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{ "slug": "agentic-ai-platform/design-architecture/platform-selection/aws-native-agentic-platform", "title": "AWS Native Agentic AI Platform: 매니지드 서비스 기반 Agent 중심 접근", "description": "Amazon Bedrock, Strands Agents SDK, AgentCore를 활용하여 인프라 운영 부담을 줄이고 Agent 개발에 집중하는 플랫폼 접근", "domain": "agentic-ai-platform", "tags": [ "agentcore", "bedrock", "strands", "aws-native", "mcp", "a2a" ], "created": "2026-03-18", "updated": "2026-06-28", "reading_time": 18, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/design-architecture/platform-selection/aws-native-agentic-platform", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/design-architecture/platform-selection/aws-native-agentic-platform.md", "related": [ "agentic-ai-platform/design-architecture/platform-selection/agentic-ai-solutions-eks", "agentic-ai-platform/design-architecture/foundations/agentic-ai-challenges", 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"agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-deployment", "agentic-ai-platform/design-architecture/platform-selection/agentic-ai-solutions-eks" ] }, { "slug": "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management", "title": "GPU 리소스 관리", "description": "EKS에서 Karpenter, KEDA, DRA를 활용한 GPU 리소스 관리 및 비용 최적화", "domain": "agentic-ai-platform", "tags": [ "gpu", "karpenter", "keda", "dra", "autoscaling", "cost-optimization", "eks", "kubernetes" ], "created": "2026-02-05", "updated": "2026-06-28", "reading_time": 15, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management.md", "related": [ "agentic-ai-platform/model-serving/gpu-infrastructure/nvidia-gpu-stack", 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}, { "slug": "agentic-ai-platform/model-serving/index", "title": "모델 서빙 & 추론 인프라", "description": "GPU 인프라 계층과 추론·학습 프레임워크 계층으로 나뉜 모델 서빙 가이드", "domain": "agentic-ai-platform", "tags": [ "model-serving", "gpu", "vllm", "llm-d", "inference", "eks" ], "created": "2026-03-06", "updated": "2026-06-26", "reading_time": 4, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/index.md", "related": [] }, { "slug": "agentic-ai-platform/model-serving/inference-frameworks/hyperpod-inference-operator", "title": "HyperPod Inference Operator (관리형 KV 캐시·지능형 라우팅)", "description": "SageMaker HyperPod Inference Operator의 관리형 KV 캐시·지능형 라우팅·DPD를 Tiered Gateway와 비교하고, L2 추론 라우팅 레이어로서의 역할과 한계를 정리", "domain": "agentic-ai-platform", "tags": [ "hyperpod", "sagemaker", "eks", "vllm", "kv-cache", "inference", "model-serving" ], "created": "2026-06-23", "updated": 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"https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-frameworks/llm-d-eks-automode.md", "related": [ "agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-deployment", "agentic-ai-platform/model-serving/gpu-infrastructure/eks-gpu-node-strategy", "agentic-ai-platform/model-serving/gpu-infrastructure/nvidia-gpu-stack", "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "agentic-ai-platform/model-serving/inference-frameworks/moe-model-serving", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management" ] }, { "slug": "agentic-ai-platform/model-serving/inference-frameworks/moe-model-serving", "title": "MoE 모델 서빙 개념 가이드", "description": "Mixture of Experts 모델의 아키텍처 개념, 분산 배포 전략, 성능 최적화 원리", "domain": "agentic-ai-platform", "tags": [ "eks", "moe", "vllm", "model-serving", "gpu", "mixtral", "inference", "architecture" ], "created": "2026-02-05", "updated": "2026-06-28", 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"agentic-ai-platform", "tags": [ "nemo", "nvidia", "fine-tuning", "tensorrt-llm", "triton", "nccl", "distributed-training", "training" ], "created": "2026-02-05", "updated": "2026-06-28", "reading_time": 9, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-frameworks/nemo-framework", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-frameworks/nemo-framework.md", "related": [ "agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-pipeline", "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management", "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "agentic-ai-platform/model-serving/inference-frameworks/moe-model-serving" ] }, { "slug": "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "title": "vLLM 모델 서빙", "description": "vLLM의 PagedAttention, 병렬화 전략, Multi-LoRA, 하드웨어 지원 아키텍처", "domain": "agentic-ai-platform", "tags": [ "vllm", "paged-attention", "tensor-parallel", "pipeline-parallel", "multi-lora", "serving", "inference", "gpu", "optimization" ], "created": "2026-02-05", "updated": "2026-06-28", "reading_time": 19, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving.md", "related": [ "agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-deployment", "agentic-ai-platform/model-serving/inference-frameworks/moe-model-serving", "agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-pipeline", "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup", "agentic-ai-platform/model-serving/inference-frameworks/llm-d-eks-automode", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management" ] }, { "slug": "agentic-ai-platform/model-serving/inference-infrastructure-overview", "title": "추론 인프라 전체 구조와 튜닝 레이어", "description": "LLM 추론이 인프라 레벨에서 동작하는 전체 요청 경로와, 계층별 튜닝 레버(인퍼런스 게이트웨이·prefill/decode 분리·context/KV cache-aware 라우팅·LMCache·캐시 히트 전략)를 한 장의 지도로 정리", "domain": "agentic-ai-platform", "tags": [ "inference", "architecture", "inference-gateway", "kv-cache", "routing", "eks" ], "created": "2026-06-25", "updated": "2026-06-28", "reading_time": 15, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-infrastructure-overview", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-infrastructure-overview.md", "related": [ "agentic-ai-platform/model-serving/inference-routing/tiered-gateway-architecture", "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management", "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "agentic-ai-platform/model-serving/inference-optimization/disaggregated-serving", "agentic-ai-platform/model-serving/inference-optimization/lmcache", "agentic-ai-platform/model-serving/inference-optimization/cache-hit-strategy", "agentic-ai-platform/model-serving/inference-optimization/index", "agentic-ai-platform/model-serving/inference-frameworks/hyperpod-inference-operator", "agentic-ai-platform/model-serving/inference-routing/request-cascading", "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy" ] }, { "slug": "agentic-ai-platform/model-serving/inference-optimization/cache-hit-strategy", "title": "캐시 히트 전략", "description": "KV/Prefix·Prompt·Semantic 3계층 추론 캐시를 하나의 의사결정 프레임으로 통합하고, 계층별 히트율 목표와 측정 지점, 튜닝 레버를 정리", "domain": "agentic-ai-platform", "tags": [ "caching", "kv-cache", "semantic-caching", "cost-optimization", "inference" ], "created": "2026-06-25", "updated": "2026-06-28", "reading_time": 6, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-optimization/cache-hit-strategy", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-optimization/cache-hit-strategy.md", "related": [ "agentic-ai-platform/model-serving/inference-infrastructure-overview", "agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy", "agentic-ai-platform/model-serving/inference-optimization/lmcache" ] }, { "slug": 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"agentic-ai-platform/model-serving/inference-frameworks/llm-d-eks-automode" ] }, { "slug": "agentic-ai-platform/model-serving/inference-optimization/gpu-autoscaling-operations", "title": "GPU 오토스케일링과 대형 모델 배포 운영", "description": "LLM 서빙을 위한 2-Tier GPU 오토스케일링(KEDA·Karpenter)·DRA 호환성과 대형 MoE 모델(GLM-5·Kimi K2.5) 배포에서 축적된 실전 운영 교훈", "domain": "agentic-ai-platform", "tags": [ "inference", "optimization", "gpu", "karpenter", "keda", "autoscaling", "lessons-learned" ], "created": "2026-04-03", "updated": "2026-06-28", "reading_time": 13, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-optimization/gpu-autoscaling-operations", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-optimization/gpu-autoscaling-operations.md", "related": [ "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management", "agentic-ai-platform/model-serving/inference-optimization/index", "agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "agentic-ai-platform/model-serving/inference-optimization/disaggregated-serving" ] }, { "slug": "agentic-ai-platform/model-serving/inference-optimization/index", "title": "Inference Optimization on EKS", "description": "LLM Inference 성능을 극대화하는 EKS 아키텍처 개요 — vLLM, KV Cache-Aware Routing, Disaggregated Serving, LWS 멀티노드, GPU 오토스케일링의 시작점", "domain": "agentic-ai-platform", "tags": [ "inference", "optimization", "eks", "gpu", "vllm", "architecture" ], "created": "2026-04-03", "updated": "2026-06-26", "reading_time": 14, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-optimization", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-optimization/index.md", "related": [ "agentic-ai-platform/model-serving/inference-infrastructure-overview", "agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "agentic-ai-platform/model-serving/inference-optimization/disaggregated-serving", "agentic-ai-platform/model-serving/inference-optimization/gpu-autoscaling-operations", "agentic-ai-platform/model-serving/gpu-infrastructure/eks-gpu-node-strategy", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management", "agentic-ai-platform/model-serving/gpu-infrastructure/nvidia-gpu-stack", "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "agentic-ai-platform/model-serving/inference-frameworks/llm-d-eks-automode", "agentic-ai-platform/model-serving/inference-frameworks/moe-model-serving" ] }, { "slug": "agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "title": "KV Cache 최적화 (vLLM Deep Dive + Cache-Aware Routing)", "description": "vLLM PagedAttention·Continuous Batching·FP8 KV Cache 등 핵심 기술 정리와 llm-d/NVIDIA Dynamo의 KV Cache-Aware Routing 비교 및 Gateway 구성", "domain": "agentic-ai-platform", "tags": [ "inference", "optimization", "vllm", "kv-cache", "paged-attention", "llm-d" ], "created": "2026-04-03", "updated": "2026-06-28", "reading_time": 9, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization.md", "related": [ "agentic-ai-platform/model-serving/inference-optimization/disaggregated-serving", "agentic-ai-platform/model-serving/inference-optimization/gpu-autoscaling-operations", "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "agentic-ai-platform/model-serving/inference-frameworks/llm-d-eks-automode", "agentic-ai-platform/model-serving/gpu-infrastructure/nvidia-gpu-stack", "agentic-ai-platform/model-serving/inference-optimization/cache-hit-strategy", "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy" ] }, { "slug": "agentic-ai-platform/model-serving/inference-optimization/lmcache", "title": "LMCache: KV 캐시 오프로딩과 공유", "description": "GPU 메모리 너머 CPU·디스크로 KV 캐시를 오프로딩하고 추론 인스턴스 간 공유하는 LMCache의 개념과, vLLM prefix cache·NIXL·kvaware 라우팅과의 관계", "domain": "agentic-ai-platform", "tags": [ "lmcache", "kv-cache", "inference", "vllm" ], "created": "2026-06-25", "updated": "2026-06-28", "reading_time": 6, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-optimization/lmcache", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-optimization/lmcache.md", "related": [ "agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "agentic-ai-platform/model-serving/inference-optimization/cache-hit-strategy", "agentic-ai-platform/model-serving/inference-infrastructure-overview", "agentic-ai-platform/model-serving/inference-optimization/disaggregated-serving", "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/model-serving/inference-frameworks/hyperpod-inference-operator", "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy" ] }, { "slug": "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy", "title": "Semantic Caching 전략", "description": "LLM Gateway 레벨 의미 기반 캐싱 전략과 구현 옵션 비교 (GPTCache, Redis Semantic Cache, Portkey, Helicone, Bifrost+Redis)", "domain": "agentic-ai-platform", "tags": [ "semantic-caching", "caching", "cost-optimization", "gateway", "kgateway", "bifrost", "litellm", "portkey", "helicone", "inference-gateway" ], "created": "2026-04-17", "updated": "2026-07-04", "reading_time": 20, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy.md", "related": [ "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "agentic-ai-platform/model-serving/inference-routing/openclaw-example" ] }, { "slug": "agentic-ai-platform/model-serving/inference-routing/cascade-routing-tuning", "title": "Cascade Routing 실전 튜닝", "description": "Inference Gateway Cascade Routing의 분류 임계값·Canary 롤아웃·Fallback·비용 드리프트 경보를 프로덕션 trace 기반으로 튜닝하는 가이드", "domain": "agentic-ai-platform", "tags": [ "cascade-routing", "inference-gateway", "langfuse", "tuning" ], "created": "2026-04-18", "updated": "2026-06-28", "reading_time": 15, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-routing/cascade-routing-tuning", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-routing/cascade-routing-tuning.md", "related": [ "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup", "agentic-ai-platform/reference-architecture/integrations/coding-tools-cost-analysis", "agentic-ai-platform/model-serving/inference-frameworks/vllm-model-serving", "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy" ] }, { "slug": "agentic-ai-platform/model-serving/inference-routing/openclaw-example", "title": "OpenClaw AI Agent Gateway 배포 및 Full Observability", "description": "OpenClaw AI 에이전트 게이트웨이를 EKS에 비용 최적화 배포하고, Bifrost Auto-Router + Cilium Hubble + Langfuse로 Full Observability 구현", "domain": "agentic-ai-platform", "tags": [ "eks", "openclaw", "bifrost", "langfuse", "cilium", "hubble", "bedrock", "graviton", "pod-identity", "observability" ], "created": "2026-03-06", "updated": "2026-06-28", "reading_time": 16, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-routing/openclaw-example", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-routing/openclaw-example.md", "related": [ "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy", "agentic-ai-platform/model-serving/inference-frameworks/llm-d-eks-automode", "agentic-ai-platform/operations-mlops/data-infrastructure/milvus-vector-database", "agentic-ai-platform/operations-mlops/governance/ragas-evaluation" ] }, { "slug": "agentic-ai-platform/model-serving/inference-routing/request-cascading", "title": "Request Cascading — 지능형 모델 라우팅", "description": "요청 복잡도 기반 모델 자동 라우팅 — LLM Classifier·LiteLLM·vLLM Semantic Router 구현 접근 비교와 RouteLLM 연구 참조, 비용 절감 효과", "domain": "agentic-ai-platform", "tags": [ "cascade-routing", "kgateway", "litellm", "bifrost", "vllm-semantic-router", "routellm", "cost-optimization" ], "created": "2026-07-04", "updated": "2026-07-04", "reading_time": 12, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-routing/request-cascading", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-routing/request-cascading.md", "related": [ "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/model-serving/inference-routing/cascade-routing-tuning", "agentic-ai-platform/reference-architecture/inference-gateway/setup/advanced-features" ] }, { "slug": "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "title": "추론 게이트웨이 & LLM Gateway 라우팅 전략", "description": "kgateway + Bifrost/LiteLLM 2-Tier 아키텍처와 Cascade Routing, Semantic Router, Hybrid Routing 설계 패턴", "domain": "agentic-ai-platform", "tags": [ "kgateway", "bifrost", "litellm", "gateway-api", "agentgateway", "cascade-routing", "semantic-caching", "vllm-semantic-router", "epp", "hyperpod-inference-operator", "kong", "kv-cache-aware-routing" ], "created": "2025-02-05", "updated": "2026-07-04", "reading_time": 46, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-routing/routing-strategy", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-routing/routing-strategy.md", "related": [ "agentic-ai-platform/model-serving/inference-routing/tiered-gateway-architecture", "agentic-ai-platform/operations-mlops/governance/ai-gateway-guardrails", "agentic-ai-platform/model-serving/inference-routing/request-cascading", "agentic-ai-platform/model-serving/inference-routing/cascade-routing-tuning", "agentic-ai-platform/model-serving/inference-optimization/kv-cache-optimization", "agentic-ai-platform/model-serving/inference-optimization/semantic-caching-strategy", "agentic-ai-platform/model-serving/inference-routing/openclaw-example", "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup", "agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-deployment", "agentic-ai-platform/reference-architecture/integrations/coding-tools-cost-analysis", "agentic-ai-platform/operations-mlops/observability/llmops-observability", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management", "agentic-ai-platform/model-serving/inference-frameworks/llm-d-eks-automode", "agentic-ai-platform/operations-mlops/observability/agent-monitoring" ] }, { "slug": "agentic-ai-platform/model-serving/inference-routing/tiered-gateway-architecture", "title": "티어드 게이트웨이 아키텍처", "description": "Agentic AI 플랫폼의 게이트웨이 계층 단일 정의: Tier 1 Ingress, Tier 2 추론 라우팅(Inference Extension)과 LLM API 게이트웨이, Agent Data Plane의 역할 구분과 채움 전략", "domain": "agentic-ai-platform", "tags": [ "gateway-api", "inference-gateway", "kgateway", "agentgateway", "networking" ], "created": "2026-06-17", "updated": "2026-06-30", "reading_time": 7, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/model-serving/inference-routing/tiered-gateway-architecture", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/model-serving/inference-routing/tiered-gateway-architecture.md", "related": [ "agentic-ai-platform/design-architecture/foundations/agentic-platform-architecture", "agentic-ai-platform/model-serving/inference-routing/routing-strategy" ] }, { "slug": "agentic-ai-platform/operations-mlops/data-infrastructure/index", "title": "데이터 인프라", "description": "Agentic AI 플랫폼의 벡터 데이터베이스·임베딩 스토어 등 데이터 계층 운영", "domain": "agentic-ai-platform", "tags": [ "operations", "data-infrastructure", "vector-database", "milvus" ], "created": "2026-04-20", "updated": "2026-06-26", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/data-infrastructure", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/data-infrastructure/index.md", "related": [] }, { "slug": "agentic-ai-platform/operations-mlops/data-infrastructure/milvus-vector-database", "title": "Milvus 벡터 데이터베이스 통합", "description": "Amazon EKS에서 Milvus 벡터 데이터베이스를 배포하고 RAG 파이프라인과 통합하는 방법", "domain": "agentic-ai-platform", "tags": [ "milvus", "vector-database", "rag", "kubernetes", "eks", "genai", "embedding" ], "created": "2026-02-05", "updated": "2026-06-28", "reading_time": 10, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/data-infrastructure/milvus-vector-database", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/data-infrastructure/milvus-vector-database.md", "related": [ "agentic-ai-platform/design-architecture/foundations/agentic-platform-architecture", "agentic-ai-platform/design-architecture/foundations/agentic-ai-challenges", "agentic-ai-platform/operations-mlops/governance/ragas-evaluation", "agentic-ai-platform/operations-mlops/observability/agent-monitoring" ] }, { "slug": "agentic-ai-platform/operations-mlops/governance/agentic-playbook", "title": "Agentic Playbook", "description": "Agent 워크플로우를 IaC처럼 선언적으로 정의하고 컴플라이언스를 자동화하는 Playbook 가이드", "domain": "agentic-ai-platform", "tags": [ "playbook", "agent", "langgraph", "guardrails", "compliance", "gitops" ], "created": "2026-04-04", "updated": "2026-06-28", "reading_time": 9, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/governance/agentic-playbook", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/governance/agentic-playbook.md", "related": [ "agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-pipeline", "agentic-ai-platform/operations-mlops/data-infrastructure/milvus-vector-database" ] }, { "slug": "agentic-ai-platform/operations-mlops/governance/ai-gateway-guardrails", "title": "AI Gateway Guardrails", "description": "LLM Gateway 레벨 Guardrails — PII Redaction, Prompt Injection 방어, Content Filtering, 도구 비교와 한국 금융권 컴플라이언스 매핑", "domain": "agentic-ai-platform", "tags": [ "guardrails", "pii", "prompt-injection", "safety", "llm-security", "compliance", "ismsp", "bedrock-guardrails", "nemo-guardrails", "llama-guard" ], "created": "2026-04-17", "updated": "2026-06-28", "reading_time": 24, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/governance/ai-gateway-guardrails", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/governance/ai-gateway-guardrails.md", "related": [ "agentic-ai-platform/operations-mlops/governance/compliance-framework", "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/model-serving/inference-routing/tiered-gateway-architecture", "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "agentic-ai-platform/operations-mlops/observability/llmops-observability", "agentic-ai-platform/design-architecture/platform-selection/agentic-ai-solutions-eks" ] }, { "slug": "agentic-ai-platform/operations-mlops/governance/compliance-framework", "title": "엔터프라이즈 컴플라이언스 프레임워크", "description": "SOC2, ISO27001, 전자금융감독규정, ISMS-P를 AI 운영에 매핑하는 컴플라이언스 가이드", "domain": "agentic-ai-platform", "tags": [ "compliance", "soc2", "iso27001", "isms-p", "audit", "security" ], "created": "2026-04-04", "updated": "2026-06-28", "reading_time": 10, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/governance/compliance-framework", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/governance/compliance-framework.md", "related": [ "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup", "agentic-ai-platform/operations-mlops/governance/ai-gateway-guardrails", "agentic-ai-platform/operations-mlops/observability/llmops-observability" ] }, { "slug": "agentic-ai-platform/operations-mlops/governance/domain-customization", "title": "도메인 특화 (LoRA + RAG)", "description": "LoRA Fine-tuning, VectorRAG, GraphRAG로 기술 도메인 코딩 퀄리티를 높이는 가이드 — FSI SI 실전 시나리오 포함", "domain": "agentic-ai-platform", "tags": [ "lora", "rag", "graphrag", "fsi", "fine-tuning", "domain", "legacy-migration" ], "created": "2026-04-04", "updated": "2026-06-28", "reading_time": 10, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/governance/domain-customization", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/governance/domain-customization.md", "related": [ "agentic-ai-platform/reference-architecture/model-lifecycle/custom-model-pipeline", "agentic-ai-platform/operations-mlops/governance/ragas-evaluation" ] }, { "slug": "agentic-ai-platform/operations-mlops/governance/index", "title": "거버넌스 · 평가 · 컴플라이언스", "description": "품질 평가·운영 플레이북·AI Gateway 가드레일·컴플라이언스·도메인 커스터마이징을 아우르는 거버넌스 문서 모음", "domain": "agentic-ai-platform", "tags": [ "operations", "governance", "compliance", "guardrails", "evaluation" ], "created": "2026-04-20", "updated": "2026-06-26", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/governance", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/governance/index.md", "related": [] }, { "slug": "agentic-ai-platform/operations-mlops/governance/ragas-evaluation", "title": "Ragas RAG 평가 프레임워크", "description": "Ragas를 활용한 RAG 파이프라인 품질 평가 및 지속적 개선 방법", "domain": "agentic-ai-platform", "tags": [ "ragas", "rag", "evaluation", "llm", "quality", "genai", "testing" ], "created": "2026-02-05", "updated": "2026-06-28", "reading_time": 21, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/governance/ragas-evaluation", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/governance/ragas-evaluation.md", "related": [ "agentic-ai-platform/operations-mlops/data-infrastructure/milvus-vector-database", "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "agentic-ai-platform/design-architecture/foundations/agentic-platform-architecture" ] }, { "slug": "agentic-ai-platform/operations-mlops/index", "title": "운영 & 거버넌스", "description": "AI 플랫폼 모니터링, Observability, 평가, 컴플라이언스, 도메인 특화 운영 가이드", "domain": "agentic-ai-platform", "tags": [ "operations", "monitoring", "observability", "mlops", "compliance" ], "created": "2026-03-06", "updated": "2026-06-26", "reading_time": 6, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/index.md", "related": [ "agentic-ai-platform/reference-architecture/index", "agentic-ai-platform/design-architecture/index" ] }, { "slug": "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "title": "AI Agent 모니터링 및 운영", "description": "Langfuse 기반 Agent 모니터링 운영 전용 문서 — 모니터링 아키텍처·핵심 메트릭·PromQL·알림·비용 추적 (도구 비교는 LLMOps Observability 문서 참조)", "domain": "agentic-ai-platform", "tags": [ "eks", "langfuse", "langsmith", "monitoring", "observability", "tracing", "opentelemetry", "operations", "alerting" ], "created": "2026-02-05", "updated": "2026-07-04", "reading_time": 12, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/observability/agent-monitoring", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/observability/agent-monitoring.md", "related": [ "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup", "agentic-ai-platform/model-serving/inference-routing/cascade-routing-tuning", "agentic-ai-platform/operations-mlops/observability/llmops-observability", "agentic-ai-platform/design-architecture/foundations/agentic-platform-architecture", "agentic-ai-platform/operations-mlops/governance/ragas-evaluation" ] }, { "slug": "agentic-ai-platform/operations-mlops/observability/index", "title": "관측성 & 모니터링", "description": "Agent 실행 추적·LLM 호출 모니터링·에이전트 수명주기 관측성을 다루는 문서 모음", "domain": "agentic-ai-platform", "tags": [ "operations", "observability", "monitoring", "langfuse" ], "created": "2026-04-20", "updated": "2026-06-26", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/observability", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/observability/index.md", "related": [] }, { "slug": "agentic-ai-platform/operations-mlops/observability/kagent-kubernetes-agents", "title": "Kagent - Kubernetes AI Agent 관리", "description": "Kagent를 활용한 Kubernetes 환경에서의 AI 에이전트 선언적 관리 아키텍처 및 오케스트레이션 패턴", "domain": "agentic-ai-platform", "tags": [ "eks", "kagent", "kubernetes", "agent", "crd", "operator" ], "created": "2026-02-05", "updated": "2026-06-30", "reading_time": 12, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/observability/kagent-kubernetes-agents", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/operations-mlops/observability/kagent-kubernetes-agents.md", "related": [ "agentic-ai-platform/model-serving/inference-routing/tiered-gateway-architecture", "agentic-ai-platform/operations-mlops/observability/llmops-observability", "agentic-ai-platform/operations-mlops/observability/agent-monitoring", "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup", "agentic-ai-platform/design-architecture/foundations/agentic-platform-architecture", "agentic-ai-platform/model-serving/gpu-infrastructure/gpu-resource-management" ] }, { "slug": "agentic-ai-platform/operations-mlops/observability/llmops-observability", "title": "LLMOps Observability 비교 가이드", "description": "LLMOps Observability 도구 비교 전용 문서 — Langfuse·LangSmith·Helicone·CloudWatch 선택 기준과 하이브리드 아키텍처 (Langfuse 운영은 Agent 모니터링 문서 참조)", "domain": "agentic-ai-platform", "tags": [ "eks", "observability", "langfuse", "langsmith", "helicone", "llmops", "monitoring" ], "created": "2026-03-16", "updated": "2026-07-04", "reading_time": 13, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/operations-mlops/observability/llmops-observability", "md_url": 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"agentic-ai-platform/reference-architecture/model-lifecycle/continuous-training/grpo-dpo-training", "agentic-ai-platform/operations-mlops/governance/ragas-evaluation", "agentic-ai-platform/model-serving/inference-routing/routing-strategy", "agentic-ai-platform/reference-architecture/integrations/monitoring-observability-setup" ] }, { "slug": "agentic-ai-platform/reference-architecture/model-lifecycle/continuous-training/grpo-dpo-training", "title": "GRPO/DPO 학습 Job", "description": "레이블링된 preference 데이터셋으로 NeMo-RL(GRPO)·TRL(DPO) 학습 Job을 Karpenter Spot 노드풀 + Volcano Gang Scheduling으로 실행하는 실전 구성.", "domain": "agentic-ai-platform", "tags": [ "continuous-training", "grpo", "dpo", "training", "nemo", "trl" ], "created": "2026-04-18", "updated": "2026-06-28", "reading_time": 5, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/reference-architecture/model-lifecycle/continuous-training/grpo-dpo-training", "md_url": 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"aidlc/enterprise/agent-versioning/index", "agentic-ai-platform/operations-mlops/governance/ragas-evaluation" ] }, { "slug": "agentic-ai-platform/reference-architecture/model-lifecycle/continuous-training/trace-to-dataset", "title": "Trace → Dataset Materializer", "description": "Langfuse OTel 트레이스를 S3 Parquet/Iceberg로 적재하고 Ragas + LLM Judge Fleet로 Reward를 레이블링해 GRPO/DPO 학습 데이터셋을 자동 구성합니다.", "domain": "agentic-ai-platform", "tags": [ "continuous-training", "langfuse", "ragas", "evaluation", "s3" ], "created": "2026-04-18", "updated": "2026-06-28", "reading_time": 5, "url": "https://devfloor9.github.io/engineering-playbook/docs/agentic-ai-platform/reference-architecture/model-lifecycle/continuous-training/trace-to-dataset", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/agentic-ai-platform/reference-architecture/model-lifecycle/continuous-training/trace-to-dataset.md", "related": [ "agentic-ai-platform/operations-mlops/governance/ragas-evaluation", 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규제 요구사항을 통합하는 실전 구현 가이드 및 단계별 Adoption 로드맵", "domain": "aidlc", "tags": [ "compliance", "implementation", "adoption", "roadmap" ], "created": "2026-04-18", "updated": "2026-06-30", "reading_time": 4, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/enterprise/regulatory-compliance/implementation-guide", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/enterprise/regulatory-compliance/implementation-guide.md", "related": [ "aidlc/enterprise/regulatory-compliance/index", "aidlc/enterprise/regulatory-compliance/frameworks/eu-ai-act", "aidlc/enterprise/regulatory-compliance/frameworks/nist-ai-rmf", "aidlc/enterprise/regulatory-compliance/frameworks/iso-42001", "aidlc/enterprise/regulatory-compliance/frameworks/korea-ai-law", "aidlc/enterprise/governance-framework", "aidlc/methodology/harness-engineering" ] }, { "slug": "aidlc/enterprise/regulatory-compliance/index", "title": "AI 규제 컴플라이언스 프레임워크", "description": "EU AI Act, NIST AI RMF, ISO/IEC 42001, 한국 AI 기본법 4개 프레임워크의 AIDLC 통합 가이드", "domain": "aidlc", "tags": [ "compliance", "regulation", "eu-ai-act", "nist", "iso-42001" ], "created": "2026-04-18", "updated": "2026-06-30", "reading_time": 8, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/enterprise/regulatory-compliance", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/enterprise/regulatory-compliance/index.md", "related": [ "aidlc/enterprise/regulatory-compliance/frameworks/eu-ai-act", "aidlc/enterprise/regulatory-compliance/frameworks/nist-ai-rmf", "aidlc/enterprise/regulatory-compliance/frameworks/iso-42001", "aidlc/enterprise/regulatory-compliance/frameworks/korea-ai-law", "aidlc/enterprise/governance-framework", "aidlc/methodology/harness-engineering", "aidlc/methodology/adaptive-execution", "aidlc/enterprise/adoption-strategy" ] }, { "slug": "aidlc/enterprise/role-composition", "title": "역할 재정의", "description": "AIDLC 엔터프라이즈 - role-composition", "domain": "aidlc", "tags": [ "aidlc", "enterprise", "agentic-ai" ], "created": "2026-04-07", "updated": "2026-06-30", "reading_time": 12, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/enterprise/role-composition", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/enterprise/role-composition.md", "related": [ "aidlc/methodology/ontology-engineering", "aidlc/methodology/harness-engineering", "aidlc/enterprise/cost-estimation", "aidlc/enterprise/adoption-strategy" ] }, { "slug": "aidlc/index", "title": "AIDLC: AI-Driven Development Lifecycle", "description": "AI-Driven Development Lifecycle — AWS Labs 공식 방법론 기반 + DDD·Ontology·Harness 엔터프라이즈 확장", "domain": "aidlc", "tags": [ "aidlc", "methodology" ], "created": "2026-03-23", "updated": "2026-06-30", "reading_time": 6, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/index.md", "related": [ 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"domain": "aidlc", "tags": [ "aidlc", "common-rules", "methodology", "governance" ], "created": "2026-04-18", "updated": "2026-06-30", "reading_time": 14, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/methodology/common-rules", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/methodology/common-rules.md", "related": [ "aidlc/operations/audit-governance", "aidlc/methodology/principles-and-model", "aidlc/methodology/adaptive-execution", "aidlc/methodology/harness-engineering" ] }, { "slug": "aidlc/methodology/ddd-integration", "title": "DDD 통합 — AI 주도 개발에서의 필수 코어", "description": "AIDLC에서 DDD가 필수 코어인 이유 — 도메인 설계부터 논리 설계까지 AI 주도 개발", "domain": "aidlc", "tags": [ "ddd", "domain-driven-design", "mob-elaboration", "kiro", "mcp", "aggregate", "entity", "cqrs", "adr" ], "created": "2026-04-07", "updated": "2026-06-30", "reading_time": 13, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/methodology/ddd-integration", "md_url": 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"updated": "2026-06-30", "reading_time": 16, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/methodology/ontology-engineering", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/methodology/ontology-engineering.md", "related": [ "aidlc/methodology/harness-engineering", "aidlc/methodology/ddd-integration", "aidlc/enterprise/cost-estimation", "aidlc/enterprise/adoption-strategy", "aidlc/operations/autonomous-response" ] }, { "slug": "aidlc/methodology/principles-and-model", "title": "AIDLC 10대 원칙과 실행 모델", "description": "AIDLC의 핵심 철학과 Intent → Unit → Bolt 실행 모델 — AWS Labs 공식 용어 매핑 포함", "domain": "aidlc", "tags": [ "aidlc", "principles", "intent", "unit", "bolt", "methodology" ], "created": "2026-04-07", "updated": "2026-06-30", "reading_time": 20, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/methodology/principles-and-model", "md_url": 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"aidlc", "toolchain" ], "created": "2026-04-07", "updated": "2026-06-30", "reading_time": 2, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/toolchain", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/toolchain/index.md", "related": [ "aidlc/toolchain/ai-coding-agents", "aidlc/toolchain/open-weight-models", "aidlc/toolchain/eks-declarative-automation", "aidlc/toolchain/technology-roadmap" ] }, { "slug": "aidlc/toolchain/open-weight-models", "title": "오픈 웨이트 모델", "description": "데이터 레지던시와 비용 최적화를 위한 오픈 웨이트 모델 활용 전략 — 온프레미스 배포, 하이브리드 구성, TCO 비교", "domain": "aidlc", "tags": [ "aidlc", "toolchain", "tooling", "agentic-ai" ], "created": "2026-04-07", "updated": "2026-06-30", "reading_time": 11, "url": "https://devfloor9.github.io/engineering-playbook/docs/aidlc/toolchain/open-weight-models", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/aidlc/toolchain/open-weight-models.md", "related": [ 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Prometheus 메트릭, TTL 튜닝, 모니터링 아키텍처, 실제 문제 해결 사례 포함", "domain": "eks-best-practices", "tags": [ "eks", "coredns", "dns", "monitoring", "prometheus", "performance" ], "created": "2025-05-20", "updated": "2026-06-30", "reading_time": 16, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/networking-performance/coredns-monitoring-optimization", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/networking-performance/coredns-monitoring-optimization.md", "related": [] }, { "slug": "eks-best-practices/networking-performance/east-west-traffic-best-practice", "title": "East-West 트래픽 최적화: 성능과 비용의 균형", "description": "EKS에서 서비스 간 통신(East-West)의 지연시간을 최소화하고 크로스-AZ 비용을 절감하는 심층 최적화 전략. 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Graceful Shutdown 패턴, Pod 라이프사이클 관리 모범 사례", "domain": "eks-best-practices", "tags": [ "eks", "kubernetes", "probes", "health-check", "graceful-shutdown", "lifecycle", "best-practices" ], "created": "2026-02-12", "updated": "2026-06-30", "reading_time": 68, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/operations-reliability/eks-pod-health-lifecycle", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/operations-reliability/eks-pod-health-lifecycle.md", "related": [] }, { "slug": "eks-best-practices/operations-reliability/eks-pod-scheduling-availability", "title": "EKS Pod 스케줄링 & 가용성 패턴", "description": "Kubernetes Pod 스케줄링 전략, Affinity/Anti-Affinity, PDB, Priority/Preemption, Taints/Tolerations 모범 사례", "domain": "eks-best-practices", "tags": [ "eks", "kubernetes", "scheduling", "affinity", "pdb", "priority", "taints", "tolerations", "descheduler" ], "created": "2026-02-12", "updated": "2026-06-30", "reading_time": 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"https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/operations-reliability/k8s-event-management", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/operations-reliability/k8s-event-management.md", "related": [ "eks-best-practices/operations-reliability/eks-debugging/observability", "eks-best-practices/operations-reliability/node-monitoring-agent", "aidlc/operations/observability-stack" ] }, { "slug": "eks-best-practices/operations-reliability/node-monitoring-agent", "title": "EKS Node Monitoring Agent", "description": "AWS EKS 클러스터의 노드 상태를 자동으로 감지하고 보고하는 Node Monitoring Agent의 아키텍처, 배포 전략, 제한사항, 모범 사례를 다룹니다.", "domain": "eks-best-practices", "tags": [ "eks", "monitoring", "node-monitoring", "aws", "observability", "cloudwatch" ], "created": "2025-08-26", "updated": "2026-06-30", "reading_time": 18, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/operations-reliability/node-monitoring-agent", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/operations-reliability/node-monitoring-agent.md", "related": [ "eks-best-practices/operations-reliability/eks-debugging/index", "eks-best-practices/operations-reliability/eks-pod-health-lifecycle", "eks-best-practices/networking-performance/nitro-architecture-performance-tuning" ] }, { "slug": "eks-best-practices/resource-cost/cost-management", "title": "대규모 EKS 비용 관리: 30-90% 절감 전략", "description": "Amazon EKS 환경에서 30-90%의 획기적 비용 절감을 달성하는 FinOps 전략. 비용 구조 분석, Karpenter 최적화, 도구 선택, 실제 성공 사례 포함", "domain": "eks-best-practices", "tags": [ "eks", "cost-management", "finops", "karpenter", "kubecost", "optimization" ], "created": "2025-02-05", "updated": "2026-06-30", "reading_time": 16, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/resource-cost/cost-management", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/resource-cost/cost-management.md", "related": [ "eks-best-practices/resource-cost/karpenter-autoscaling", "eks-best-practices/operations-reliability/gitops-cluster-operation" ] }, { "slug": "eks-best-practices/resource-cost/eks-resource-optimization", "title": "EKS Pod 리소스 최적화 가이드", "description": "Kubernetes Pod의 CPU/Memory 리소스 설정, QoS 클래스, VPA/HPA 오토스케일링, 리소스 Right-Sizing 전략", "domain": "eks-best-practices", "tags": [ "eks", "kubernetes", "resources", "cpu", "memory", "qos", "vpa", "hpa", "right-sizing", "optimization" ], "created": "2026-02-12", "updated": "2026-06-30", "reading_time": 62, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/resource-cost/eks-resource-optimization", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/resource-cost/eks-resource-optimization.md", "related": [] }, { "slug": "eks-best-practices/resource-cost/index", "title": "리소스 & 비용 최적화", "description": "Karpenter 오토스케일링, Pod 리소스 최적화, EKS 비용 관리 전략", "domain": "eks-best-practices", "tags": [ "eks", "karpenter", "cost-management", "resource-optimization", "finops" ], "created": "2026-03-24", "updated": "2026-06-30", "reading_time": 2, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/resource-cost", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/resource-cost/index.md", "related": [] }, { "slug": "eks-best-practices/resource-cost/karpenter-autoscaling", "title": "Karpenter 기반 EKS 스케일링 전략 종합 가이드", "description": "Amazon EKS에서 Karpenter를 활용한 스케일링 전략 종합 가이드. 반응형/예측형/아키텍처적 복원력 접근법 비교, CloudWatch와 Prometheus 아키텍처 비교, HPA 구성, 프로덕션 패턴 포함", "domain": "eks-best-practices", "tags": [ "eks", "karpenter", "autoscaling", "performance", "cloudwatch", "prometheus", "spot-instances" ], "created": "2025-02-09", "updated": "2026-06-30", "reading_time": 28, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/resource-cost/karpenter-autoscaling", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/resource-cost/karpenter-autoscaling.md", "related": [] }, { "slug": "eks-best-practices/security-authn/eks-api-server-authn-authz", "title": "EKS API Server 인증/인가 가이드", "description": "Non-Standard Caller(CI/CD, 모니터링, 자동화)의 EKS API Server 접근을 위한 인증/인가 Best Practices", "domain": "eks-best-practices", "tags": [ "eks", "security", "authentication", "authorization", "access-entry", "pod-identity", "oidc", "rbac" ], "created": "2026-03-24", "updated": "2026-06-30", "reading_time": 12, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/security-authn/eks-api-server-authn-authz", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/security-authn/eks-api-server-authn-authz.md", "related": [] }, { "slug": "eks-best-practices/security-authn/index", "title": "보안 & 인증", "description": "EKS API Server 인증/인가, IAM 통합, Pod Identity 등 보안 관련 베스트 프랙티스", "domain": "eks-best-practices", "tags": [ "eks", "security", "authentication", "authorization", "iam" ], "created": "2026-03-24", "updated": "2026-06-30", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/eks-best-practices/security-authn", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/eks-best-practices/security-authn/index.md", "related": [] }, { "slug": "hybrid-infrastructure/harbor-hybrid-integration", "title": "Harbor 2.13과 EKS Hybrid Nodes 통합 가이드", "description": "Harbor 2.13 프라이빗 컨테이너 레지스트리를 Amazon EKS Hybrid Nodes (Kubernetes 1.33)와 통합하기 위한 완전한 단계별 가이드로, 설치, SSL/TLS 구성, 인증 및 문제 해결을 다룹니다.", "domain": "hybrid-infrastructure", "tags": [ "eks", "hybrid-nodes", "harbor", "container-registry", "kubernetes", "ssl-tls", "nodeadm" ], "created": "2025-08-20", "updated": "2026-06-30", "reading_time": 4, "url": "https://devfloor9.github.io/engineering-playbook/docs/hybrid-infrastructure/harbor-hybrid-integration", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/hybrid-infrastructure/harbor-hybrid-integration.md", "related": [] }, { "slug": "hybrid-infrastructure/hybrid-nodes-adoption-guide", "title": "EKS Hybrid Nodes 완전 가이드", "description": "Amazon EKS Hybrid Nodes 도입을 위한 완전한 가이드: 아키텍처, 구성, 네트워킹, DNS, GPU 서버, 비용 분석 및 동적 리소스 할당(DRA)", "domain": "hybrid-infrastructure", "tags": [ "eks", "hybrid-nodes", "nodeadm", "kubernetes", "harbor", "networking", "dns", "gpu", "dra", "cost-optimization", "architecture" ], "created": "2025-08-20", "updated": "2026-06-30", "reading_time": 12, "url": "https://devfloor9.github.io/engineering-playbook/docs/hybrid-infrastructure/hybrid-nodes-adoption-guide", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/hybrid-infrastructure/hybrid-nodes-adoption-guide.md", "related": [] }, { "slug": "hybrid-infrastructure/hybrid-nodes-file-storage", "title": "EKS Hybrid Nodes 공유 파일 스토리지 솔루션", "description": "EKS Hybrid Nodes 환경에서 공유 파일 스토리지 구현을 위한 포괄적 가이드로, AWS 관리형 서비스, 엔터프라이즈 스토리지 통합 및 Amazon Linux 2023 대체 접근법을 다룹니다.", "domain": "hybrid-infrastructure", "tags": [ "eks", "hybrid-nodes", "storage", "efs", "fsx", "nfs", "amazon-linux-2023" ], "created": "2025-09-15", "updated": "2026-06-30", "reading_time": 11, "url": "https://devfloor9.github.io/engineering-playbook/docs/hybrid-infrastructure/hybrid-nodes-file-storage", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/hybrid-infrastructure/hybrid-nodes-file-storage.md", "related": [] }, { "slug": "hybrid-infrastructure/hybrid-nodes-networking-gateway", "title": "EKS Hybrid Nodes 네트워킹 라우팅 설계와 Hybrid Nodes Gateway", "description": "EKS Hybrid Nodes의 Node/Pod CIDR 라우팅 요건, CNI NAT 구성의 한계, CGNAT(100.64.0.0/10) 대역 지원, 그리고 Pod 라우팅 요건을 제거하는 Hybrid Nodes Gateway 아키텍처 분석", "domain": "hybrid-infrastructure", "tags": [ "eks", "hybrid-node", "cilium", "networking", "hybrid" ], "created": "2026-06-12", "updated": "2026-06-28", "reading_time": 18, "url": "https://devfloor9.github.io/engineering-playbook/docs/hybrid-infrastructure/hybrid-nodes-networking-gateway", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/hybrid-infrastructure/hybrid-nodes-networking-gateway.md", "related": [ "hybrid-infrastructure/hybrid-nodes-adoption-guide", "eks-best-practices/networking-performance/east-west-traffic-best-practice" ] }, { "slug": "hybrid-infrastructure/index", "title": "Hybrid Infrastructure", "description": "Amazon EKS를 활용한 하이브리드 클라우드 및 멀티 클라우드 환경 구축에 대한 심화 기술 문서", "domain": "hybrid-infrastructure", "tags": [], "created": "2025-02-05", "updated": "2026-06-30", "reading_time": 4, "url": "https://devfloor9.github.io/engineering-playbook/docs/hybrid-infrastructure", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/hybrid-infrastructure/index.md", "related": [ "hybrid-infrastructure/hybrid-nodes-adoption-guide", "hybrid-infrastructure/hybrid-nodes-networking-gateway", "hybrid-infrastructure/sriov-dgx-h200-hybrid", "hybrid-infrastructure/hybrid-nodes-file-storage", "hybrid-infrastructure/harbor-hybrid-integration" ] }, { "slug": "hybrid-infrastructure/sriov-dgx-h200-hybrid", "title": "DGX H200 SR-IOV 네트워킹 구성", "description": "NVIDIA DGX H200 시스템에서 Amazon EKS Hybrid Nodes를 실행할 때 발생하는 SR-IOV VF 이름 불일치 문제를 드라이버 호환성, 영구 명명 및 systemd 오케스트레이션을 통해 해결합니다.", "domain": "hybrid-infrastructure", "tags": [ "eks", "hybrid-nodes", "dgx-h200", "sriov", "infiniband", "networking", "mlnx-ofed" ], "created": "2025-09-01", "updated": "2026-06-30", "reading_time": 12, "url": "https://devfloor9.github.io/engineering-playbook/docs/hybrid-infrastructure/sriov-dgx-h200-hybrid", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/hybrid-infrastructure/sriov-dgx-h200-hybrid.md", "related": [] }, { "slug": "intro", "title": "Engineering Playbook 소개", "description": "클라우드 네이티브 아키텍처 엔지니어링 플레이북 & 벤치마크 리포트", "domain": "getting-started", "tags": [ "kubernetes", "cloud-native", "introduction", "getting-started" ], "created": "2025-09-11", "updated": "2026-06-30", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/intro", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/intro.md", "related": [] }, { "slug": "rosa/index", "title": "ROSA (Red Hat OpenShift on AWS)", "description": "Red Hat OpenShift Service on AWS (ROSA) 구축 및 운영에 대한 기술 문서", "domain": "rosa", "tags": [], "created": "2025-02-05", "updated": "2026-06-30", "reading_time": 6, "url": "https://devfloor9.github.io/engineering-playbook/docs/rosa", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/rosa/index.md", "related": [ "rosa/rosa-demo-installation", "rosa/rosa-security-compliance" ] }, { "slug": "rosa/rosa-demo-installation", "title": "ROSA 데모 설치 가이드", "description": "ROSA 클러스터 설치 데모 - STS 기반 클러스터 생성, IAM 역할 구성, 오토스케일링 설정 및 관리자 접근 구성 가이드", "domain": "rosa", "tags": [ "rosa", "openshift", "installation", "sts", "demo", "autoscaling", "iam" ], "created": "2025-02-05", "updated": "2026-06-30", "reading_time": 3, "url": "https://devfloor9.github.io/engineering-playbook/docs/rosa/rosa-demo-installation", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/rosa/rosa-demo-installation.md", "related": [] }, { "slug": "rosa/rosa-security-compliance", "title": "ROSA 보안 규정 준수 콘솔 접근 제어", "description": "금융권 보안 요구사항을 충족하기 위한 Red Hat Hybrid Cloud Console 접근 제어 방안. IdP, MFA, IP 기반 접근 통제를 통한 안전한 관리자 접근 제어 전략", "domain": "rosa", "tags": [ "rosa", "openshift", "security", "compliance", "idp", "mfa", "financial" ], "created": "2025-02-05", "updated": "2026-06-30", "reading_time": 3, "url": "https://devfloor9.github.io/engineering-playbook/docs/rosa/rosa-security-compliance", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/rosa/rosa-security-compliance.md", "related": [] }, { "slug": "security-governance/default-namespace-incident", "title": "EKS Default Namespace 삭제 시 장애 대응 가이드", "description": "EKS 클러스터에서 default namespace 삭제로 인한 Control Plane 접근 불가 장애의 원인 분석, 복구 절차, 그리고 재발 방지 전략을 다룹니다.", "domain": "security-governance", "tags": [ "eks", "security", "incident-response", "namespace", "troubleshooting" ], "created": "2025-01-07", "updated": "2026-06-30", "reading_time": 16, "url": "https://devfloor9.github.io/engineering-playbook/docs/security-governance/default-namespace-incident", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/security-governance/default-namespace-incident.md", "related": [] }, { "slug": "security-governance/guardduty-extended-threat-detection", "title": "GuardDuty Extended Threat Detection", "description": "Amazon GuardDuty Extended Threat Detection을 활용한 EKS 위협 탐지 및 대응", "domain": "security-governance", "tags": [ "eks", "security", "guardduty", "threat-detection", "mitre" ], "created": "2026-02-09", "updated": "2026-06-30", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/security-governance/guardduty-extended-threat-detection", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/security-governance/guardduty-extended-threat-detection.md", "related": [] }, { "slug": "security-governance/identity-first-security", "title": "Identity-First Security 아키텍처", "description": "EKS Pod Identity 기반 제로트러스트 접근 제어 및 IRSA 마이그레이션 가이드", "domain": "security-governance", "tags": [ "eks", "security", "pod-identity", "irsa", "zero-trust" ], "created": "2026-02-09", "updated": "2026-06-30", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/security-governance/identity-first-security", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/security-governance/identity-first-security.md", "related": [] }, { "slug": "security-governance/index", "title": "Security & Governance", "description": "Amazon EKS 환경에서의 보안 강화 및 컴플라이언스 준수에 대한 심화 기술 문서", "domain": "security-governance", "tags": [], "created": "2025-02-05", "updated": "2026-06-30", "reading_time": 14, "url": "https://devfloor9.github.io/engineering-playbook/docs/security-governance", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/security-governance/index.md", "related": [ "security-governance/default-namespace-incident", "security-governance/identity-first-security", "security-governance/guardduty-extended-threat-detection", "security-governance/kyverno-policy-management", "security-governance/supply-chain-security" ] }, { "slug": "security-governance/kyverno-policy-management", "title": "Kyverno 기반 정책 관리", "description": "Kyverno v1.17+ (현재 v1.18)을 활용한 Kubernetes 정책 관리 및 거버넌스", "domain": "security-governance", "tags": [ "eks", "security", "kyverno", "policy", "governance" ], "created": "2026-02-09", "updated": "2026-06-30", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/security-governance/kyverno-policy-management", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/security-governance/kyverno-policy-management.md", "related": [] }, { "slug": "security-governance/supply-chain-security", "title": "컨테이너 공급망 보안", "description": "컨테이너 이미지 서명, SBOM, CI/CD 보안 게이트를 통한 공급망 보안 강화", "domain": "security-governance", "tags": [ "eks", "security", "supply-chain", "ecr", "sigstore", "sbom" ], "created": "2026-02-09", "updated": "2026-06-30", "reading_time": 1, "url": "https://devfloor9.github.io/engineering-playbook/docs/security-governance/supply-chain-security", "md_url": "https://devfloor9.github.io/engineering-playbook/llm-wiki/security-governance/supply-chain-security.md", "related": [] } ] }