From 64edfc88f81ada393e86be5ff858b5de28f0e33b Mon Sep 17 00:00:00 2001 From: Chanyeong Date: Wed, 11 Dec 2024 03:59:06 +0900 Subject: [PATCH] =?UTF-8?q?=EB=B8=94=EB=A1=9C=EA=B7=B8=20=EC=9E=91?= =?UTF-8?q?=EC=84=B1?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- _posts/2024-12-10-aws_dynamodb (copy).md | 162 +++++++++++++++++ _posts/2024-12-10-aws_dynamodb.md | 145 +++++++++++++++ _posts/2024-12-10-aws_efs.md | 169 ++++++++++++++++++ _posts/2024-12-10-aws_s3.md | 3 + .../image-20241211035030209.png | Bin 0 -> 63536 bytes .../image-20241211035110509.png | Bin 0 -> 52653 bytes .../image-20241211035129809.png | Bin 0 -> 38956 bytes .../image-20241211033941210.png | Bin 0 -> 47197 bytes .../image-20241211034010469.png | Bin 0 -> 31498 bytes .../image-20241211034048209.png | Bin 0 -> 147380 bytes .../image-20241210174348408.png | Bin 0 -> 34005 bytes 11 files changed, 479 insertions(+) create mode 100644 _posts/2024-12-10-aws_dynamodb (copy).md create mode 100644 _posts/2024-12-10-aws_dynamodb.md create mode 100644 _posts/2024-12-10-aws_efs.md create mode 100644 images/2024-12-10-aws_dynamodb/image-20241211035030209.png create mode 100644 images/2024-12-10-aws_dynamodb/image-20241211035110509.png create mode 100644 images/2024-12-10-aws_dynamodb/image-20241211035129809.png create mode 100644 images/2024-12-10-aws_efs/image-20241211033941210.png create mode 100644 images/2024-12-10-aws_efs/image-20241211034010469.png create mode 100644 images/2024-12-10-aws_efs/image-20241211034048209.png create mode 100644 images/2024-12-10-aws_s3/image-20241210174348408.png diff --git a/_posts/2024-12-10-aws_dynamodb (copy).md b/_posts/2024-12-10-aws_dynamodb (copy).md new file mode 100644 index 000000000000..4f9558b02907 --- /dev/null +++ b/_posts/2024-12-10-aws_dynamodb (copy).md @@ -0,0 +1,162 @@ +--- +layout: single +title: "Amazon DynamoDB Overview part2" +categories: AWS +tag: [blog, AWS] +search: true +typora-root-url: ../ + + + + + + + + + + + + + +--- + + + +**[**AWS**]**[**Amazon DynamoDB Overview Part 2**](https://park-chanyeong.github.io) +{: .notice--primary} + + + +## DynamoDB Overview: Part 2 + +### Advanced DynamoDB Concepts + +#### 1. **Transactions** +- DynamoDB는 **ACID 트랜잭션**을 지원하여 데이터 일관성과 무결성을 보장. +- 트랜잭션은 하나 이상의 테이블에서 여러 항목을 읽고 쓸 수 있음. +- 주요 API: + - `TransactWriteItems`: 여러 항목에 대한 원자적 쓰기. + - `TransactGetItems`: 여러 항목에 대한 일관된 읽기. +- 트랜잭션의 제한사항: + - 한 번의 트랜잭션으로 최대 25개의 항목 작업 가능. + - 4MB 크기 제한 존재. +- **사용 예시**: + - 은행 애플리케이션에서 계좌 이체 작업 (A 계좌에서 출금하고 B 계좌에 입금). + - 전자상거래 애플리케이션에서 주문 생성 시 재고 업데이트. + +#### 2. **Partitioning and Performance** +- DynamoDB는 **Partition Key**를 기준으로 데이터를 파티셔닝하여 성능과 확장성을 보장. +- 파티션 설계: + - **균등한 분배**가 중요. 핫 파티션(hot partition) 문제를 피해야 함. + - 예시: 날짜를 Partition Key로 사용하지 말고, 사용자 ID와 결합하여 키를 다양화. +- 읽기/쓰기 처리량: + - 파티션당 최대 처리량 제한 있음. 균형 잡힌 키 설계가 필수. + - 예시: 글로벌 애플리케이션의 사용자 데이터를 지역별로 분배. + +--- + +### DynamoDB Accelerator (DAX) + +#### DAX 정의 +- DAX는 DynamoDB의 인메모리 캐시 서비스로, 읽기 성능을 대폭 향상시키는 데 사용됨. +- **특징**: + - 최대 10배 빠른 읽기 성능 제공. + - 지연 시간이 마이크로초 단위로 감소. + - API 호출 수정 없이 기존 DynamoDB 애플리케이션과 통합 가능. + +#### DAX의 작동 방식 +- DynamoDB 요청이 먼저 DAX 캐시로 전달됨. + - 캐시에 데이터가 있을 경우 즉시 반환. + - 캐시에 없는 경우 DynamoDB에서 조회 후 DAX에 캐싱. +- **일관성 모델**: + - Eventual Consistency만 지원. + +#### DAX 활용 사례 +1. **읽기 집약적인 애플리케이션**: + - 예시: 인기 상품 정보를 빠르게 조회하는 전자상거래 사이트. +2. **리더보드 시스템**: + - Sort Key와 결합하여 빠른 순위 계산 제공. + - 예시: 모바일 게임에서 실시간 리더보드. +3. **IoT 데이터 조회**: + - 수백만 개의 IoT 장치 데이터를 빠르게 검색. + - 예시: 스마트 홈 장치 상태 조회. + +#### DAX 구성 +- DAX 클러스터는 다중 노드로 구성 가능 (최대 10개). + - **Primary Node**: 쓰기 작업 담당. + - **Replica Node**: 읽기 작업 담당. +- 노드 간 자동 복제 및 장애 복구 지원. + +--- + +### Backup and Restore + +#### 1. **On-Demand Backup** +- 데이터 손실에 대비하여 언제든지 테이블의 전체 백업 생성 가능. +- 백업 생성 중에도 읽기/쓰기 작업에 영향을 미치지 않음. +- **사용 예시**: + - 대규모 애플리케이션 업데이트 전 데이터 백업. + +#### 2. **Point-in-Time Recovery (PITR)** +- 특정 시점으로 데이터 복구 가능. +- 최근 35일 내 데이터를 복원. +- **사용 예시**: + - 실수로 데이터가 삭제되거나 수정된 경우 이전 상태로 복구. + +--- + +### Security in DynamoDB + +#### 1. **Encryption** +- **DynamoDB는 기본적으로 데이터를 암호화**하여 저장. +- AWS Key Management Service (KMS)를 사용하여 고객 관리형 키로 데이터 암호화 가능. +- **사용 예시**: + - 민감한 사용자 데이터를 저장하는 애플리케이션. + +#### 2. **Access Control** +- IAM 정책을 사용하여 사용자와 애플리케이션의 접근을 제어. +- Fine-grained access control: + - 특정 항목 수준에서 권한을 부여 가능. + - 예시: 특정 사용자만 자신의 데이터를 읽고 쓰도록 제한. + +--- + +### Cross-Region Replication + +- **Global Tables**: DynamoDB 테이블을 다중 리전에 걸쳐 복제하여 글로벌 애플리케이션 지원. +- **특징**: + - 모든 리전에서 읽기 및 쓰기 가능. + - 데이터 충돌 해결을 위한 최종 쓰기 승리 정책 적용. +- **사용 예시**: + - 글로벌 사용자 기반을 가진 소셜 미디어 애플리케이션. + +--- + +### Advanced Data Modeling + +#### 1. **One-to-Many Relationships** +- **테이블 설계**: + - Partition Key와 Sort Key를 조합하여 관계를 표현. + - 예시: 사용자 ID를 Partition Key로, 주문 ID를 Sort Key로 사용하여 주문 기록 저장. + +#### 2. **Many-to-Many Relationships** +- **테이블 설계**: + - 보조 인덱스(GSI)를 활용하여 관계 탐색. + - 예시: 학생과 수업 관계에서 학생 ID와 수업 ID를 각각 GSI로 설정. + +--- + +### DynamoDB의 확장 사례 + +#### 1. **IoT Data Storage** +- 수백만 개의 IoT 장치에서 데이터를 실시간으로 수집하고 저장. +- **예시**: 스마트 가전제품의 상태 데이터. + +#### 2. **Real-Time Analytics** +- DynamoDB Streams와 Lambda를 사용하여 실시간 데이터 분석 파이프라인 구축. +- **예시**: 사용자 활동 데이터를 기반으로 추천 시스템 작동. + +#### 3. **Gaming Leaderboards** +- Sort Key를 활용하여 순위를 저장하고 조회. +- **예시**: 게임에서 상위 100명의 플레이어를 실시간으로 표시. +- DAX와 결합하여 읽기 속도를 극대화하여 수천만 사용자 지원 가능. \ No newline at end of file diff --git a/_posts/2024-12-10-aws_dynamodb.md b/_posts/2024-12-10-aws_dynamodb.md new file mode 100644 index 000000000000..906f271be28a --- /dev/null +++ b/_posts/2024-12-10-aws_dynamodb.md @@ -0,0 +1,145 @@ +--- +layout: single +title: "Amazon DynamoDB Overview part1" +categories: AWS +tag: [blog, AWS] +search: true +typora-root-url: ../ + + + + + + + + + + + + + +--- + + + +**[**AWS**]**[**Amazon DynamoDB Overview Part 1**](https://park-chanyeong.github.io) +{: .notice--primary} + +## DynamoDB Overview + +![image-20241211035030209](/images/2024-12-10-aws_dynamodb/image-20241211035030209.png) + +### What is DynamoDB? +- **DynamoDB**: AWS의 완전 관리형 NoSQL 데이터베이스 서비스. + - 데이터는 고가용성을 위해 다중 AZ에 자동 복제됨. + - 완전 분산형 데이터베이스로 확장 가능한 워크로드를 처리 가능. + - 초당 수백만 건의 요청, 테라바이트급 스토리지를 지원. + +#### 주요 특징 +1. **스키마리스 데이터 구조** + - 고정된 스키마 없이 데이터를 저장하며, 각 항목의 속성은 필요에 따라 추가 가능. + - 예시: 온라인 쇼핑몰에서 상품 데이터가 각기 다른 속성을 가질 때 유용. + - 상품 A: {"이름": "노트북", "가격": 1000, "카테고리": "전자기기"} + - 상품 B: {"이름": "책", "저자": "홍길동", "카테고리": "서적"} +2. **빠른 성능** + - 낮은 지연 시간과 일관된 성능 제공. + - 예시: IoT 센서에서 실시간으로 수집된 데이터를 처리할 때. +3. **보안** + - IAM 통합으로 인증 및 권한 관리 가능. + - 예시: 특정 사용자 그룹에 읽기 전용 권한 제공. +4. **자동 확장성** + - 수요에 따라 용량 자동 조정. + - 예시: 블랙프라이데이와 같은 트래픽 급증 상황에서 유연한 확장 가능. + +--- + +### DynamoDB 테이블 기본 구성 +1. **테이블**: + - 테이블은 항목(row)과 속성(column)으로 구성. + - 테이블은 Primary Key로 항목을 고유하게 식별. + - 예시: "사용자 테이블"에 고유 사용자 ID를 Primary Key로 사용. + +2. **Primary Key**: + - Partition Key (HASH Key): 고유 식별자를 사용하여 항목 분배. + - 예시: 사용자 ID, 주문 번호 등. + - ![image-20241211035129809](/images/2024-12-10-aws_dynamodb/image-20241211035129809.png) + - Partition Key + Sort Key (HASH + RANGE Key): 정렬 가능한 추가 키로 데이터 그룹화. + - 예시: "사용자 ID" + "주문 날짜" 조합으로 사용자별 주문 이력 관리. + - ![image-20241211035110509](/images/2024-12-10-aws_dynamodb/image-20241211035110509.png) + +3. **속성**: + - 지원 데이터 타입: + - 스칼라 타입: String, Number, Binary, Boolean, Null. + - 문서 타입: List, Map. + - 집합 타입: String Set, Number Set, Binary Set. + - 항목 크기 제한: 400KB. + - 예시: 사용자 프로필 데이터에 다양한 데이터 타입 활용. + - {"이름": "홍길동", "나이": 25, "취미": ["축구", "독서"]} + +--- + +### Capacity Modes +1. **프로비저닝 모드**: + - 읽기 및 쓰기 용량을 명시적으로 설정. + - **WCU (Write Capacity Unit)**: 1초 동안 1KB 데이터 쓰기 가능. + - **RCU (Read Capacity Unit)**: 1초 동안 Strongly Consistent Read 기준 4KB 데이터 읽기 가능. + - 예시: 매일 일정량의 데이터를 처리하는 로그 저장 시스템. +2. **온디맨드 모드**: + - 사용량에 따라 자동으로 처리 용량 조정. + - 초기 설정 없이 탄력적인 리소스 관리 가능. + - 예시: 트래픽 패턴이 예측 불가능한 스타트업의 애플리케이션. + +--- + +### 데이터 읽기/쓰기 +1. **데이터 읽기** + - **Strongly Consistent Read**: 항상 최신 데이터 보장. + - 예시: 금융 거래 시스템에서 실시간 계좌 잔액 확인. + - **Eventually Consistent Read**: 지연된 일관성, 더 높은 처리량 제공. + - 예시: 뉴스 애플리케이션에서 뉴스 댓글 로딩. +2. **데이터 쓰기** + - 항목이 Primary Key를 기준으로 테이블에 저장. + - 예시: 온라인 주문 처리 시스템에서 주문 데이터 저장. + +--- + +### Indexes +1. **Global Secondary Index (GSI)**: + - 기존 Primary Key 외 다른 속성으로 데이터 조회 가능. + - 별도 용량(WCU/RCU)을 프로비저닝. + - 예시: 사용자 테이블에서 이메일 주소로 검색 가능하도록 설정. +2. **Local Secondary Index (LSI)**: + - 동일한 Partition Key를 공유하는 데이터 조회. + - 테이블 생성 시에만 추가 가능. + - 예시: 사용자 ID를 기준으로 최신 로그를 시간순으로 조회. + +--- + +### DynamoDB Streams +- **DynamoDB Streams**: 항목의 생성, 수정, 삭제 작업을 스트림 데이터로 기록. + - 스트림 데이터는 24시간 동안 보존. + - **사용 사례**: + - 실시간 이벤트 처리 (예: 신규 사용자 환영 이메일). + - 데이터 분석. + - 교차 리전 복제. + - 예시: 채팅 애플리케이션에서 메시지 업데이트 이벤트를 실시간 반영. + +--- + +### Time To Live (TTL) +- **TTL**: 지정된 시간 이후 데이터가 자동 삭제되도록 설정. + - 스토리지 최적화 및 규정 준수를 위해 유용. + - 예시: 30일이 지난 쿠폰 데이터를 자동 삭제. + +--- + +### DynamoDB의 데이터 엔지니어링 활용 사례 +1. **데이터 처리 파이프라인**: + - DynamoDB Streams를 활용하여 실시간 데이터 스트리밍 구축. + - 예시: IoT 센서 데이터가 DynamoDB로 입력되고 스트림을 통해 분석 시스템으로 전송. +2. **규모 확장이 필요한 애플리케이션**: + - IoT 데이터 수집 및 처리. + - 예시: 스마트 홈 시스템에서 수백만 개의 장치 상태를 저장. +3. **빅데이터 처리**: + - MapReduce 작업의 중간 상태 저장소로 사용. + - 예시: DynamoDB에 중간 데이터를 저장하고 Amazon EMR로 최종 분석 수행. \ No newline at end of file diff --git a/_posts/2024-12-10-aws_efs.md b/_posts/2024-12-10-aws_efs.md new file mode 100644 index 000000000000..4a2c0ac72ea1 --- /dev/null +++ b/_posts/2024-12-10-aws_efs.md @@ -0,0 +1,169 @@ +--- +layout: single +title: "Amazon EBS/EFS, AWS Backup" +categories: AWS +tag: [blog, AWS] +search: true +typora-root-url: ../ + + + + + + + + + + + + + + +--- + + + +**[**AWS**]**[**Amazon EBS/EFS, AWS Backup**](https://park-chanyeong.github.io) +{: .notice--primary} + + + + + +## Amazon EBS/EFS 그리고 AWS Backup + +### 1. **Elastic Block Store (EBS)** + +![image-20241211033941210](/images/2024-12-10-aws_efs/image-20241211033941210.png) + +#### EBS 정의 및 특징 +- **EBS (Elastic Block Store)**: AWS에서 제공하는 고성능 블록 스토리지. + - EC2 인스턴스에 연결 가능하며, 네트워크를 통해 데이터 접근. + - EC2 인스턴스 종료 후에도 데이터를 영구적으로 보관 가능. + - 데이터베이스, 파일 시스템, 애플리케이션 로그 저장 등 다양한 워크로드 지원. + +#### EBS 특징 +1. **지역 제한** + - EBS 볼륨은 특정 가용 영역(Availability Zone, AZ)에 속하며, 다른 AZ로 이동 시 스냅샷 복원이 필요함. +2. **확장성** + - 볼륨 크기와 IOPS는 필요에 따라 확장 가능. + - 축소는 불가능하며, 용량 증가 시 자동 데이터 재배치 수행. +3. **성능 계층** + - **General Purpose SSD (gp2/gp3)**: 범용 워크로드에 적합한 저비용 SSD 스토리지. + - **Provisioned IOPS SSD (io1/io2)**: 높은 IOPS가 필요한 데이터베이스 워크로드에 적합. + - **Throughput Optimized HDD (st1)**: 대규모 시퀀스 읽기/쓰기 워크로드에 적합. + - **Cold HDD (sc1)**: 자주 액세스하지 않는 데이터에 최적화된 저비용 스토리지. + +#### EBS 추가 기능 +1. **Delete on Termination** + - EC2 인스턴스 종료 시, 루트 볼륨을 자동 삭제할지 여부를 설정. + - 데이터 보존 필요 시 비활성화 가능. +2. **Elastic Volumes** + - 인스턴스 연결 상태에서 볼륨 크기, 유형, IOPS 변경 가능. + - 다운타임 없이 실시간으로 조정 가능. +3. **EBS 스냅샷** + - EBS 볼륨의 스냅샷을 생성하여 데이터를 백업하거나 복제 가능. + - 증분 스냅샷 방식으로 저장 공간 절약. + +#### 사용 사례 +- 관계형 데이터베이스(MySQL, PostgreSQL). +- 빅데이터 워크로드(Hadoop, Spark). +- NoSQL 데이터베이스(Cassandra, MongoDB). +- **데이터 엔지니어링 예시**: + - 데이터베이스 스냅샷을 통해 데이터 복구 지점을 생성. + - Apache Airflow와 통합하여 정기적인 데이터 처리 및 결과 저장. + +--- + +### 2. **Amazon EFS (Elastic File System)** + +![image-20241211034010469](/images/2024-12-10-aws_efs/image-20241211034010469.png) + +#### EFS 정의 +- **EFS (Elastic File System)**: AWS의 완전 관리형 네트워크 파일 시스템. + - EC2 인스턴스와 공유 파일 스토리지를 제공하며, 다중 AZ에서 액세스 가능. + - 자동 확장 기능으로 파일 시스템 크기를 동적으로 조정. + +#### EFS 특징 +1. **POSIX 호환** + - UNIX 기반 애플리케이션과 호환 가능. + - 디렉토리 구조, 파일 권한, 심볼릭 링크 지원. +2. **고가용성 및 내구성** + - 데이터를 다중 AZ에 복제하여 높은 가용성과 내구성 제공. +3. **스토리지 클래스** + - **Standard**: 고빈도 데이터 액세스에 적합. + - **Infrequent Access (IA)**: 자주 사용하지 않는 데이터 저장 시 비용 절감 가능. + - **Lifecycle Management**: 7일 이상 미사용 데이터를 자동으로 IA로 이동 가능. +4. **암호화** + - 데이터 전송 중 및 저장 중 암호화 지원. + - AWS KMS(Key Management Service) 통합. + +#### 사용 사례 +- 빅데이터 분석과 머신러닝. +- 미디어 처리 및 콘텐츠 관리. +- DevOps 환경에서의 공유 파일 시스템. +- **데이터 엔지니어링 예시**: + - Spark 클러스터의 공유 파일 저장소로 사용하여 작업 결과 저장. + - DataPipeline에서 중간 파일 저장소로 활용. + +--- + +### 3. **EBS와 EFS 비교** +| 특성 | EBS | EFS | +| --------------------- | ------------------------ | ------------------------ | +| **연결성** | 단일 EC2 인스턴스 | 다중 EC2 인스턴스 | +| **확장성** | 크기 수동 조정 | 자동 확장 | +| **성능** | 높은 IOPS 제공 | 여러 워크로드 동시 지원 | +| **비용** | 상대적으로 저렴 | 상대적으로 비쌈 | +| **사용 사례** | 데이터베이스, 로그 저장 | 웹 서버, 데이터 공유 | +| **데이터 엔지니어링** | 데이터베이스 스냅샷 관리 | Spark 클러스터 공유 파일 | + +--- + +### 4. **AWS Backup** + +![image-20241211034048209](/images/2024-12-10-aws_efs/image-20241211034048209.png) + +#### AWS Backup 정의 +- AWS Backup은 백업 및 복구 작업을 중앙에서 관리하는 완전 관리형 서비스. +- Amazon EBS, RDS, DynamoDB, EFS 등 여러 AWS 서비스와 통합 가능. +- 재해 복구 및 데이터 보호를 위한 백업 정책 자동화 지원. + +#### 주요 기능 +1. **중앙 관리** + - AWS 리소스의 백업 작업을 단일 콘솔에서 관리. + - 여러 계정과 리전에 걸쳐 백업 정책 적용 가능. +2. **백업 계획(Backup Plan)** + - 백업 빈도, 보존 기간 설정. + - 교차 리전 복제를 통해 데이터 보호 강화. +3. **Vault Lock** + - 백업 볼트를 변경/삭제로부터 보호. + - WORM (Write Once, Read Many) 정책 적용 가능. +4. **자동화 및 스케줄링** + - 백업 프로세스를 자동화하여 운영 효율성 증대. + +#### 복구 기능 +- 스냅샷 복구 및 EFS 파일 시스템 복원 지원. +- 백업 데이터는 AWS Backup 콘솔에서 복구 가능. + +#### 비용 +- 백업 저장 용량 및 복제 작업에 따른 과금. +- 교차 리전 복제와 장기 보존 시 추가 비용 발생. + +#### **데이터 엔지니어링 예시** +- 주기적인 데이터베이스 백업으로 손실 가능성 최소화. +- Athena 쿼리를 위한 정기적인 S3 데이터 스냅샷 생성. +- Amazon Glue 작업과 연결하여 데이터 복구 워크플로 구현. + +--- + +### 5. **추가 참고사항** +#### 백업 관리 모범 사례 +- 정기적인 복구 테스트 실행으로 신뢰성 확보. +- 백업 보존 정책 설정으로 비용 최적화. +- 민감 데이터는 암호화하여 저장. +- **데이터 엔지니어링 관점**: + - S3 데이터 레이크 백업 및 복구. + - 빅데이터 파이프라인의 재사용 가능 복구 포인트 설정. + +AWS 스토리지 서비스와 백업 옵션은 다양한 워크로드에 맞게 설계되었으며, 운영 환경에 따라 적절히 활용하면 비용 효율성과 보안성을 동시에 달성 가능. \ No newline at end of file diff --git a/_posts/2024-12-10-aws_s3.md b/_posts/2024-12-10-aws_s3.md index 43953aad9d58..49f3d57758cf 100644 --- a/_posts/2024-12-10-aws_s3.md +++ b/_posts/2024-12-10-aws_s3.md @@ -120,6 +120,9 @@ typora-root-url: ../ - 복제는 비동기로 작동. #### 수명 주기 정책 (Lifecycle Policies) + +![image-20241210174348408](/images/2024-12-10-aws_s3/image-20241210174348408.png) + - 객체를 특정 기간 후 저렴한 스토리지 클래스로 자동 이동. - 예: 30일 지난 로그 데이터를 Glacier로 이동. - 오래된 데이터 자동 삭제 설정 가능. diff --git a/images/2024-12-10-aws_dynamodb/image-20241211035030209.png b/images/2024-12-10-aws_dynamodb/image-20241211035030209.png new file mode 100644 index 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