갤럭시 규모의 인공지능 서비스를 위한 AWS 데이터베이스 아키텍처 - 김상필 솔루션 아키텍트 매니저, AWS / 김정환 데브옵스 엔지니어, 삼성전자 / 이혁 데이터베이스 운영 엔지니어, 삼성전자 :: AWS Summit Seoul 2019

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
갤럭시 규모의 인공지능 서비스를 위한
AWS 데이터베이스 아키텍처
김상필
솔루션즈 아키텍트 매니저
AWS Korea
이혁
Database Engineer
Samsung Electronics
김정환
Global Service Reliability Engineer
Samsung Electronics

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
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니다

What are modern applications?
AWS Database service options
Case study: Samsung Bixby 2.0
Case study: Bixby Database architecture
Agenda

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Characteristics of modern applications
Internet-scale and transactional
Users: 1M+
Data volume: TB–PB–EB
Locality: Global
Performance: Milliseconds–microseconds
Request Rate: Millions
Access: Mobile, IoT, devices
Scale: Up-out-in
Economics: Pay-as-you-go
Developer access: Instant API accessSocial mediaRide hailing Media streaming Dating

Modern applications require internet-scale performance

Data categories and common use cases
Relational Key value Document In-memory Graph
Referential
integrity, ACID
transactions,
schema-
on-write
Low-latency,
key lookups
with high
throughput and
fast ingestion
of data
Indexing and
storing
documents
with support
for query on
any attribute
Microseconds
latency, key-
based queries,
and specialized
data structures
Creating and
navigating
data relations
easily and
quickly
Lift and shift,
EMR, CRM,
finance
Real-time
bidding,
shopping cart,
social
Content
management,
personalization,
mobile
Leaderboards,
real-time
analytics,
caching
Fraud detection,
social
networking,
recommendation
engine
Search
Indexing and
searching
semistructured
logs and data
Product
catalog, help,
and FAQs,
full text
Time series Ledger
Collect, store,
and process
data sequenced
by time
IoT
applications,
event tracking
Complete,
immutable, and
verifiable history
of all changes to
application data
Systems
of record,
supply chain,
healthcare,
registrations,
financial

AWS: Purpose-built databases
Relational Key value Document In-memory Graph Search
Amazon
DynamoDB
Amazon
Neptune
Amazon RDS
Aurora CommercialCommunity
Amazon
ElastiCache
Amazon
Elasticsearch
Service
Amazon
DocumentDB
Time series Ledger
Amazon
Timestream
Amazon
Quantum
Ledger
DatabaseMemcachedRedis

Amazon DynamoDB
Fast and flexible key value database service for any scale
Comprehensive
security
Encrypts all data by
default and fully integrates
with AWS Identity and
Access Management for
robust security
Performance at scale
Consistent, single-digit
millisecond response times at
any scale; build applications with
virtually unlimited throughput
Global database for
global users and apps
Build global applications with
fast access to local data by easily
replicating tables across multiple
AWS Regions
Serverless
No hardware provisioning,
software patching, or
upgrades; scales up or down
automatically; continuously
backs up your data

Amazon Aurora
MySQL and PostgreSQL compatible relational database built for the cloud
Performance and availability of commercial-grade databases at 1/10th the cost
Availability
and durability
Fault-tolerant, self-healing
storage; six copies of data
across three AZs; continuous
backup to S3
Fully managed
Managed by RDS:
no hardware provisioning,
software patching, setup,
configuration, or backups
Highly secure
Network isolation,
encryption at
rest/transit
Performance
and scalability
5x throughput of standard
MySQL and 3x of standard
PostgreSQL; scale-out up to
15 read replicas

When to Use Which Services
Situation Solution
Existing application Use your existing engine on RDS
• MySQL Amazon Aurora, RDS for MySQL
• PostgreSQL Amazon Aurora, RDS for PostgreSQL
• MariaDB Amazon Aurora, RDS for MariaDB
• Oracle Use SCT to determine complexity Aurora, RDS for Oracle
• SQL Server Use SCT to determine complexity Aurora, RDS for SQL Server
New application • If you can avoid relational features DynamoDB
• If you need relational features Amazon Aurora
In-memory store/cache • Amazon ElastiCache
Time series data • Amazon Timestream
Track every application change, crypto verifiable.
Have a central trust authority
• Amazon Quantum Ledger Database (QLDB)
Don’t have a trusted central authority • Amazon Managed Blockchain
Data Warehouse & BI • Amazon Redshift, Amazon Redshift Spectrum, and Amazon QuickSight
Adhoc analysis of data in S3 • Amazon Athena and Amazon QuickSight
Apache Spark, Hadoop, HBase (needle in a
haystack type queries)
• Amazon EMR
Log analytics, operational monitoring, & search • Amazon Elasticsearch Service and Amazon Kinesis

Architect services ground-up for the cloud
and for the explosion of data
Offer a portfolio of purpose-built
services, optimized for your workloads
Help you innovate faster through
managed services
Our approach
Provide services that help you migrate
existing apps and databases to the cloud

S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
김정환(Jay Kim)
Global Service Reliability Engineer
Samsung Electronics
jay-.kim@samsung.com
rpkim.net
linkedin.com/in/rpkimjay

Introduction video

Samsung’s A.I. service 2018
Bixby 2.0
2017
Bixby 1.0
NOW
2017 2018

2019
Bixby 2.0
AI Interface
AI Developer Platform
Bixby developer center
voice-activated
personal assistant
DEMOCRATIZED AI UNPRECEDENTED
REACH
POWERFUL
PERSONALIZATION
An open artificial
intelligence platform
https://bixbydevelopers.com
https://bixby.developer.samsung.com
Samsung device
ecosystem
Learn user
preferences
Bixby 2.0

Multi-Locales Service
ko-KR en-GB
en-US
zh-CN
de-DE
It-IT
fr-FR
es-ES
World-wide Service
60 Million Users
Multi-Devices Service
Mobile, Television
and so on
2019
AI Interface
voice-activated
personal assistant
Bixby 2.0

True benefits of using
for
2019
AI Interface
voice-activated
personal assistant
Bixby 2.0

Bixby’s Global-scale footprints with AWS
ap-northeast-2
(Seoul)
cn-north-1
(Beijing)
eu-west-1
(Ireland)
us-east-2
(Ohio)
2019
AI Interface
voice-activated
personal assistant
Bixby Production regions
Bixby 2.0

Bixby’s Global-scale footprints with AWS
ap-northeast-2
(Seoul)
cn-north-1
(Beijing)
eu-west-1
(Ireland)
us-east-2
(Ohio)
2019
AI Interface
voice-activated
personal assistant
us-west-2
(Oregon)
us-east-1
(N. Virginia)
cn-north-2
(Ningxia)
Bixby 2.0
Bixby Dev/Staging/Production regions

Excellent compatibility with third-party tools
Packer
Spinnaker Ansible
Application
Provisioning
Continuous
Delivery
Monitoring
System
Datadog
Terraform
Infrastructure
creation
DEV
STG
Prod
2019
AI Interface
voice-activated
personal assistant
Bixby using third-party tools
Bixby 2.0

Terraform
Infrastructure
creation
2019
AI Interface
voice-activated
personal assistant
Bixby using various continuous delivery pipelines
Bixby 2.0
Userdata.sh
$ curl http://169.254.169.254/latest/meta-data/
$ role=ABC # from instance tag
$ ansible-pull –e “role=ABC“ –U git@github.com:ansible.git playbook.yml
Instance Tags
ansible-role ABC
package-version ABC-273a81-v1.5.zip
AnsibleEC2
Ansible
# Add cronjob for ansible-pull
# Getting package-version
# Install & Service Execution
Github
Infrastructure provisioning : creation machine, infrastructure
Application bootstrapping: install & configuration the application

2019
AI Interface
voice-activated
personal assistant
Bixby using various AWS services for automation
Bixby 2.0Security Group
Inbound change CloudTrail
Detect!
CloudWatch
Event
RevokeSecurityGroupIngress
AuthorizeSecurityGroupIngress
Lambda Slack
EC2
Block
Bitcoin
mining
B

AWS services powering Bixby
Compute
Container Registry Lambda
Elastic Load Balancer Auto Scaling
Elastic Container Service EC2
Database
Aurora
DynamoDB
ElasticCache
RDS
Developer Tools
CodeDeploy CLI
Security, Identity & Compliance
IAM
KMS
Certificate Manager
Storage
EBS
EFS
S3 2019
AI Interface
voice-activated
personal assistant
Bixby 2.0
Management & Governance
CloudWatch CloudTrail
Trusted Advisor
Networking & Content Delivery
CloudFront Route53
VPC API Gateway

Why run Artificial Intelligence on AWS
2019
AI Interface
voice-activated
personal assistant
Bixby 2.0
GPU
Instances
EFS
File system
Database
services
For ASR For sharing
model data
For personal
language model

High Level Diagram
2019
AI Interface
voice-activated
personal assistant
Bixby 2.0

PLM
Bixby Platform Overview
PLM
Personal Language Model
2019
AI Interface
voice-activated
personal assistant
Bixby 2.0
ASR NLU TTS
Storage
Services
Users
Database
Services
Automatic Speech Recognition
ASR NLU
Natural Language Understanding
TTS
Text to Speech

Bixby Database architecture
이혁
Database Engineer
Samsung Electronics

Launching Bixby
Bixby 1.0 in 2017
Commercial shared file system
Bixby 2.0 in 2018
Database

Challenges in Bixby 1.0
• Each personal data started getting bigger
• 100MB+ for each device : file loading time
• Many small files
• Hard to work together
• Each team had their own files
• Hard to extract meaningful value
• Operating File System Cluster on AWS
• Disk / Node failure
• inode limitations
• Managing commercial license

What we needed?
Database

What we needed?
Blazingly fastPB scalability
No license China region

How we selected PLM DB?
RDBMS NoSQL
Open source
Aurora
Cloud native Open source
Other cloud
DynamoDB
Cloud native
PB scalability

PLM DB PoC scenario
• Requirements
• No global replication
• Database in 1 region + cache in all : network latency
• Same architecture for all regions
• Each region has 1,920+ concurrent users for load
• 300 items per device : 192KB
• Generated test data : 10TB
• Goal
• Get 300 items from DB within 100ms
• Put it into Cache once and get 10x within 10ms
Seoul OhioIreland
DB
API API API

PLM DB PoC scenario
• Test schema in DynamoDB
Device id
(PK*)
Seq_num
(SK**)
Last name First name Nick name Full name …
x2019 1 Cho EunAh Frozen Eunah Cho …
x2019 2 Cho BeomSeung Iron man BeomSeung Cho …
x2019 3 Lee Hyuk Groot Hyuk Lee …
…
* PK : Partitioning Key
** SK : Sort Key

PLM DB PoC result-1
How we tested?
1. API servers in 3 regions called.
2. DynamoDB in Seoul for 1 hour.
3. DynamoDB returned 300 items(192KB).
4. Logged the query + round trip time.
5. Measured average number.
Why we did this test?
1. Whether the centralized database was
possible or not.
52ms
(Seoul)
1,512ms
(Ireland)
945ms
(Ohio)
Network made differences!

PLM DB PoC result-2
1,442ms
(Ireland)
2,339ms
(Ohio)
3,063ms
(Seoul)
How we tested?
1. API servers in 3 regions called.
2. DynamoDB in Seoul for 1 hour.
3. DynamoDB returned 300 items(192KB).
4. Put data into ElastiCache Redis.
5. Get data from ElastiCache Redis 10x.
6. Logged the query + round trip time.
7. Measured average number.
Why it took too long
1. DynamoDB worked well
2. ElastiCache Redis latency increased under
high memory utilization and high traffic.
What we learned?
1. Needs to keep some free memory space in
operation for consistent low latency for
Elasticache Redis.
Network + ElastiCache Redis
made differences!

Key design is the key
• Primary key selection for
performance at scale – NoSQL
itself is not a silver bullet
• Understanding for Access
Pattern for simplicity and cost -
We have no secondary index

DynamoDB Schema Design for Bixby
Partition1 Partition2 ….. PartitionN Partition1 Partition2 ….. PartitionN
3000 rows
1000 rows
1000 rows
1000 rows
service_iduser_id xxx_iddomain
Partition key Sort key
1000 rows 1000 rows 1000 rows
domainuser_id xxx_idservice_id
Partition key Sort key
* Cardinality for IDs
user_id(1) : service_id(1) : domain(N) : xxx_id(M)

Choosing AWS database options for Bixby
DynamoDB for Personal data
Aurora MySQL : Member & admin
ElastiCache Redis for caching data
EMR for analytics
S3 for object data
EFS for low-latencyRDS MySQL : China
RDS PostgreSQL : Geo functions

AWS Benefits
ElastiCache Redis
• Version : 2.8 - 5.0*
• Cluster-mode*
• Read scale-out with slaves*
Aurora MySQL
• Cloud based architecture : super performance with
low-price
• All instances are supported*
• Read scale-out with up to 15 read replicas
• Up to 5 cross region replication*
• Custom endpoint*
* Supported by AWS
DynamoDB
• Auto Scaling
• 3 Availability Zones
• VPC endpoint : Security
• Consistent performance and low latency at any
scale

Lessons learned
• PoC
• Database and API server have to be in the same place because of network
• Needs to keep some free memory space in operation for consistent low latency for Elasticache Redis
• DynamoDB table design
• Making access pattern simple is the key
• Spreading out traffic across all partitions is important
• Less or no secondary key is better if possible
• vs Bixby 1.0
• Working as one team easily through DB!
• No license and operational cost with DynamoDB and EFS

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갤럭시 규모의 인공지능 서비스를 위한 AWS 데이터베이스 아키텍처 - 김상필 솔루션 아키텍트 매니저, AWS / 김정환 데브옵스 엔지니어, 삼성전자 / 이혁 데이터베이스 운영 엔지니어, 삼성전자 :: AWS Summit Seoul 2019

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