면접 준비 내용을 정리합니다.
- HTTP 1.1 / HTTP 2 / HTTP 3
- HTTPS / TLS Handshake
- REST / GraphQL / gRPC
- Status Code / Header / Cookie
- Content Negotiation
- Idempotent / Safe Method
- API Versioning
- Pagination / Filtering / Sorting
- Rate Limit 정책 설계
- Process lifecycle
- Context switching
- Virtual memory
- Page cache
- File descriptor limit
- epoll / kqueue
- Thread vs Event Loop
- Node.js event loop phases
- Async I/O
- Promise / Callback / Stream
- Backpressure
- GC 알고리즘
- Heap snapshot
- Flamegraph
- Memory leak 패턴
- Schema design
- Normalization / Denormalization
- Index design (B-Tree, covering index)
- ACID
- Isolation Level
- Lock (row / gap / next-key)
- Deadlock handling
- Execution plan 분석
- Partitioning
- Sharding
- Replication (sync / async)
- Read replica lag 대응
- Zero-downtime migration
- Redis 자료구조
- TTL 전략
- Cache Aside / Write Through / Write Behind
- Cache invalidation
- Hot key 대응
- Session store
- Distributed lock (Redlock, fencing token)
- Cache stampede 방지
- ERD
- Domain model
- Aggregate boundary
- Data consistency rule
- Schema versioning
- Backward compatibility
- Event-driven architecture
- Message Queue: SQS
- Message Queue: Kafka
- Message Queue: RabbitMQ
- Message Queue: BullMQ
- Delivery semantics
- At-least-once
- At-most-once
- Exactly-once (실무 한계)
- Idempotency key
- Deduplication 전략
- Ordering guarantee
- Consumer group
- DLQ
- Retry / Backoff
- Replay / Backfill
- CDC (Debezium 등)
- Outbox Pattern
- Saga Pattern (Choreography / Orchestration)
- Backpressure 제어
- Shadow traffic
- Query optimization
- Index tuning
- Connection pool sizing
- Thread pool sizing
- Cache strategy
- Lock contention 분석
- CPU / Memory profiling
- Bottleneck tracing
- Load test (k6)
- Autoscaling
- Horizontal vs Vertical scaling
- Capacity planning
- Queue depth 기반 scaling
- Hot partition 대응
- Structured logging
- Correlation ID / Trace ID
- Log pipeline (Promtail -> Loki -> S3)
- Log sampling
- PII masking
- RED / USE method
- Prometheus
- Cardinality 관리
- Thanos
- Long-term retention
- OpenTelemetry
- Trace context propagation
- SLI / SLO / Error budget
- Alert fatigue 방지
- Incident runbook
- Reverse Proxy (Nginx, Envoy)
- Load Balancer (L4/L7)
- CDN (Cache Key, TTL, Invalidation)
- DNS 구조 & TTL
- NAT / Public vs Private subnet
- EC2 / ASG / ALB
- VPC / Subnet / NAT / SG
- RDS / Aurora
- ElastiCache
- S3
- IAM
- SQS / SNS / EventBridge
- CloudWatch
- EBS vs Instance store
- Docker
- Docker Compose
- Multi-stage build
- Image size optimization
- Pod / Deployment / Service / Ingress
- HPA / VPA
- ConfigMap / Secret
- Resource request / limit
- Liveness / Readiness probe
- PodDisruptionBudget
- Node autoscaling
- Git Flow / Trunk based
- GitHub Actions
- Build cache
- Docker image build pipeline
- Helm
- ArgoCD (GitOps)
- Blue/Green
- Canary
- Feature flag 시스템
- Rollback 전략
- Zero-downtime deployment
- DB migration 전략
- Unit test
- Integration test
- E2E test (supertest)
- Contract test
- Test fixture 전략
- Test isolation
- Deterministic test
- Load test automation
- Chaos testing (optional)
- Session / JWT
- OAuth2 / OIDC
- Refresh Token Rotation
- Token Revocation
- CSRF Protection
- CORS / CSP
- SQL Injection
- XSS / CSRF
- SSRF
- JWT security
- Secret management (KMS / Vault)
- TLS config
- Rate limit
- WAF
- Audit log
- Least privilege IAM
- Dependency vulnerability scanning
- Timeout
- Retry / Backoff
- Circuit breaker
- Bulkhead
- Graceful shutdown
- Idempotent consumer
- Data recovery
- Backup / Restore
- DR strategy (multi-region)
- RCA / Postmortem 문화
- Layered / Clean / Hexagonal
- DDD
- Monolith vs Microservice
- Event-driven
- API versioning
- Backward compatibility
- Schema evolution
- Tech debt management
- ADR (Architecture Decision Record)
- AWS pricing 구조
- Reserved Instance / Savings Plan
- Storage tiering
- Egress cost 관리
- Autoscaling 비용 최적화
- Cost anomaly detection
- Budget alert
- Resource right-sizing
- 기술 의사결정
- 트레이드오프 설명
- 시스템 설계 인터뷰 대응
- 장애 대응 리딩 (Incident Commander)
- 데이터 기반 의사결정
- 멘토링
- 기술 로드맵 수립
- RFC 작성
- Cross-team communication
- 채용 인터뷰