0 0 $$ $ 0

Total

Take all the costs in to consideration

The TCO of Cloud Compute

A TCO Conversation with your customer?

When you turn off your cloud resources, you actually stop paying for them

Cost andDemand

Q1 Q2 Q3 Q4 Q1

wasted capacity

lost customers, ordered hardware

wasted capacity

wasted capacity

wasted capacity

200k

300k

600k

Time

Capacity of resources

Actual demand

Maintaining on-premise infrastructure for peak demand is expensive

DemandAWS

AWS enables companies to match resources to demand

Q1 Q2 Q3 Q4 Q1

200k

300k

600k

Demand

Time

Auto scaling : Types of Scaling

Scaling by Schedule• Use Scheduled Actions in Auto Scaling Service

• Date• Time• Min and Max of Auto Scaling Group Size

• You can create up to 125 actions, scheduled up to 31 days into the future, for each of your auto scaling groups. This gives you the ability to scale up to four times a day for a month.

Scaling by Policy• Scaling up Policy - Double the group size • Scaling down Policy - Decrement by 1

Scale By Hand• Not so auto, but still better than nothing!

11StyleShare, Feb 2013

Typical Mobile Game Traffic

12StyleShare, Sep 2013

Cost Optimization during a day

1 5 9 13 17 21 25 29 33 37 41 45 49

Week

Web

Ser

vers

Weekly CPU Load

Cost Optimization during a year

14쿠키런 , DevSisters, Sep 2013

Elasticity == Savings in Costs

On-Demand

Pay for compute capacity by the hour with no long-term commitments

For spiky workloads, zero upfront

Reserved

Make a low, one-time payment and receive a significant discount on the hourly charge

For committed workloads

Spot

Bid for unused capacity, charged at a Spot Price which fluctuates based on supply and demand

For transient workloads

Dedicated

Launch instances within Amazon VPC that run on hardware dedicated to a single customer

For highly sensitive or compliance-related workloads

Free Tier

Get Started on AWS with free usage & no commitment

For POCs and getting started

$

AWS Offers Options that Fit the Needs

Annual Utilization

On DemandLight Utilization

RIMedium

Utilization RIHeavy Utilization

RI

10% $234 77.95% 210.43% 479.49%

20% $468 18.97% 73.68% 189.74%

30% $702 0.68% 28.09% 93.16%

40% $936 10.51% 5.30% 44.87%

50% $1,170 16.41% 8.38% 15.90%

60% $1,404 20.34% 17.49% 3.42%

70% $1,638 23.15% 24.00% 17.22%

80% $1,872 25.26% 28.89% 27.56%

90% $2,106 26.89% 32.69% 35.61%

100% $2,340 28.21% 35.73% 42.05%

Optimal Savings Sub-Optimal Savings Least Savings

RI Cost Savings over On Demand

M1.large – Linux– 1 Year RI

The breakeven for RIs is surprisingly quick

Sample Cash Flow Summary from RI Analysis

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240

2

4

6

8

10

12

14

On Demand

Light Utilization RI

Medium Utilization RI

Heavy utilization RI

Optimizing costs with RIs

AWS customers use Spot for even greater savings

Best Spot use-cases include any batch-oriented, fault-tolerant application

What are Spot Instances?

Availability Zone

Region

Availability Zone

Unused

Unused

Unused

Unused

Unused

Unused

Sold at 50% Discount!

Sold at 56% Discount!

Sold at 66% Discount!

Sold at 59% Discount!

Sold at 54% Discount!

Sold at 63% Discount!

What is the tradeoff?

Availability Zone

Region

Availability Zone

Unused

Unused

Unused

Unused

Unused

Unused

Reclaimed

Reclaimed

Customers Can Save Up to 92% Off the On-Demand Price

50%50%

57%

63%

50%

66%

50%

CycleCloud runs a HPC Cluster with 30000 cores at $1279/Hour (57% savings)!

Some say the 30th fastest super computer with 1 GiB interconnect

Lucky Oyster crawled 3.4B Web Pages, building a 400M entry index in around 14 hours for $100 (>85% savings)!

Spot Instance Use Cases

Use Case Types of Applications

Batch Processing Generic background processing (scale out computing)

Hadoop Hadoop/MapReduce processing type jobs (e.g., Search, Big Data)

Scientific Computing Scientific trials/simulations/analysis in chemistry, physics, and biology

Video and Image Processing/Rendering

Transform videos into specific formats

Testing Provide testing of software, websites, etc.

Web/Data Crawling Analyzing data and processing it

Financial Hedgefund analytics, energy trading, etc.

HPC Utilize HPC servers to do  embarrassingly parallel jobs

Cheap Compute Backend servers for Facebook games

Optimal Combination of the Pricing Options

Start out risk-free and commitment- free

On-Demand Instances

POCs, Companies that need to preserve cash, Apps constrained by capital

Savings - Purchase Reserved for your Baseline capacity

Reserved + On-Demand

Apps with committed usageBaseline: Use Heavy Peak: On-Demand

More Savings -Convert On-Demand to Light RIs

More Light RI

Apps with predictable usageSpikes: On-Demand

Steady State Usage Pattern

(Example: Corporate Website)

Spiky Predictable Usage Pattern

(Example: Marketing Promotions Website)

Uncertain unpredictable Usage Pattern

(Example: Social game or Mobile Website)

What if …?

http://media.amazonwebservices.com/AWS_TCO_Web_Applications.pdf

AWS offers significant savings in each scenario over an equivalent solution deployed on-premises.

The TCO of Cloud Storage

On-Premises Storage

Raw StorageDisk storage volumes in a box

Usable StorageRAID protection, Formatted Ready

Allocated StoragePre-allocation / Capacity Planning

Utilized StorageDisk storage available to the database, Operating system

Application StorageActual storage used by the application

Allocation

1 PB

1,048,576 GB

80%90%

70%-80%

1,820,133 GB

On-Premises Storage

Raw StorageDisk storage volumes in a box

Usable StorageRAID protection, Formatted Ready

Allocated StoragePre-allocation

Utilized StorageDisk storage available to the database, Operating system

Application StorageActual storage used by the application

Amazon S3

1 PB

It’s Easy to Get an Incomplete and Incorrect Comparison of Cloud and Internal Storage

August 2011 “File Storage Costs Less In The Cloud Than In-House”

The Real Comparison: On-Premises

The Real Comparison: Cloud

25 Price cuts (8 of them related to Storage and Data Transfer)

August 2011 “File Storage Costs Less In The Cloud Than In-House”

$165,840

$251,600Cloud Storage Costs of 100 TB

35%savings

Use Provisioned IOPS

Provisioned IOPS is cheaper than standard IOPS steady state

Proactive cost optimization with Trusted Advisor

Intangible Cost Savings – Take a closer look at what you get

Standardization and Consistency of

HW/SW

Global Footprint and Expansion

Automation and Operational Excellence

Rate of Innovation

Security and Compliance

Deploy

Return on Agility

http://aws.amazon.com/tco-calculator/

Analysts Whitepapers and Resources on TCO of AWS

AMAZON CLOUD INFRASTRUCTURE REPRESENTS A

70%SAVINGS

SAP applications on AWS provides infrastructure savings of up

71%

AWS is a Price

Leader

IDC TCO Study – Business Value Highlights

39 Source IDC Whitepaper, sponsored by Amazon, “The Business Value of

Amazon Web Services Accelerates Over Time.” July 2012

감사합니다 !

info-kr@amazon.comaws.amazon.com/ko/economics