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Getting to MVP (Minimum Viable Product)
Traditional World customer is known
features are known
solution is known
Traditional World
is not where we live
Most startups Know the problem, but not the solution
Many don't even know precisely what
problem they solve
Lean Startups:
LEARN & ADAPT
1. Focus on a simple implementation of your idea
1. Focus on a simple implementation of your idea
2. Start with a minimal core set of features
1. Focus on a simple implementation of your idea
2. Start with a minimal core set of features
3. Release and listen to your users
1. Focus on a simple implementation of your idea
2. Start with a minimal core set of features
3. Release and listen to your users
Minimum Viable Product
MVP Smallest thing I can do to test my idea?
a prototype shouldn't require big investments
It should be cheap and validate ideas
This Session
From 0 to MVP in 30 minutes
What matters most?
Cost of Innovation
Focus
« Want to increase innovation?
Lower the cost of failure »
Joi Ito
AWS enables you to
Fail Forward
Fail Faster
Fail Cheaper
Product Development
MVP
Time
Scale
Innovation & Iteration
MVP
Time
Scale
Innovation & Iteration
Time
Scale
Started: burbn, location-based mobile
app. Photo sharing is just one feature
Now: re-written as
photo app. Sold to FB
for 1bn
Innovation & Iteration
Time
Scale
Started: odeo, site to create & share
podcasts
Now: micro-blogging,
500M users, >10Bn
valuation
Innovation & Iteration
Time
Scale
Started: developed 51 games, none very
successful. But then game 52…
Now: raised $42M,
downloaded 1B times,
25% paid, best sold
game on AppStore
“Timing, perseverance, and ten years of trying
will eventually make you look like an overnight
success.”
Biz Stone, Twitter co-founder
AWS lowers the cost of Innovation
Time
Scale
Scenario Small team with initial idea for Mobile app
3 months to get to launch
Unknown customer/problem/solution
No cash….
Dev / Test Environment
Time
Scale
Average Spend
$0 p/m
Alpha Release
Time
Scale
Average Spend
$15 p/m
Beta Release / MVP
Time
Scale
Average Spend
$235 p/m
Getting to MVP for $250
Time
Scale
Total Spend to MVP
$250 $235 $15 $0
• 3 months dev/test/release
• Serving Beta customers
• Ready for full production
and scale
Your application
Your business & what makes you unique
Innovation, not undifferentiated heavy lifting
Spending developer time in the right place
Automate as much as you can
(Deep insight alert: Developer Time = Money)
FOCUS!
Build apps, not infrastructure
"Startups are all about focus. AWS enables focus" Ray Bradford, Kleiner Perkins, Caulfield & Byers
“Your users around the world don’t
care that you wrote your own DB”
Mike Krieger, Instagram Cofounder
AWS OpsWorks
AWS CloudFormation
AWS Elastic Beanstalk
DevOps framework
for application
lifecycle management
and automation
Templates to deploy
& manage template-
driven provisioning
Automated
resource
management – web
apps made easy
DIY / On Demand
DIY, on demand
resources: EC2, S3,
customer AMI’s, etc.
Control Convenience
Focus requires Automation
DEMO Your MVP on AWS Elastic Beanstalk
What’s AWS Elastic Beanstalk?
User Application
Application Service
HTTP Service
Language Interpreter
Operating System
Host
We Create the EC2 Instance You Focus on Developing Your App
Flexibility to Choose your Stack
We’re going to build this…
Thank You aws.amazon.com/start-ups
aws.amazon.com/ko/activate
Getting to MVP Frograms
frograms
TITLE
내 취향을 분석하는 영화추천 서비스 왓챠
어떤 영화를 볼 지 선택할 때, 취향을 분석하여 좋아할만한 영화를 추천해 주는 개인화 서비스
내 취향을 분석하는 영화추천 서비스 왓챠
베타 버전 개발 (Beta Dev Stage)
Traditional Hosting Provider
• 한대의 서버에 App서버 DB서버 함께 사용
• Loosely Coupled Architecture 필요
• Vertical Scaling (서버 스펙 업그레이드) 어려움
• Horizontal Scaling (서버 수량 증가) 어려움
• App서버 1대 DB서버 1대
• 시간 부족으로 인한 Time To Market 중요
• 사용자 유입 속도 예측 불가
• 빠르게 이용자 요구에 대처 할 수 있는 능력 필요
베타서비스 시작 (Beta Service on AWS)
App Server m1.large
DB Server m1.medium
So, We started with Simple Architecture
애플리케이션 서버 (Scale Up/Down)
AMI
App Server
m1.large m1.xlarge
• Ruby on Rails 웹 애플리케이션
• 모바일 API 개발
• 인스턴스 타입 변경이 수분안에
가능
• AMI (Amazon Machine Image)를
통한 인스턴스 타입 업그레이드
Right Instance Type
애플리케이션 서버 (Customized AMI)
애플리케이션 서버 (Rapidly Scale Out/In)
Elastic Load Balancer
App Servers
With • 순간적으로 폭증하는 트래픽
• SES를 통한 대량 Email 발송처리
• 수분만에 Spot Instance 추가
• 트래픽 처리 끝난 후 모두 제거
Marketing Promotion
m3.xlarge
데이터 베이스 (Test & Apply)
Extra Large Large Medium
• 실시간 Modify 를 통한 무중단 업그레이드
App Servers
• 초창기 단순 구조, Read Replica 1-click 추가
또한, 그 외에도…
Application Server
Database Server
추천서버 Cache 서버 Search 서버
m3.xlarge On-demand
Spot Instance
Extra Large Read Replica
M1.xlarge
추천 관련된 모든 역할을 담당하는 서버 DB, 캐시서버, 어플리케이션 서버와 통신
m1.xlarge
Redis, Memcached
m1.xlarge
Sphinx
Next Step with AWS
“앞으로 개개인에게 특화된 '개인화' 서비스에 미래가 있다고 생각해요. 영화 뿐만 아니라 개인화 할 수 있는 것들은 무궁무진합니다.
이러한 분야에서 빠른 시장진입을 위해서 AWS가 많은 도움을 줄것입니다.”
드라마
영화
게임 뉴스
음악
문화컨텐츠
동영상
쇼핑
공연
맛집
Innovators Needed !!
경험 많은 서버/백엔드 개발자
Machine Learning 전공자
Getting to Scale
503 Service Temporarily Unavailable
The server is temporarily unable
to service your request due to
maintenance downtime or capacity
problems. Please try again later.
With AWS, scale from one instance…
…to thousands
Fully automated!
BUT…
How do I scale my architecture to
support my first 10M users?
“Think Big, Start Small, Scale Fast”
Eric Ries, author of NY Times
bestseller “The Lean Startup”
01 02 03 04
Idea MVP Profitability Scale
Getting to Scale
By building a scalable Architecture to
support your first 10M users
1. Dev & Test
2. Alpha Release
3. Beta Release
Production 1.0
Architecture
Database Options
Self-Managed Fully-Managed
Database Server
on Amazon EC2
Your choice of
database running on
Amazon EC2
Bring Your Own
License (BYOL)
Amazon
DynamoDB
Managed NoSQL
database service
using SSD storage
Seamless scalability
Zero administration
Amazon RDS
Relational Database
as a managed
service
Flexible licensing:
BYOL or License
Included
But how do I choose what
DB technology I need?
SQL? NoSQL?
Some folks won’t like this.
But…
Start with SQL databases
But, but, but, but…
No. You don’t.
Start with SQL databases
Established and well worn technology
Lots of existing code, communities, books, tools, etc
Clear patterns to scalability
You aren’t going to break SQL DBs in your first 10 million users. No really, you won’t
Why SQL?
• Database-as-a-Service
• No need to install or manage database
instances
• Scalable and fault tolerant configurations
Feature Details
Platform support Create MySQL, SQL Server and Oracle
Preconfigured Get started instantly with sensible default settings
Automated patching Keep your database platform up to date automatically
Backups Automatic backups and point in time recovery using snapshots Manual DB snapshots
Failover Automated failover to slave hosts in event of a failure
Replication Easily create read-replicas of your data and seamlessly replicate data across availability zones
Amazon Relational Database Service (RDS)
Automatic resizing of
compute clusters based on
demand Trigger auto-scaling policy
Feature Details
Control Define minimum and maximum instance pool sizes and when scaling and cool down occurs.
Integrated to Amazon CloudWatch
Use metrics gathered by CloudWatch to drive scaling.
Instance types Run Auto Scaling for On-Demand and Spot Instances. Compatible with VPC.
as-create-auto-scaling-group MyGroup
--launch-configuration MyConfig
--availability-zones us-east-1a
--min-size 4
--max-size 200
Auto-Scaling Amazon CloudWatch
Production 1.0 Architecture
Production 1.0 Architecture
Well-designed, 2 Tier architecture
Highly Available due to Multiple Availability Zone
Load Balancing & Auto-Scaling for full scalability
Fully managed Database included
Capable of serving >10K-100Ks users
BUT…
Production 1.0 Architecture
Wasted server capacity for static content
Reliability and durability are not yet optimal
End-user experience could be improved thru offloading & caching
SO…
Let’s add
Simple Storage Service (S3)
CloudFront to optimize the end-user experience
Durable storage, any object
99.999999999% durability of objects
Unlimited storage of objects of any type
Up to 5TB size per object
Feature Details
Flexible object store Buckets act like drives, folder structures within
Access control Granular control over object permissions
Server-side encryption 256bit AES encryption of objects
Multi-part uploads Improved throughput & control
Object versioning Archive old objects and version new ones
Object expiry Automatically remove old objects
Access logging Full audit log of bucket/object actions
Web content hosting Serve content as web site with built in page handling
Notifications Receive notifications on key events
Import/Export Physical device import/export service
Simple Storage Service (S3)
• World-wide content distribution
network
• Easily distribute content to end
users with low latency, high data
transfer speeds, and no
commitments Feature Details
Fast Multiple world-wide edge locations to serve content as close to your users as possible
Integrated with other services Works seamlessly with S3 and EC2 origin servers
Dynamic content Supports static and dynamic content from origin servers
Streaming Supports rtmp from S3 and includes support for live streaming from Adobe FMS and Microsoft Media Server
CloudFront
Production 1.2
Architecture
Production 1.2 Architecture
Well-designed, 2 Tier architecture
Highly Available due to Multiple Availability Zone
Load Balancing & Auto-Scaling for full scalability
Fully managed Database included
Static content stored in durable, consistent way
Improved end-user experience through CDN
Capable of serving >100K-1M+ users
BUT…
Production 1.2 Architecture
You are now at Scale…
…with lots of data…
…and need to optimize continuously.
But how and where?
SO…
Let’s add
Big Data for analytics of web, mobile, gaming,
and log data
Multiple managed AWS services for Big Data
• Managed, elastic Hadoop cluster
• Integrates with S3 & DynamoDB
• Leverage Hive & Pig analytics scripts
Feature Details
Scalable Use as many or as few compute instances running Hadoop as you want. Modify the number of instances while your job flow is running
Integrated with other services
Works seamlessly with S3 as origin and output. Integrates with DynamoDB
Comprehensive Supports languages such as Hive and Pig for defining analytics, and allows complex definitions in Cascading, Java, Ruby, Perl, Python, PHP, R, or C++
Cost effective Works with Spot instance types
Monitoring Monitor job flows from with the management console
Elastic MapReduce (EMR)
Foursquare… Founded in 2009 112M in Venture Capital 33 million users 1.3 million businesses using the service
…generates a lot of Data 3.5 billion check-ins 15M+ venues, Terabytes of log data
Uses EMR for Evaluation of new features
Machine learning
Exploratory analysis
Daily customer usage reporting
Long-term trend analysis
Benefits of EMR
Ease-of-Use “We have decreased the processing time for urgent data-analysis”
Flexibility To deal with changing requirements & dynamically expand reporting clusters
Costs “We have reduced our analytics costs by over 50%”
Production 1.3
Architecture
Production 1.3 Architecture
Well-designed, 2 Tier architecture
Highly Available due to Multiple Availability Zone
Load Balancing & Auto-Scaling for full scalability
Static content stored in durable, consistent way
Improved end-user experience through CDN
Big Data analytics built in for continuous optimization
Capable of serving >1m-10M+ users
DEMO Getting to Scale
Thank You aws.amazon.com/start-ups
aws.amazon.com/ko/activate
Getting to Scale
2011. 9
2013. 9
Architecture on AWS
S3 Bucket
ELB Amazon SES Worker
Database
Client
CloudFront
Search Engine AMIs Route53 Monitoring ElastiCache
Web
MQ
Elastic Compute Cloud
Elastic Compute Cloud
~5 Instances
~32 Instances
Elastic Load Balancer
HTTPS Request HTTP
CloudFront
CloudFront
ElastiCache
ElastiCache
Getting to Profitability
Time
Usage
Page Views
Revenue
Etc.
The Infamous Hockey Stick
Time
Usage
Page Views
Revenue
Etc.
The Infamous Hockey Stick
Costs
You want only 3 things
Revenue to go Up
Unit Costs to go Down
Margin to go Up
Time
Usage
Page Views
Revenue
Etc.
The Infamous Hockey Stick
Costs
How does AWS help here?
Economies of Scale
Pricing Models
Cost Aware Architecting
What does this look like in
the real world?
An example
Enterprise software provider in APAC
Focused on SaaS for storage, security, collaboration, etc.
Backed by leading VC’s in the region
Strong growth – winning customers globally
Focused on profitability & reducing unit costs
Worked closely with the AWS team to optimize its architecture
Margin
Growth
-10%
price drop
in S3
-20%
RI purchase
-22%
Migration
Cassandra
to Dynamo
-18%
Price drop in
S3 of 25%
54%
reduction in
unit costs
“Based on a True Story”
01 02 03 04
Idea MVP Profitability Scale
Getting to Profitability 03 04
Profitability Scale
Pricing Models
Cost Aware Architecting
Total Cost of Ownership
On-Demand
Pay for compute
capacity by the hour
with no long-term
commitments
For spiky workloads,
or to define needs
Cost Optimization using different purchase models
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
For time-insensitive or
transient workloads
Free Tier
Get Started on AWS
with free usage & no
commitment
For POCs and
getting started
aws.amazon.com/ko/activate
Reserved Instance Pricing
Make a low, one-time payment and receive a
significant discount on the hourly charge
For committed utilization
•Light Utilization RI
•Medium Utilization RI
•High Utilization RI
•1-year
•3-year
2 Terms 3 Versions
Reserved Instance Pricing
Utilization RI option Savings over On-Demand
<10% On-Demand
10% - 40% Light Utilization RI Up to 56%
40% - 75% Medium Utilization RI Up to 66%
>75% Heavy Utilization RI Up to 71%
• Most traffic happens in the afternoons and evenings, so they reduce the number of
instances at night by 40%.
• At peak traffic $52 an hour is spent on EC2 and at night, during off peak, the spend is as
little as $15 an hour. Saving per hour = 71%
Save more money by using Spot Instances
Up to 85% savings over On Demand pricing
Spot market for under-utilized capacity Requested Bid Price and Pay as you go
Spot Price < On-Demand Price
Use Case Types of Applications
Batch Processing Generic background processing (scale out computing)
Hadoop Hadoop/MapReduce processing type jobs (e.g. Search, Big Data, etc.)
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, web sites, 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
Use Cases for Spot Pricing
Optimizing Video Transcoding Workloads
for a FREEMIUM model
Free Offering Optimize for reducing cost
Acceptable Delay Limits
Implementation – Leverage spot pricing
– Maximum Bid Price
– < On-demand Rate
– Use on-demand Instances, if delay
Get strongly reduced price for your workload
Premium Offering Optimized for Faster response
No Delays
Implementation
– Invest in Reserved Instances
– Use on-demand for Elasticity
Get Instant Capacity for higher price
Getting to Profitability 03 04
Profitability Scale
Pricing Models
Cost Aware Architecting
Total Cost of Ownership
“Give me 4 fault tolerant algorithms and I can pick
the best one almost with my eyes closed.
If you then ask me which one is best for the
business, in terms of dollar costs, I would be
clueless...”
Werner Vogels, CTO, Amazon
Cost optimization through ‘Cost Aware Architecting’
…by leveraging: Reduce Cost of…
Compute 1. S3 & CloudFront for Caching & Offloading
Storage 3. Storing derivative objects in S3 ‘Reduced Redundancy’
Database 4. Read Replicas and/or ElastiCache
Test & Dev 5. Rapid proto-typing & Lean Dev/Test
2. Auto-Scaling done Right
1. S3 & CloudFront for Caching & Offloading
• Reduce your compute demand and costs
• Improve end-user experience
• Increase reliability and durability
Cost Aware Architecting to Reduce costs of EC2
1. S3 & CloudFront for Caching & Offloading
Cost Aware Architecting to Reduce costs of EC2
1. S3 & CloudFront for Caching & Offloading
Cost Aware Architecting to Reduce costs of EC2
1. S3 & CloudFront for Caching & Offloading
Cost Aware Architecting to Reduce costs of EC2
1. S3 & CloudFront for Caching & Offloading
Cost Aware Architecting to Reduce costs of EC2
2. Auto-Scaling done Right with Real Time reaction response
• Elastic Load Balancing and (event-driven) Auto Scaling
• Notification of pending news flash (with audible alarm)
• On-demand ramp up of capacity (6 mins.)
• Subscriber alert push delivered
• Mass response traffic handled (followed by ramp down)
Cost Aware Architecting to Reduce costs of EC2
Buuuk for Singapore Press Holding (SPH)
2. Auto-Scaling done Right with Real Time reaction response
Cost Aware Architecting to Reduce costs of EC2
Straits Times Buuuk
2. Auto-Scaling done Right with Real Time reaction response
Cost Aware Architecting to Reduce costs of EC2
2. Auto-Scaling done Right with Real Time reaction response
Cost Aware Architecting to Reduce costs of EC2
2. Auto-Scaling done Right with Real Time reaction response
Cost Aware Architecting to Reduce costs of EC2
2. Auto-Scaling done Right with Real Time reaction response
Cost Aware Architecting to Reduce costs of EC2
3. Storing derivative objects in S3 ‘Reduced Redundancy’
• Original vs. derived assets : 33% savings
• Single reference and consistency
• Control, accurate logs and tracking
Cost Aware Architecting to Reduce costs of S3
Reduced Redundancy Storage
‘RRS’
4. Read Replicas and/or ElastiCache (‘Database Smarts’)
• Scale out and share work
• Optimal performance, minimize load
• Enhance reliability, ensure data safety
• Cost reduction
Cost Aware Architecting to Reduce costs of DB
5. Rapid proto-typing & Lean Dev/Test
• Inexpensive idea validation
• Seamless switch over and versioning
• Rapid dev / test agility
Cost Aware Architecting to Reduce costs of Test/Dev
Getting to Profitability 03 04
Profitability Scale
Pricing Models
Cost Aware Architecting
Total Cost of Ownership
When calculating TCO…
#1 Start by understanding your use cases & usage patterns
Traditional HW / Hosting
On and Off Fast Growth
Predictable peaks Variable peaks
WASTE
CUSTOMER DISSATISFACTION
AWS = Elastic Capacity
Fast Growth On and Off
Predictable peaks Variable peaks
When calculating TCO…
#1 Start by understanding your use cases & usage patterns
#2 Apples to Apples – Take all the fixed costs into consideration
When calculating TCO…
#1 Start by understanding your use cases & usage patterns
#2 Apples to Apples – Take all the fixed costs into consideration
#3 Leverage ‘Cost Aware Architecting’ to reduce resources
0
10
20
30
40
50
60
Hosting
Traditional Hosting vs AWS
# of
(virtual)
servers
Offload
to S3
Caching
with CF
Auto-
Scaling Etc. Hosting
When calculating TCO…
#1 Start by understanding your use cases & usage patterns
#2 Apples to Apples – Take all the fixed costs into consideration
#3 Leverage ‘Cost Aware Architecting’ to reduce resources
#4 Include pricing models (RI, Spot) and economies of scale
Margin
Growth
-10%
price drop
in S3
-20%
RI purchase
-22%
Migration
Cassandra
to Dynamo
-18%
Price drop in
S3 of 25%
54%
reduction in
unit costs
“Based on a True Story”
When calculating TCO…
#1 Start by understanding your use cases & usage patterns
#2 Apples to Apples – Take all the fixed costs into consideration
#3 Leverage ‘Cost Aware Architecting’ to reduce resources
#4 Include pricing models (RI, Spot) and economies of scale
#5 Take a look at what’s included: Intangible Cost Savings !
New Customers Amazon EC2
Amazon RDS
Amazon ELB
Amazon S3
Amazon EBS
For All Customers Amazon SQS/SNS
Amazon DynamoDB
Amazon SES
Amazon SWF
And more…
AWS Elastic Beanstalk
AWS CloudFormation
AWS IAM
Auto Scaling
Consolidated Billing
No Charge for
Inbound Data Transfer
Data Transfer between
Instances within an
Availability Zone
Free Usage Tier
Did you know?
Free Services Data Transfer
Trusted Advisor
A premium security spec at non-premium
prices
• Security groups for EC2
and VPC
Network ACL
• Multi-Factor Authentication
• CloudHSM
• RDS Oracle transparent
encryption
• VPC
• Direct connect
• Dedicated instances
• Identity & Access
Management
• S3 Encryption
DEMO Getting to Scale
Off-loading of static content to CloudFront to
reduce required server capacity
So what does this mean in terms of costs?
Month
Medium EC2 instances 1 $ 121
CloudFront Data Transfer Out 1Tb $ 168
CloudFront Requests $1.89
TOTAL $ 291
Month
Medium EC2 instances 4 $ 485
AWS Data Transfer Out 1Tb $ 194
TOTAL $ 679
Standard Architecture Optimized Architecture
57% lower cost – 6 x faster
Thank You aws.amazon.com/start-ups
aws.amazon.com/ko/activate
Getting to Profitability on AWS
the beatpacking company
초기
투자비용
인력
안정성
스타트업 인프라 선택의 고려요소
MONEY
AWS 비용 구조
대부분의 경우 가장 많은 부분을 차지
Amazon
EC2
EC2 절약의 2가지 키워드
24 시간 내내 같은 양의 인스턴스를 사용할 필요가 없다.
EC2 절약의 2가지 키워드
On-Demand와 멀어질 수록 비용은 최적화 된다.
AWS EC2 Instance Types
On-Demand
• Pay As You Go • 원하는 언제든 생성/삭제 가능 • 시간당 가장 비싸게 이용
AWS EC2 Instance Types
Reserved
• 1년 혹은 3년의 기간 + 사용 정도로 미리 약정 • On-Demand 대비 저렴한 시간당 요금 • 계약하는 만큼 언제든 이용 가능 • 초기 선결제 금액
AWS 가용영역에 존재하는 여유 자원을 경매를 통해 이용
인스턴스 생명 주기와 수량을 통제할 수 없음
EC2 Spot Instance
EC2 Spot Instance
하지만, 잘만 활용하면 최대 80% 정도 비용 감축 가능
요금 비교
시간당(달러)
시간당(원) 할인율
On-Demand $0.740 \792.48
Reserved/1yr $0.511 \547.49 -31%
Reserved/3yr $0.358 \383.56 -51%
Spot $0.192 \205.71 -74%
AWS Tokyo Region / 1a / c1.xlarge / 2013-10-12 환율 기준 Reserved Heavy Utilization, 선결제 금액을 시간당 환산 반영
EC2 Spot Instance
c1.xlarge / us-east
EC2 Spot Instance
c1.xlarge / us-east
EC2 Spot Instance
• 가용영역에 따라 서로 다른 가격 • 가용영역에 따른 서로 다른 패턴
• 반면 어떤 가용영역은 계속 안정된 가격 흐름을 보인다
• 주된 가용영역 선택에 있어 고려 요소
EC2 Spot Instance – 입찰 전략
• On-Demand 가격에 입찰하여 가격 통제
• 그 시각 최저가로 낙찰되므로 무조건 저액을 써낼 필요는 없음
EC2 Spot Instance
c1.xlarge / ap-northeast-1
EC2 Spot Instance
Spot의 단점인 인스턴스 생명주기를 관리하지 못하는 점 AutoScaling 전략을 통해 극복
Auto Scaling
EC2 Spot Instance + AutoScaling
On-Demand Group Spot Group
• 부하 증가에 천천히 반응하여 Scale-Up
• 부하 감소에 빠르게 반응하여 Scale-Down
• 부하 증가에 빠르게 반응하여 Scale-Up
• 부하 감소에 천천히 반응하여 Scale-Down
Spot 인스턴스 위주로 부하를 수용하고, Spot 인스턴스 부족분을 On-Demand 로 수용
EC2 Spot Instance + AutoScaling
6:00 9:00 12:00 15:00 18:00 21:00 0:00
On-Demand Spot Load
Spot : 5분간 평균 CPU이용률 40% OD : 5분간 평균 CPU이용률 60%
EC2 Spot Instance + AutoScaling
6:00 9:00 12:00 15:00 18:00 21:00 0:00
On-Demand Spot Load
Spot 확보에 실패한 경우 On-Demand가 Scale-Up
Spot 확보에 따른 On-Demand Scale-Down
EC2 Spot Instance + AutoScaling
301.92
68.448 59.144
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On-Demand On-Demand + Spot RI(1yr) + Spot
BEAT API 서버 비용 비교
일 비용($)
77%
( 세줄)정리
• Spot 인스턴스를 최대한 활용하여 비용 절감 • Spot 인스턴스의 단점을 AutoScaling 전략으로 커버 • 어느 정도 부하 패턴이 일정해 지면
On-Demand 인스턴스를 RI 인스턴스로 변경