AWS Cloud Kata | Taipei - Getting to Profitability

The Infamous Hockey Stick
Usage
Page Views
Revenue
Etc.

Time

Usage
Page Views
Revenue
Etc.

Costs

Time

Revenue to go Up
Unit Costs to go Down
Margin to go Up

Usage
Page Views
Revenue
Etc.
Costs

Time

Economies of Scale
Pricing Models
Cost Aware Architecting

What does this look like in
the real world?

An example
!
!
!
!
!
!

 
 
 
 
 
 

Enterprise
so+ware
provider
in
APAC

Focused
on
SaaS
for
storage,
security,
collabora=on,
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
op=mize
its
architecture

“Based on a True Story”
Margin
Growth

54%
reduction in
unit costs

-20%
-10%
price drop RI purchase
in S3

-22%
Migration
Cassandra
to Dynamo

-18%
Price drop in
S3 of 25%

Idea

MVP

Scale

Profitability

01

02

03

04

Scale

Getting to Profitability

Profitability

03

04

Pricing Models
Cost Aware Architecting
Total Cost of Ownership

Cost Optimization using different purchase models
Free Tier

On-Demand

Reserved

Spot

Get Started on AWS
with free usage & no
commitment

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

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

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

For POCs and
getting started

For spiky workloads,
or to define needs

For committed
utilization

For time-insensitive or
transient workloads

Reserved Instance Pricing
Make a low, one-time payment and receive a
significant discount on the hourly charge
For committed utilization
3 Versions
• Light Utilization RI
• Medium Utilization RI
• High Utilization RI

2 Terms
• 1-year
• 3-year

Reserved Instance Pricing
U"liza"on

RI
op"on

Savings
over
On-‐Demand

<10%

On-‐Demand

10%
-‐
40%

Light
U=liza=on
RI

Up
to
56%

40%
-‐
75%

Medium
U=liza=on
RI

Up
to
66%

>75%

Heavy
U=liza=on
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
Spot
market
for
under-‐
u=lized
capacity

Requested
Bid
Price
and

Pay
as
you
go

Spot
Price
<
On-‐Demand
Price

Up
to
85%
savings
over
On
Demand
pricing

Use Cases for Spot Pricing
Use
Case

Batch
Processing

Types
of
Applica"ons

Generic
background
processing
(scale
out
compu=ng)

Hadoop

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

Scien"fic
Compu"ng

Scien=fic
trials/simula=ons/analysis
in
chemistry,
physics,
and
biology

Video
and
Image
Processing/
Rendering

Tes"ng

Transform
videos
into
specific
formats

Web/Data
Crawling

Financial

HPC

Analyzing
data
and
processing
it

Hedgefund
analy=cs,
energy
trading,
etc

U=lize
HPC
servers
to
do

embarrassingly
parallel
jobs

Cheap
Compute

Backend
servers
for
Facebook
games

Provide
tes=ng
of
so+ware,
web
sites,
etc

Optimizing Video Transcoding Workloads
for a FREEMIUM model
Premium Offering

Free Offering
Optimize for reducing cost
Acceptable Delay Limits

Optimized for Faster response
No Delays

Implementation
– 
– 
– 
– 

Leverage spot pricing
Maximum Bid Price
< On-demand Rate
Use on-demand Instances, if delay

Get strongly reduced price for your
workload

Implementation
–  Invest in Reserved Instances
–  Use on-demand for Elasticity

Get Instant Capacity for higher price

“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’
Reduce Cost of…
Compute

…by leveraging:
1. S3 & CloudFront for Caching & Offloading
2. Auto-Scaling done Right

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

Cost Aware Architecting to Reduce costs of EC2
•  Reduce your compute demand and costs
•  Improve end-user experience
•  Increase reliability and durability

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)

Buuuk for Singapore Press Holding (SPH)


Buuuk

Straits Times

Cost Aware Architecting to Reduce costs of S3
3. Storing derivative objects in S3 ‘Reduced Redundancy’
•  Original vs. derived assets : 33% savings
•  Single reference and consistency
•  Control, accurate logs and tracking

Reduced Redundancy Storage
‘RRS’

Cost Aware Architecting to Reduce costs of DB
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 Test/Dev
5. Rapid proto-typing & Lean Dev/Test
•  Inexpensive idea validation
•  Seamless switch over and versioning
•  Rapid dev / test agility

When
calcula"ng
TCO…

#1
Start
by
understanding
your
use
cases
&
usage
paUerns

Tradi=onal
HW
/
Hos=ng

WASTE

On and Off

Fast Growth

Variable peaks

Predictable peaks

CUSTOMER DISSATISFACTION

AWS
=
Elas=c
Capacity

On and Off

Fast Growth

Variable peaks

Predictable peaks

When
calcula"ng
TCO…

#1
Start
by
understanding
your
use
cases
&
usage
paUerns

#2
Apples
to
Apples
–
Take
all
the
ﬁxed
costs
into
considera"on

When
calcula"ng
TCO…

#1
Start
by
understanding
your
use
cases
&
usage
paUerns

#2
Apples
to
Apples
–
Take
all
the
ﬁxed
costs
into
considera"on

#3
Leverage
‘Cost
Aware
Architec"ng’
to
reduce
resources

Tradi"onal
Hos"ng
vs
AWS

# of
(virtual)
servers

60

50

40

30

20

10

0

Hos=ng

Hosting

Offload
to S3

Caching
with CF

AutoScaling

Etc.

When
calcula"ng
TCO…

#1
Start
by
understanding
your
use
cases
&
usage
paUerns

#2
Apples
to
Apples
–
Take
all
the
ﬁxed
costs
into
considera"on

#3
Leverage
‘Cost
Aware
Architec"ng’
to
reduce
resources

#4
Include
pricing
models
(RI,
Spot)
and
economies
of
scale

When
calcula"ng
TCO…

#1
Start
by
understanding
your
use
cases
&
usage
paUerns

#2
Apples
to
Apples
–
Take
all
the
ﬁxed
costs
into
considera"on

#3
Leverage
‘Cost
Aware
Architec"ng’
to
reduce
resources

#4
Include
pricing
models
(RI,
Spot)
and
economies
of
scale

#5
Take
a
look
at
what’s
included:
Intangible
Cost
Savings
!

Did you know?
Free Usage Tier

Free Services

Data Transfer

AWS Elastic Beanstalk
AWS CloudFormation
AWS IAM
Auto Scaling
Consolidated Billing

No Charge for

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…

Inbound Data Transfer
Data Transfer between
Instances within an
Availability Zone

A premium security spec at non-premium prices
• 

VPC

• 

Direct connect

and VPC

• 

Dedicated instances

Network ACL

• 

Identity & Access

• 

Multi-Factor Authentication

Management

• 

CloudHSM

S3 Encryption

• 

RDS Oracle transparent

• 

• 

Security groups for EC2

encryption

DEMO

Gegng
to
Scale

Off-loading of static content to CloudFront to reduce required
server capacity

So what does this mean in terms of costs?
Standard Architecture
Month
Medium EC2 instances 4
$ 485
AWS Data Transfer Out 1Tb $ 194
TOTAL
$ 679

Optimized Architecture
Month
Medium EC2 instances
1
$ 121
CloudFront Data Transfer Out 1Tb $ 168
CloudFront Requests
$1.89
TOTAL
$ 291

57% lower cost – 6 x faster

Thank You
aws.amazon.com/start-‐ups

aws.amazon.com/ac"vate

Taipei

台北

WhosCall
a trusted contact experience

AWS Cloud Kata for Start-Ups and Developers

Gogolook at a glance
Gogolook is a mobile App start-up in a rapid growth based in Taipei, Taiwan. Our App
– WhosCall provides real-time phone number lookup, search, caller identification and
blocks services for smartphone.
Gogolook’s vision is to create a trusted contact experience. WhosCall has helped
millions of people to recognize unidentified phone calls with our phone number
cloud database, which synchronizes data from the Taiwan, Japan, Korea, Hong Kong,
South East Asia, and the Middle East. Our cloud database has over 600 million
numbers, and is still growing at a fast pace.
WhosCall had received public praise as Taiwan’s new innovation model by Google
CEO, Eric Schmidt, and has reach 4 million downloads within 1 year. The daily page
view of calls is over 10 million.

Google Play Ranking

Taiwan

No. 4
Communication

Japan

South Korea

Singapore

Saudi Arabia

No. 11

No. 13

No. 10

No. 7


iOS App Store Ranking

Hong Kong

No. 1
Paid App

Japan

Taiwan

No.1

No.1

Paid App

Paid App


Objectives
!   Collect trustworthy information of phone numbers via
•  Phone number search engine
•  Crowdsourcing (collaborative phonebook)

!   Provide to everyone of the trustworthy information
•  Smartphone Apps
•  Open APIs

Solution - Mobile App
WhosCall helps identify calls in seconds
through Internet searching and community
reporting. No matter what kind of calls you
receive, from malicious phone frauds,
disturbing telemarketing calls, or just random
calls from stores, you are able to know “Who’s
Calling” at a glance. If you have missed calls,
check before you call back! WhosCall saves
you from all the embarrassing communication!

★ Global Caller ID
★ Real-time Searching
★ Block Calls & SMS
★ Temporary Contact Management

Solution - Trusted Partners of WhosCall

Trust

Gain trust
in a glance

Bind

Missing Call
Connection


Engage

Add to
Favorite Contact

AWS Services to talk

Amazon
EC2

Elastic Load
Balancing

Auto
Scaling

CloudWatch


Amazon SQS

Route 53

All Server Side in AWS

Mobile Client


WhosCall and AWS
!   Objective
•  Provide service to the global users with WhosCall strategy
!   Benefit from Flexible
•  Deploy WhosCall server cross multi regions
•  Reserved Instance: some of AP servers and Database
•  RI for basic loading and
On-Demand instance for peak (Auto Scaling)
•  Save more than 25% cost

Route 53

ELB
Auto scaling Group

AP server
on Instance

DB1 on
Reserved Instances
Region 1

ELB
Auto scaling Group

AP server
on Instance

DB2 on
Reserved Instances
Region 2

DB3 (master) on RI
Region 3

Database
Replication

Cron Job Data Computing
Instance PythonProcess AMI
Use
boto libiary

Data Computing Process
on Spot Instances

DB3 on RI

AP Server
Job Queue

Message Processes
on Spot Instances

AWS Cloud Kata for Start-Ups and Developers Auto scaling Group

Messages
Amount Alert

WhosCall and AWS (cont.)
!   Objective
•  Provide better service base on large amount of log
!   Benefit from Spot
•  Log data process job
•  Computing and analyzing data
•  Trying EMR now.
•  Can launch more instances and process data faster


Spot Instance
!   Temporarily computing resource, everyone could bid it.
!   Processing log data in SQS:
• 
• 

Use spot to process messages in queue.
Save Money: m1.small from $0.065 / hr to $0.01 / hr

!   Computing and analyzing log data:
• 
• 

Need lots of temporary Computing instance at same time
Save Time: faster over 5 times than before


Contact Network of Trust


AWS Cloud Kata | Taipei - Getting to Profitability

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