코드형 인프라 (IaC)

스크립트를 통한 시스템 관리.

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Modes: 1. One-way (Mirroring). 2. Two-way (Bidirectional). 3. Continuous (Real-time). Techniques: File-level vs Block-level sync, delta encoding, version vectors, last-writer-wins resolution.

        graph LR
  Center["코드형 인프라 (IaC)"]:::main
  Rel_synthetic_biology["synthetic-biology"]:::related -.-> Center
  click Rel_synthetic_biology "/terms/synthetic-biology"
  classDef main fill:#7c3aed,stroke:#8b5cf6,stroke-width:2px,color:white,font-weight:bold,rx:5,ry:5;
  classDef pre fill:#0f172a,stroke:#3b82f6,color:#94a3b8,rx:5,ry:5;
  classDef child fill:#0f172a,stroke:#10b981,color:#94a3b8,rx:5,ry:5;
  classDef related fill:#0f172a,stroke:#8b5cf6,stroke-dasharray: 5 5,color:#94a3b8,rx:5,ry:5;
  linkStyle default stroke:#4b5563,stroke-width:2px;

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🧒 5살도 이해할 수 있게 설명

수많은 컴퓨터와 서버를 일일이 수동으로 설정하는 대신, 일종의 '레시피'를 쓰는 것과 같아요. 그 레시피를 프로그램에 넣으면, 프로그램이 알아서 내가 원하는 대로 네트워크를 자동으로 뚝딱 만들어주죠.

🤓 Expert Deep Dive

Technically, synchronization is governed by the 'CAP Theorem' (Consistency, Availability, Partition Tolerance). In a distributed system, you must trade off between 'Strong Consistency' (all nodes see the same data at the same time) and 'High Availability' (the system stays up even if some parts fail). 'Eventual Consistency' is a common model where the system guarantees that if no new updates are made, all nodes will eventually converge to the same state. Implementation methods include 'Change Data Capture' (CDC), which monitors database logs for changes, and 'Consensus [Algorithms](/ko/terms/consensus-algorithms)' like Raft or Paxos, which allow a cluster of servers to agree on a single 'Truth' in the presence of failures.

🧒 5살도 이해할 수 있게 설명

🤓 Expert Deep Dive

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