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S E O U L | M A Y 4 , 2 0 2 3

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© 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved.
!
Why Not?
AWS
(TANGO )
SK telecom

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•
•
• SK Telecom “TANGO”
•
Agenda

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& &
,
,
&

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. . . . . . ,
+ +

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Amazon
:
+ + 2

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Oracle
SQL Server
MongoDB
Redis
…
Amazon Aurora
Amazon RDS
Amazon DocumentDB
Amazon ElastiCache
Amazon MemoryDB
Oracle
SQL Server
IBM DB2
Sybase
…
Amazon Aurora
Amazon RDS
Oracle
SQL Server
MySQL
PostgreSQL
…
Amazon DynamoDB
Amazon Elasticache
Amazon Neptune
Amazon DocumentDB
Amazon Timestream
…
AWS

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1 :
, ,
•
•
Amazon RDS, Amazon Aurora

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2 :
•
•
•
•
•
•
•
Amazon ElastiCache
Amazon MemoryDB
Amazon RDS, Amazon Aurora

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3 :
•
•
•
•
• - ,
Amazon DynamoDB
Amazon DocumentDB
Amazon Keyspaces
Amazon ElastiCache
Amazon MemoryDB
Amazon RDS, Amazon Aurora

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4 :
Amazon Timestream
Amazon Neptune
Amazon QLDB
•
•
•
•
•
•
•
•
- ,
Amazon DynamoDB
Amazon DocumentDB
Amazon ElastiCache
Amazon MemoryDB
Amazon RDS, Amazon Aurora
Amazon Keyspaces

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.
NoSQL
Amazon DynamoDB, Amazon DocumentDB, Amazon Keyspaces
: , , , , ,
Amazon Aurora, Amazon RDS
: , ,
-
Amazon ElastiCache, Amazon MemoryDB
:
1
2
3
Amazon Neptune, Amazon Timestream, Amazon QLDB
: , , , , ,
4

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© 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved.
SK Telecom
(TANGO )
SK Telecom

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TANGO
T A N G O ( T - A D V A N C E D N E X T G E N E R A T I O N O S S )
TANGO ?
• SKT
• : , , , 설계 구축
• 구성: O, I, PF, A, EC 5
• DB 방안 (21 )
• 5G (22 )
• 3G, LTE, IP (23 )
• (24 )
TANGO
O
Operation: ,
I
PF
A
EC
Inventory:
Platform:
Analytics:
Engineering&Construction:
전환 대상 On Premise

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전환 목표
T A N G O
MSA/
[ /가용성 향상]
,
DB
[ / ]
TCO
/
[ / ]
TANGO
[ 성능/속도 ]
( )

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확장성 한계
•
• DB 및
성능 이슈
•
• AI
• S/W 비용
• 경감 필요
• DB :
•
✓ (LTE/5G)
✓ (AI)
전환 목표
D B :
[ DB ]

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DB
설계 개발 운용
최적화
오픈소스 DB 전환 ( )
• 성능/ 최적화(APM)
•
▪ 최적화
▪ Graviton 적용
▪ RDS
/
• 적합한 DB 선택
• ,
▪ 분산 설계
▪ Query Awareness
▪ S3 활용 (DB )
• SQL 전환 가이드
•
이
• /
•
• DB
• SQL

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DB
선 택
• 관계형 DB
• NoSQL
• 시계열 DB
-
- Join
- RDB
-
-
- Vacuum
- (비용 대비 효과)
- 구성
- 관리 편의성
- 운영 부담 감소
DB DB 선택 /
• MySQL
• PostgreSQL
• Aurora MySQL
• RDS for MySQL
• Serverless
• EC2
• Oracle
, 개발 및 유지보수 을 고려한 DB 선택 필요

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DB
D B 분 산 설 계
[Oracle DB, All-Active 구조, ]
[Aurora MySQL, Master-Slave 구조, ]
업무 영역 별 DB
• DB 분리
DB 샤딩
•
• Key
• ) ID
S3 활용
• DB
Query Awareness
• Slave (Read Replica) 활용한 Select Query 처리
• Master

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DB
S Q L 전 환 가 이 드
[ SQL ] [ SQL ]
MySQL
SQL ,

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DB
DMS를 활용하여 Oracle에서 Aurora MySQL로 데이터 마이그레이션 진행
DMS 중계 서버

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DB
G R A V I T O N 적 용 결 과 공 유
TANGO Graviton vs Intel 진행
: TANGO , DB , 큰 경우 Graviton이 우수한 성능을 보임
Graviton CPU의 가격은 11.7% 1.3배 이상 우수하여 TANGO
AVG CPU 사용률 (%)
74%
98%
17% 16%
KPI2 DB PRI DB
1.3
Select Latency(ms)
301
ms
681
ms
23ms 24ms
KPI2 DB KPI1 DB
2.3
DML Latency(ms)
682
ms
903
ms
444
ms
490
ms
KPI2 DB PI6 DB
1.3
Graviton : db.r6g
Intel: db.r5

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[ ] Graviton Test
• Pri DB:
• KPI DB1: Core KPI
• KPI DB:2 KPI
• PI DB1~9:

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DB
•
• Read Replica 삭제 및 /휴일 / 기능 적용
[TANGO STG ]

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Lesson Learned
DMS 등의 Tool 활용 숙지, 수 차례의
Oracle과 동등 수준 E2E 성능 확보
성능 최소화를 위한 DB 최적화(분산) 설계 중요
전환 개발에 대한
SQL 전환 가이드 사전 제공, DB 에 스키마
1
2
3
DB 비용 비중 높음 ( 56%), DB 유지보수 비용 증가 가능성 존재
Graviton 사용 필수, 저가형 스토리지 사용 확대 필요, 유지보수 절감 방안 필요
4
,

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(23년)
구 조 개 선 및 S 3 활 용 확 대 를 통 한 비 용 감 추 진
DB
, Slave DB
DB S3(Athena)
1
2
3
TANGO (3G, LTE, IP )
DB

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© 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved.