diff --git a/.github/workflows/ci-python.yml b/.github/workflows/ci-python.yml
index 54d1ab1a..e958f8c3 100644
--- a/.github/workflows/ci-python.yml
+++ b/.github/workflows/ci-python.yml
@@ -2,8 +2,6 @@ name: CI (Python/FastAPI)
 
 on:
   push:
-    branches:
-      - feature/onnx
     tags:
       - 'pre-processing-v*'
   pull_request:
@@ -60,17 +58,17 @@ jobs:
       - name: Run Formatter Check (Black)
         run: poetry run black --check .
 
-  test:
-     name: Run Tests
-     runs-on: ubuntu-latest
-     needs: lint
-     defaults:
-       run:
-         working-directory: apps/pre-processing-service
-     steps:
-       - name: Checkout repository
-         uses: actions/checkout@v4
-
+#  test:
+#     name: Run Tests
+#     runs-on: ubuntu-latest
+#     needs: lint
+#     defaults:
+#       run:
+#         working-directory: apps/pre-processing-service
+#     steps:
+#       - name: Checkout repository
+#         uses: actions/checkout@v4
+#
 #       - name: Set up Python 3.11
 #         uses: actions/setup-python@v5
 #         with:
@@ -123,7 +121,7 @@ jobs:
     name: Build Docker Image and push
     runs-on: ubuntu-latest
     needs:
-      - test
+#      - test
       - set-image-tag
     if: startsWith(github.ref, 'refs/tags/pre-processing-v')
 
diff --git a/.github/workflows/deploy-fastapi.yml b/.github/workflows/deploy-fastapi.yml
new file mode 100644
index 00000000..23ee6676
--- /dev/null
+++ b/.github/workflows/deploy-fastapi.yml
@@ -0,0 +1,148 @@
+name: Deploy FastAPI
+on:
+  push:
+    branches:
+      - fix/**
+  workflow_run:
+    workflows: ["CI (Python/FastAPI)"]
+    types: [completed]
+
+jobs:
+  deploy:
+    name: Deploy to AWS FastAPI EC2
+    runs-on: ubuntu-latest
+    if: |
+      github.event.workflow_run.conclusion == 'success' &&
+      startsWith(github.event.workflow_run.head_branch, 'pre-processing-v')
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Create env file
+        run: |
+          echo "DB_HOST=${{ secrets.DB_HOST }}" > .env.prod
+          echo "DB_PORT=${{ secrets.DB_PORT }}" >> .env.prod
+          echo "DB_USER=${{ secrets.DB_USER }}" >> .env.prod
+          echo "DB_PASS=${{ secrets.DB_PASS }}" >> .env.prod
+          echo "DB_NAME=${{ secrets.DB_NAME }}" >> .env.prod
+          echo "LOKI_HOST=${{ secrets.LOKI_HOST }}" >> .env.prod
+          echo "LOKI_USERNAME=${{ secrets.LOKI_USERNAME }}" >> .env.prod
+          echo "LOKI_PASSWORD=${{ secrets.LOKI_PASSWORD }}" >> .env.prod
+          echo "ENV_NAME=${{ secrets.ENV_NAME }}" >> .env.prod
+          echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> .env.prod
+
+      - name: Set repo lowercase
+        run: echo "REPO_LC=${GITHUB_REPOSITORY,,}" >> $GITHUB_ENV
+
+      - name: Copy docker compose files to FastAPI EC2
+        uses: appleboy/scp-action@v0.1.7
+        with:
+          host: ${{ secrets.FASTAPI_SERVER_HOST }}
+          username: ubuntu
+          key: ${{ secrets.SERVER_SSH_KEY }}
+          source: "docker/production-fastapi/docker-compose.yml"
+          target: "~/app"
+
+      - name: Copy .env.prod file to FastAPI EC2
+        uses: appleboy/scp-action@v0.1.7
+        with:
+          host: ${{ secrets.FASTAPI_SERVER_HOST }}
+          username: ubuntu
+          key: ${{ secrets.SERVER_SSH_KEY }}
+          source: ".env.prod"
+          target: "~/app/docker/production/"
+          overwrite: true
+
+      - name: Copy promtail-config to FastAPI EC2
+        uses: appleboy/scp-action@v0.1.7
+        with:
+          host: ${{ secrets.FASTAPI_SERVER_HOST }}
+          username: ubuntu
+          key: ${{ secrets.SERVER_SSH_KEY }}
+          source: "docker/production-fastapi/promtail-config.yml"
+          target: "~/app/docker/production/"
+          overwrite: true
+
+      - name: Check ONNX model on FastAPI EC2
+        id: check-onnx
+        uses: appleboy/ssh-action@v1.0.3
+        with:
+          host: ${{ secrets.FASTAPI_SERVER_HOST }}
+          username: ubuntu
+          key: ${{ secrets.SERVER_SSH_KEY }}
+          script: |
+            if [ -f "~/app/models/klue_bert.onnx" ]; then
+              echo "exists=true" >> $GITHUB_OUTPUT
+            else
+              echo "exists=false" >> $GITHUB_OUTPUT
+            fi
+
+      - name: Copy ONNX to FastAPI EC2
+        if: steps.check-onnx.outputs.exists == 'false'
+        uses: appleboy/scp-action@v0.1.7
+        with:
+          host: ${{ secrets.FASTAPI_SERVER_HOST }}
+          username: ubuntu
+          key: ${{ secrets.SERVER_SSH_KEY }}
+          source: "apps/pre-processing-service/klue_bert.onnx"
+          target: "~/app/models/"
+          overwrite: false
+
+      - name: Deploy on EC2
+        uses: appleboy/ssh-action@v1.0.3
+        with:
+          host: ${{secrets.FASTAPI_SERVER_HOST}}
+          username: ubuntu
+          key: ${{secrets.SERVER_SSH_KEY}}
+          script: |
+            cd ~/app/docker/production
+            
+            echo "${{secrets.GITHUB_TOKEN}}" | docker login ghcr.io -u ${{github.actor}} --password-stdin
+            
+            docker-compose pull
+            
+            docker-compose down
+            
+            docker-compose up -d
+            
+            sleep 5
+            docker-compose ps
+            
+            echo "Waiting for containers to become healthy..."
+            for i in {1..30}; do
+            unhealthy=$(docker ps --filter "health=unhealthy" --format "{{.Names}}")
+            starting=$(docker ps --filter "health=starting" --format "{{.Names}}")
+            if [ -z "$unhealthy" ] && [ -z "$starting" ]; then
+            echo "All containers are healthy!"
+            break
+            fi
+            echo "Waiting... ($i/30)"
+            sleep 2
+            done
+
+            docker image prune -f
+
+      - name: Send Discord notification - Success
+        if: success()
+        uses: Ilshidur/action-discord@master
+        env:
+          DISCORD_WEBHOOK: ${{ secrets.DISCORD_WEBHOOK_URL }}
+        with:
+          args: |
+            **배포 성공**
+            **Repository:** ${{ env.REPO_LC }}
+            **Tag:** ${{ github.ref_name }}
+            **Server:** ${{ secrets.FASTAPI_SERVER_HOST }}
+            **Status:** Success!
+
+      - name: Send Discord notification - Failure
+        if: failure()
+        uses: Ilshidur/action-discord@master
+        env:
+          DISCORD_WEBHOOK: ${{ secrets.DISCORD_WEBHOOK_URL }}
+        with:
+          args: |
+            **배포 실패**
+            **Repository:** ${{ env.REPO_LC }}
+            **Tag:** ${{ github.ref_name }}
+            **Error:** 배포 중 오류가 발생했습니다.
+            **Check:** ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
\ No newline at end of file
diff --git a/.github/workflows/deploy-java.yml b/.github/workflows/deploy-java.yml
index d7526506..db0bc3e0 100644
--- a/.github/workflows/deploy-java.yml
+++ b/.github/workflows/deploy-java.yml
@@ -5,7 +5,7 @@ on:
     branches:
       - fix/**
   workflow_run:
-    workflows: ["CI (Java)", "CI (Python/FastAPI)"]
+    workflows: ["CI (Java)"]
     types: [completed]
 
 
@@ -15,9 +15,7 @@ jobs:
     runs-on: ubuntu-latest
     if: |
       github.event.workflow_run.conclusion == 'success' &&
-      (startsWith(github.event.workflow_run.head_branch, 'user-service-v') ||
-       startsWith(github.event.workflow_run.head_branch, 'pre-processing-v'))
-
+      startsWith(github.event.workflow_run.head_branch, 'user-service-v')
 
     steps:
       - uses: actions/checkout@v4
@@ -28,10 +26,11 @@ jobs:
           echo "DB_USER=${{ secrets.DB_USER }}" >> .env.prod
           echo "DB_PASS=${{ secrets.DB_PASS }}" >> .env.prod
           echo "DB_NAME=${{ secrets.DB_NAME }}" >> .env.prod
-          echo "ENV_NAME=${{ secrets.LOKI_URL }}" >> .env.prod
-          echo "ENV_NAME=${{ secrets.LOKI_USERNAME }}" >> .env.prod
-          echo "ENV_NAME=${{ secrets.LOKI_PASSWORD }}" >> .env.prod
+          echo "LOKI_HOST=${{ secrets.LOKI_HOST }}" >> .env.prod
+          echo "LOKI_USERNAME=${{ secrets.LOKI_USERNAME }}" >> .env.prod
+          echo "LOKI_PASSWORD=${{ secrets.LOKI_PASSWORD }}" >> .env.prod
           echo "ENV_NAME=${{ secrets.ENV_NAME }}" >> .env.prod
+          echo "FASTAPI_SERVER_HOST=${{ secrets.FASTAPI_SERVER_HOST }}" >> .env.prod
 
       - name: Set repo lowercase
         run: echo "REPO_LC=${GITHUB_REPOSITORY,,}" >> $GITHUB_ENV
@@ -75,7 +74,6 @@ jobs:
           target: "~/app/docker/production/"
           overwrite: true
 
-
       - name: Deploy on EC2
         uses: appleboy/ssh-action@v1.0.3
         with:
@@ -140,4 +138,4 @@ jobs:
             **Repository:** ${{ env.REPO_LC }}
             **Tag:** ${{ github.ref_name }}
             **Error:** 배포 중 오류가 발생했습니다.
-            **Check:** ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
\ No newline at end of file
+            **Check:** ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
diff --git a/.gitignore b/.gitignore
index 06344943..aa6f88c9 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,4 +1,7 @@
 .idea
 logs
 *.log
-*.env*
\ No newline at end of file
+*.env*
+__pycache__
+
+*.onnx
\ No newline at end of file
diff --git a/apps/pre-processing-service/app/api/endpoints/test.py b/apps/pre-processing-service/app/api/endpoints/test.py
index 91977a3f..ca1a43b5 100644
--- a/apps/pre-processing-service/app/api/endpoints/test.py
+++ b/apps/pre-processing-service/app/api/endpoints/test.py
@@ -1,4 +1,6 @@
 # app/api/endpoints/embedding.py
+from time import sleep
+
 import loguru
 from fastapi import APIRouter
 from sqlalchemy import text
@@ -8,14 +10,17 @@
 from fastapi import APIRouter
 from typing import Mapping, Any, Dict
 from ...model.schemas import *
+from ...service.blog.blog_create_service import BlogContentService
 from ...service.blog.naver_blog_post_service import NaverBlogPostService
 from ...service.blog.tistory_blog_post_service import TistoryBlogPostService
+from ...service.crawl_service import CrawlService
 from ...service.keyword_service import keyword_search
 from ...service.match_service import MatchService
 from ...service.search_service import SearchService
 
 # from ...service.similarity_service import SimilarityService
 from ...db.db_connecter import engine  # ✅ 우리가 만든 DB 유틸 임포트
+from ...service.similarity_service import SimilarityService
 
 # 이 파일만의 독립적인 라우터를 생성합니다.
 router = APIRouter()
@@ -62,54 +67,66 @@ def with_meta(data: Mapping[str, Any], meta: Mapping[str, Any]) -> Dict[str, Any
 
 @router.get("/tester", response_model=None)
 async def processing_tester():
-    request_dict = {
-        "tag": "naver",
-        "category": "50000000",
-        "start_date": "2025-09-01",
-        "end_date": "2025-09-02",
-    }
     # 네이버 키워드 검색
-    naver_request = RequestNaverSearch(**with_meta(request_dict))
+    naver_request = RequestNaverSearch(tag="naver")
     response_data = await keyword_search(naver_request)
-    keyword = response_data.get("keyword")
+    keyword = response_data["data"].get("keyword")
     loguru.logger.info(keyword)
 
-    keyword = {
-        "keyword": keyword,
-    }
-
     # 싸다구 상품 검색
-    sadagu_request = RequestSadaguSearch(**with_meta(keyword))
-    search_service = SearchService()
-    keyword_result = await search_service.search_products(sadagu_request)
+    sadagu_request = RequestSadaguSearch(keyword=keyword)
+    searchservice = SearchService()
+    keyword_result = await searchservice.search_products(sadagu_request)
     loguru.logger.info(keyword_result)
 
     # 싸다구 상품 매치
-    keyword["search_results"] = keyword_result.get("search_results")
-    keyword_match_request = RequestSadaguMatch(**with_meta(keyword))
+
+    data = keyword_result["data"]
+    keyword_match_request = RequestSadaguMatch(
+        keyword=data.get("keyword"), search_results=data.get("search_results")
+    )
     match_service = MatchService()
     keyword_match_response = match_service.match_products(keyword_match_request)
     loguru.logger.info(keyword_match_response)
 
     # 싸다구 상품 유사도 분석
-    keyword["matched_products"] = keyword_match_response.get("matched_products")
-    keyword_similarity_request = RequestSadaguSimilarity(**with_meta(keyword))
-    # similarity_service = SimilarityService()
-    # keyword_similarity_response = similarity_service.select_product_by_similarity(
-    #     keyword_similarity_request
-    # )
-    # loguru.logger.info(keyword_similarity_response)
-
+    data = keyword_match_response["data"]
+    keyword_similarity_request = RequestSadaguSimilarity(
+        keyword=data.get("keyword"), matched_products=data.get("matched_products")
+    )
+    similarity_service = SimilarityService()
+    keyword_similarity_response = similarity_service.select_product_by_similarity(
+        keyword_similarity_request
+    )
+    loguru.logger.info(keyword_similarity_response)
+    sleep(5)
     # 싸다구 상품 크롤링
+    a = RequestSadaguCrawl(
+        product_url=keyword_similarity_response["data"]["selected_product"].get("url")
+    )
+    crawl = CrawlService()
+    crawl_response = await crawl.crawl_product_detail(a)
+    loguru.logger.info(crawl_response)
 
+    sleep(5)
     # 블로그 생성
+    data = crawl_response
+    rag = RequestBlogCreate(product_info=data.get("product_detail"), target_length=500)
+    blog_service = BlogContentService()
+    rag_data = blog_service.generate_blog_content(rag)
+    loguru.logger.info(rag_data)
 
+    sleep(15)
     # 블로그 배포
-    tistory_service = TistoryBlogPostService()
-    result = tistory_service.post_content(
-        title="안녕하살법",
-        content="안녕하살법 받아치기러기 코드 받아치기",
-        tags=["퉁퉁퉁사후르", "짜라짜라"],
+    data = rag_data
+    # tistory_service = TistoryBlogPostService()
+    naverblogPostService = NaverBlogPostService()
+    result = naverblogPostService.post_content(
+        # blog_id="wtecho331",
+        # blog_pw="wt505033@#",
+        title=data.get("title"),
+        content=data.get("content"),
+        tags=data.get("tags"),
     )
     loguru.logger.info(result)
 
diff --git a/apps/pre-processing-service/app/core/config.py b/apps/pre-processing-service/app/core/config.py
index 69e29d35..2de3833a 100644
--- a/apps/pre-processing-service/app/core/config.py
+++ b/apps/pre-processing-service/app/core/config.py
@@ -76,10 +76,15 @@ class BaseSettingsConfig(BaseSettings):
     db_pass: str
     db_name: str
     env_name: str
+    app_name: str
 
     # MeCab 사전 경로 (자동 감지)
     mecab_path: Optional[str] = None
 
+    # Loki 설정
+    loki_host: str = "localhost"
+    loki_port: int = 3100
+
     # 테스트/추가용 필드
     openai_api_key: Optional[str] = None  # << 이 부분 추가
 
diff --git a/apps/pre-processing-service/app/core/logging_config.py b/apps/pre-processing-service/app/core/logging_config.py
new file mode 100644
index 00000000..50edd1a6
--- /dev/null
+++ b/apps/pre-processing-service/app/core/logging_config.py
@@ -0,0 +1,92 @@
+import os
+from loguru import logger
+import sys
+from contextvars import ContextVar
+
+try:
+    from app.middleware.ServiceLoggerMiddleware import trace_id_context
+except ImportError:
+    trace_id_context: ContextVar[str] = ContextVar("trace_id", default="")
+
+
+def setup_file_logging():
+    """
+    PromTail을 통해 Loki로 전송하기 위한 파일 로깅 설정
+    """
+    # 기존 loguru 핸들러 제거 (기본 콘솔 출력 제거)
+    logger.remove()
+
+    log_dir = "/logs/production"
+
+    os.makedirs(log_dir, exist_ok=True)
+
+    log_file_path = os.path.join(log_dir, "app.log")
+    error_log_file_path = os.path.join(log_dir, "error.log")
+
+    # trace_id를 포함한 structured 로그 포맷
+    def add_trace_id_filter(record):
+        try:
+            current_trace_id = trace_id_context.get()
+            if current_trace_id:
+                record["extra"]["trace_id"] = current_trace_id
+            else:
+                record["extra"]["trace_id"] = ""
+        except LookupError:
+            record["extra"]["trace_id"] = ""
+        return record
+
+    # 파일 로깅에서 LoggingMiddleware 제외하는 필터
+    def exclude_logging_middleware_filter(record):
+        # LoggingMiddleware의 로그는 파일에 기록하지 않음
+        if record["name"] == "app.middleware.logging":
+            return False
+        return add_trace_id_filter(record)
+
+    structured_format = "{time:YYYY-MM-DD HH:mm:ss.SSS} {level: <8} {thread.name: <15} {name}:{function}:{line} [{extra[trace_id]}] {message}"
+
+    logger.add(
+        log_file_path,
+        format=structured_format,
+        level="DEBUG",
+        rotation="100 MB",  # 100MB마다 로테이션
+        retention="7 days",  # 7일간 보관
+        compression="zip",  # 압축
+        enqueue=True,  # 멀티프로세스 안전
+        serialize=False,  # JSON 직렬화 비활성화 (PromTail에서 파싱)
+        backtrace=True,  # 백트레이스 포함
+        diagnose=True,  # 진단 정보 포함
+        filter=exclude_logging_middleware_filter,
+    )
+
+    # 에러 레벨 이상은 별도 파일에도 기록
+    logger.add(
+        error_log_file_path,
+        format=structured_format,
+        level="ERROR",
+        rotation="50 MB",
+        retention="30 days",
+        compression="zip",
+        enqueue=True,
+        serialize=False,
+        backtrace=True,
+        diagnose=True,
+        filter=exclude_logging_middleware_filter,
+    )
+
+    # 개발 환경에서는 콘솔 출력도 유지
+    if os.getenv("ENVIRONMENT", "development") == "development":
+        logger.add(
+            sys.stdout,
+            format="[{extra[trace_id]}] {time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {name}:{function}:{line} | {message}",
+            level="DEBUG",
+            colorize=False,
+            filter=add_trace_id_filter,
+        )
+
+    logger.info("File logging setup completed for PromTail integration")
+    return logger
+
+
+def get_logger():
+    """구성된 로거 인스턴스 반환"""
+    return logger
diff --git a/apps/pre-processing-service/app/main.py b/apps/pre-processing-service/app/main.py
index 9865d845..4bbf3ff1 100644
--- a/apps/pre-processing-service/app/main.py
+++ b/apps/pre-processing-service/app/main.py
@@ -5,6 +5,11 @@
 from fastapi.exceptions import RequestValidationError
 from app.middleware.ServiceLoggerMiddleware import ServiceLoggerMiddleware
 
+# 파일 로깅 설정 초기화
+from app.core.logging_config import setup_file_logging
+
+setup_file_logging()
+
 # --- 애플리케이션 구성 요소 임포트 ---
 from app.api.router import api_router
 from app.middleware.logging import LoggingMiddleware
diff --git a/apps/pre-processing-service/app/middleware/ServiceLoggerMiddleware.py b/apps/pre-processing-service/app/middleware/ServiceLoggerMiddleware.py
index acb120fa..30d3475b 100644
--- a/apps/pre-processing-service/app/middleware/ServiceLoggerMiddleware.py
+++ b/apps/pre-processing-service/app/middleware/ServiceLoggerMiddleware.py
@@ -8,8 +8,12 @@
 
 import json
 import time
+import asyncio
 
-trace_id_context: ContextVar[str] = ContextVar("trace_id", default="NO_TRACE_ID")
+from app.middleware.rds_logger import RDSLogger
+from app.middleware.loki_logger import LokiLogger
+
+trace_id_context: ContextVar[str] = ContextVar("trace_id", default="")
 
 
 class ServiceLoggerMiddleware(BaseHTTPMiddleware):
@@ -18,9 +22,17 @@ class ServiceLoggerMiddleware(BaseHTTPMiddleware):
     URL 패턴을 기반으로 자동으로 서비스 타입 식별 및 로깅
     """
 
-    def __init__(self, app, service_mappings: Dict[str, Dict] = None):
+    def __init__(
+        self,
+        app,
+        service_mappings: Dict[str, Dict] = None,
+        enable_rds: bool = True,
+        enable_loki: bool = True,
+    ):
         """
         :param service_mappings: URL 패턴별 서비스 설정
+        :param enable_rds: RDS 로깅 활성화 여부
+        :param enable_loki: Loki 로깅 활성화 여부
         예: {
             "/keywords/search": {
                 "service_type": "NAVER_CRAWLING",
@@ -31,13 +43,23 @@ def __init__(self, app, service_mappings: Dict[str, Dict] = None):
         """
         super().__init__(app)
         self.service_mappings = service_mappings or self._default_mappings()
+        self.enable_rds = enable_rds
+        self.enable_loki = enable_loki
+
+        # 로거 인스턴스 초기화
+        self.rds_logger = RDSLogger() if enable_rds else None
+        # Loki 직접 로깅 비활성화 - PromTail을 통해 파일로 로깅
+        # self.loki_logger = LokiLogger() if enable_loki else None
+        self.loki_logger = None
 
     def _default_mappings(self) -> Dict[str, Dict]:
         """기본 서비스 매핑 설정"""
         return {
+            # 네이버 키워드 검색
             "/keywords/search": {
                 "service_type": "NAVER_CRAWLING",
                 "track_params": [
+                    "tag",
                     "keyword",
                     "category",
                     "startDate",
@@ -45,25 +67,121 @@ def _default_mappings(self) -> Dict[str, Dict]:
                     "job_id",
                     "schedule_id",
                 ],
-                "response_trackers": ["keyword", "total_keywords", "results_count"],
+                "response_trackers": ["keyword", "total_keyword", "success", "status"],
             },
+            # 블로그 RAG 콘텐츠 생성
+            "/blogs/rag/create": {
+                "service_type": "BLOG_RAG_CREATE",
+                "track_params": [
+                    "keyword",
+                    "product_info",
+                    "content_type",
+                    "target_length",
+                    "job_id",
+                    "schedule_id",
+                    "schedule_his_id",
+                ],
+                "response_trackers": [
+                    "title",
+                    "content_length",
+                    "tags_count",
+                    "success",
+                    "status",
+                ],
+            },
+            # 블로그 배포
             "/blogs/publish": {
                 "service_type": "BLOG_PUBLISH",
                 "track_params": [
                     "tag",
-                    "title",
-                    "content",
-                    "tags",
+                    "blog_id",
+                    "post_title",
+                    "post_content",
+                    "post_tags",
+                    "job_id",
+                    "schedule_id",
+                    "schedule_his_id",
+                ],
+                "response_trackers": [
+                    "tag",
+                    "post_title",
+                    "post_url",
+                    "published_at",
+                    "publish_success",
+                    "metadata",
+                    "success",
+                    "status",
+                ],
+            },
+            # 상품 검색
+            "/products/search": {
+                "service_type": "PRODUCT_SEARCH",
+                "track_params": [
+                    "keyword",
                     "job_id",
                     "schedule_id",
                     "schedule_his_id",
                 ],
                 "response_trackers": [
+                    "keyword",
+                    "search_results_count",
+                    "success",
+                    "status",
+                ],
+            },
+            # 상품 매칭
+            "/products/match": {
+                "service_type": "PRODUCT_MATCH",
+                "track_params": [
+                    "keyword",
+                    "search_results",
                     "job_id",
                     "schedule_id",
                     "schedule_his_id",
+                ],
+                "response_trackers": [
+                    "keyword",
+                    "matched_products_count",
+                    "success",
+                    "status",
+                ],
+            },
+            # 상품 유사도 분석
+            "/products/similarity": {
+                "service_type": "PRODUCT_SIMILARITY",
+                "track_params": [
+                    "keyword",
+                    "matched_products",
+                    "search_results",
+                    "job_id",
+                    "schedule_id",
+                    "schedule_his_id",
+                ],
+                "response_trackers": [
+                    "keyword",
+                    "selected_product",
+                    "reason",
+                    "success",
+                    "status",
+                ],
+            },
+            # 상품 크롤링
+            "/products/crawl": {
+                "service_type": "PRODUCT_CRAWL",
+                "track_params": [
+                    "tag",
+                    "product_url",
+                    "job_id",
+                    "schedule_id",
+                    "schedule_his_id",
+                ],
+                "response_trackers": [
+                    "tag",
+                    "product_url",
+                    "product_detail",
+                    "crawled_at",
+                    "success",
                     "status",
-                    "metadata",
                 ],
             },
         }
@@ -78,7 +196,8 @@ async def dispatch(self, request: Request, call_next):
             return await call_next(request)
 
         # 2. 시작 로깅
-        trace_id = trace_id_context.get("NO_TRACE_ID")
+        trace_id = request.headers.get("X-Request-ID", "")
+        trace_id_context.set(trace_id)
         start_time = time.time()
 
         # 파라미터 추출 및 시작 로그
@@ -91,11 +210,23 @@ async def dispatch(self, request: Request, call_next):
         service_type = service_config["service_type"]
         logger.info(f"[{service_type}_START] trace_id={trace_id}{param_str}")
 
+        # source_id 추출 (job_id, schedule_id 등에서)
+        source_id = self._extract_source_id(params)
+        run_id = params.get("run_id")
+
+        # RDS 및 Loki에 시작 로그 전송
+        start_message = f"[{service_type}_START]{param_str}"
+        await self._log_to_external_systems(
+            "start", service_type, source_id, trace_id, start_message, run_id, params
+        )
+
         # 3. 요청 처리
         try:
             response = await call_next(request)
 
             # 4. 성공 로깅
+            duration_ms = int((time.time() - start_time) * 1000)
+
             if 200 <= response.status_code < 300:
                 await self._log_success_response(
                     service_type,
@@ -105,16 +236,60 @@ async def dispatch(self, request: Request, call_next):
                     response,
                     service_config["response_trackers"],
                 )
+
+                # 외부 로깅 시스템에 성공 로그 전송
+                success_message = f"[{service_type}_SUCCESS]{param_str} status_code={response.status_code}"
+                await self._log_to_external_systems(
+                    "success",
+                    service_type,
+                    source_id,
+                    trace_id,
+                    success_message,
+                    run_id,
+                    params,
+                    duration_ms=duration_ms,
+                )
             else:
                 await self._log_error_response(
                     service_type, trace_id, start_time, param_str, response
                 )
 
+                # 외부 로깅 시스템에 에러 로그 전송
+                error_message = f"[{service_type}_ERROR]{param_str} status_code={response.status_code}"
+                await self._log_to_external_systems(
+                    "error",
+                    service_type,
+                    source_id,
+                    trace_id,
+                    error_message,
+                    run_id,
+                    params,
+                    duration_ms=duration_ms,
+                    error_code=f"HTTP_{response.status_code}",
+                )
+
             return response
 
         except Exception as e:
             # 5. 예외 로깅
+            duration_ms = int((time.time() - start_time) * 1000)
             await self._log_exception(service_type, trace_id, start_time, param_str, e)
+
+            # 외부 로깅 시스템에 예외 로그 전송
+            exception_message = (
+                f"[{service_type}_EXCEPTION]{param_str} exception={str(e)}"
+            )
+            await self._log_to_external_systems(
+                "error",
+                service_type,
+                source_id,
+                trace_id,
+                exception_message,
+                run_id,
+                params,
+                duration_ms=duration_ms,
+                error_code="EXCEPTION",
+            )
             raise
 
     def _get_service_config(self, url_path: str) -> Optional[Dict]:
@@ -248,3 +423,94 @@ async def _log_exception(
             f"execution_time={duration:.4f}s{param_str} "
             f"exception={str(exception)}"
         )
+
+    def _extract_source_id(self, params: Dict[str, Any]) -> int:
+        """파라미터에서 source_id 추출 (job_id, schedule_id 등 우선순위)"""
+        for key in ["job_id", "schedule_id", "task_id", "workflow_id"]:
+            if key in params and params[key]:
+                try:
+                    return int(params[key])
+                except (ValueError, TypeError):
+                    continue
+        return 0  # 기본값
+
+    async def _log_to_external_systems(
+        self,
+        log_type: str,  # start, success, error
+        service_type: str,
+        source_id: int,
+        trace_id: str,
+        message: str,
+        run_id: Optional[int] = None,
+        params: Optional[Dict[str, Any]] = None,
+        duration_ms: Optional[int] = None,
+        error_code: Optional[str] = None,
+    ):
+        """RDS와 Loki에 로그 전송"""
+        tasks = []
+
+        # 로깅할 추가 데이터 준비
+        additional_data = params.copy() if params else {}
+
+        if self.rds_logger:
+            if log_type == "start":
+                task = self.rds_logger.log_start(
+                    service_type, source_id, trace_id, message, run_id, additional_data
+                )
+            elif log_type == "success":
+                task = self.rds_logger.log_success(
+                    service_type,
+                    source_id,
+                    trace_id,
+                    message,
+                    duration_ms,
+                    run_id,
+                    additional_data,
+                )
+            elif log_type == "error":
+                task = self.rds_logger.log_error(
+                    service_type,
+                    source_id,
+                    trace_id,
+                    message,
+                    error_code,
+                    duration_ms,
+                    run_id,
+                    additional_data,
+                )
+            tasks.append(task)
+
+        if self.loki_logger:
+            if log_type == "start":
+                task = self.loki_logger.log_start(
+                    service_type, source_id, trace_id, message, run_id, additional_data
+                )
+            elif log_type == "success":
+                task = self.loki_logger.log_success(
+                    service_type,
+                    source_id,
+                    trace_id,
+                    message,
+                    duration_ms,
+                    run_id,
+                    additional_data,
+                )
+            elif log_type == "error":
+                task = self.loki_logger.log_error(
+                    service_type,
+                    source_id,
+                    trace_id,
+                    message,
+                    error_code,
+                    duration_ms,
+                    run_id,
+                    additional_data,
+                )
+            tasks.append(task)
+
+        # 비동기로 병렬 실행 (로깅 실패가 메인 로직에 영향을 주지 않도록)
+        if tasks:
+            try:
+                await asyncio.gather(*tasks, return_exceptions=True)
+            except Exception as e:
+                logger.debug(f"외부 로깅 시스템 전송 중 일부 실패: {e}")
diff --git a/apps/pre-processing-service/app/middleware/logging.py b/apps/pre-processing-service/app/middleware/logging.py
index 9a8cb6a0..15bfd757 100644
--- a/apps/pre-processing-service/app/middleware/logging.py
+++ b/apps/pre-processing-service/app/middleware/logging.py
@@ -3,11 +3,24 @@
 from loguru import logger
 from starlette.middleware.base import BaseHTTPMiddleware
 
+# trace_id context 변수 import
+try:
+    from app.middleware.ServiceLoggerMiddleware import trace_id_context
+except ImportError:
+    from contextvars import ContextVar
+
+    trace_id_context: ContextVar[str] = ContextVar("trace_id", default="")
+
 
 class LoggingMiddleware(BaseHTTPMiddleware):
     async def dispatch(self, request: Request, call_next):
         start_time = time.time()
 
+        # trace_id 설정 (X-Request-ID 헤더에서)
+        current_trace_id = request.headers.get("X-Request-ID", "")
+        if current_trace_id:
+            trace_id_context.set(current_trace_id)
+
         # 1. 요청 시작 로그
         logger.info(
             "요청 시작: IP='{}' 메서드='{}' URL='{}'",
diff --git a/apps/pre-processing-service/app/middleware/loki_logger.py b/apps/pre-processing-service/app/middleware/loki_logger.py
new file mode 100644
index 00000000..0a4d603c
--- /dev/null
+++ b/apps/pre-processing-service/app/middleware/loki_logger.py
@@ -0,0 +1,198 @@
+import json
+import aiohttp
+import asyncio
+from typing import Dict, List, Any, Optional
+from datetime import datetime
+from loguru import logger
+
+from app.model.execution_log import ExecutionLog
+from app.core.config import settings
+
+
+class LokiLogger:
+    """Loki에 로그를 전송하는 클래스"""
+
+    def __init__(self):
+        self.loki_url = f"{settings.loki_host}:{settings.loki_port}/loki/api/v1/push"
+        self.app_name = settings.app_name
+        self.session = None
+
+    async def _get_session(self) -> aiohttp.ClientSession:
+        """aiohttp 세션 관리"""
+        if self.session is None or self.session.closed:
+            self.session = aiohttp.ClientSession()
+        return self.session
+
+    async def close(self):
+        """세션 종료"""
+        if self.session and not self.session.closed:
+            await self.session.close()
+
+    async def send_log(
+        self,
+        execution_type: str,
+        source_id: int,
+        log_level: str,
+        log_message: str,
+        trace_id: Optional[str] = None,
+        run_id: Optional[int] = None,
+        status: Optional[str] = None,
+        duration_ms: Optional[int] = None,
+        error_code: Optional[str] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """
+        Loki로 로그 전송
+
+        Args:
+            execution_type: task, schedule, job, workflow
+            source_id: 모든 데이터에 대한 ID
+            log_level: INFO, ERROR, WARNING, DEBUG
+            log_message: 로그 메시지
+            trace_id: 추적 ID
+            run_id: 실행 ID
+            status: SUCCESS, ERROR, RUNNING, PENDING
+            duration_ms: 실행 시간(밀리초)
+            error_code: 에러 코드
+            additional_data: 추가 데이터
+
+        Returns:
+            bool: 전송 성공 여부
+        """
+        try:
+            execution_log = ExecutionLog(
+                execution_type=execution_type,
+                source_id=source_id,
+                log_level=log_level,
+                executed_at=datetime.now(),
+                log_message=log_message,
+                trace_id=trace_id,
+                run_id=run_id,
+                status=status,
+                duration_ms=duration_ms,
+                error_code=error_code,
+                reserved4=additional_data,
+            )
+
+            loki_data = execution_log.to_loki_format(self.app_name)
+
+            # Loki push API 형식으로 변환
+            payload = {
+                "streams": [
+                    {
+                        "stream": loki_data["labels"],
+                        "values": [
+                            [
+                                str(loki_data["log"]["timestamp"]),
+                                json.dumps(loki_data["log"], ensure_ascii=False),
+                            ]
+                        ],
+                    }
+                ]
+            }
+
+            session = await self._get_session()
+
+            async with session.post(
+                self.loki_url,
+                json=payload,
+                headers={"Content-Type": "application/json"},
+                timeout=aiohttp.ClientTimeout(total=5),
+            ) as response:
+                if response.status == 204:
+                    # logger.debug(f"Loki 로그 전송 성공: {execution_type} - {log_message[:50]}...")
+                    return True
+                else:
+                    response_text = await response.text()
+                    logger.error(
+                        f"Loki 로그 전송 실패: status={response.status}, response={response_text}"
+                    )
+                    return False
+
+        except asyncio.TimeoutError:
+            logger.error("Loki 로그 전송 타임아웃")
+            return False
+        except Exception as e:
+            logger.error(f"Loki 로그 전송 실패: {str(e)}")
+            return False
+
+    async def log_start(
+        self,
+        execution_type: str,
+        source_id: int,
+        trace_id: str,
+        log_message: str,
+        run_id: Optional[int] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """시작 로그 전송"""
+        return await self.send_log(
+            execution_type=execution_type,
+            source_id=source_id,
+            log_level="INFO",
+            log_message=log_message,
+            trace_id=trace_id,
+            run_id=run_id,
+            status="RUNNING",
+            additional_data=additional_data,
+        )
+
+    async def log_success(
+        self,
+        execution_type: str,
+        source_id: int,
+        trace_id: str,
+        log_message: str,
+        duration_ms: int,
+        run_id: Optional[int] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """성공 로그 전송"""
+        return await self.send_log(
+            execution_type=execution_type,
+            source_id=source_id,
+            log_level="INFO",
+            log_message=log_message,
+            trace_id=trace_id,
+            run_id=run_id,
+            status="SUCCESS",
+            duration_ms=duration_ms,
+            additional_data=additional_data,
+        )
+
+    async def log_error(
+        self,
+        execution_type: str,
+        source_id: int,
+        trace_id: str,
+        log_message: str,
+        error_code: str,
+        duration_ms: Optional[int] = None,
+        run_id: Optional[int] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """에러 로그 전송"""
+        return await self.send_log(
+            execution_type=execution_type,
+            source_id=source_id,
+            log_level="ERROR",
+            log_message=log_message,
+            trace_id=trace_id,
+            run_id=run_id,
+            status="ERROR",
+            duration_ms=duration_ms,
+            error_code=error_code,
+            additional_data=additional_data,
+        )
+
+    def __del__(self):
+        """소멸자에서 세션 정리"""
+        if self.session and not self.session.closed:
+            try:
+                loop = asyncio.get_event_loop()
+                if loop.is_running():
+                    loop.create_task(self.session.close())
+                else:
+                    loop.run_until_complete(self.session.close())
+            except:
+                pass
diff --git a/apps/pre-processing-service/app/middleware/rds_logger.py b/apps/pre-processing-service/app/middleware/rds_logger.py
new file mode 100644
index 00000000..66bad19c
--- /dev/null
+++ b/apps/pre-processing-service/app/middleware/rds_logger.py
@@ -0,0 +1,153 @@
+from typing import Optional
+from datetime import datetime
+import traceback
+from loguru import logger
+
+from app.db.mariadb_manager import MariadbManager
+from app.model.execution_log import ExecutionLog
+
+
+class RDSLogger:
+    """RDS(MariaDB)에 로그를 저장하는 클래스"""
+
+    def __init__(self):
+        self.db_manager = MariadbManager()
+
+    async def log_execution(
+        self,
+        execution_type: str,
+        source_id: int,
+        log_level: str,
+        log_message: str,
+        trace_id: Optional[str] = None,
+        run_id: Optional[int] = None,
+        status: Optional[str] = None,
+        duration_ms: Optional[int] = None,
+        error_code: Optional[str] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """
+        execution_log 테이블에 로그 저장
+
+        Args:
+            execution_type: task, schedule, job, workflow
+            source_id: 모든 데이터에 대한 ID
+            log_level: INFO, ERROR, WARNING, DEBUG
+            log_message: 로그 메시지
+            trace_id: 추적 ID
+            run_id: 실행 ID
+            status: SUCCESS, ERROR, RUNNING, PENDING
+            duration_ms: 실행 시간(밀리초)
+            error_code: 에러 코드
+            additional_data: 추가 데이터 (reserved4에 JSON으로 저장)
+
+        Returns:
+            bool: 저장 성공 여부
+        """
+        try:
+            execution_log = ExecutionLog(
+                execution_type=execution_type,
+                source_id=source_id,
+                log_level=log_level,
+                executed_at=datetime.now(),
+                log_message=log_message,
+                trace_id=trace_id,
+                run_id=run_id,
+                status=status,
+                duration_ms=duration_ms,
+                error_code=error_code,
+                reserved4=additional_data,
+            )
+
+            log_data = execution_log.to_dict()
+
+            # 컬럼명과 값 분리
+            columns = list(log_data.keys())
+            values = list(log_data.values())
+            placeholders = ", ".join(["%s"] * len(values))
+            columns_str = ", ".join(columns)
+
+            insert_query = f"""
+            INSERT INTO execution_log ({columns_str})
+            VALUES ({placeholders})
+            """
+
+            with self.db_manager.get_cursor() as cursor:
+                cursor.execute(insert_query, values)
+
+            # logger.debug(f"RDS 로그 저장 성공: {execution_type} - {log_message[:50]}...")
+            return True
+
+        except Exception as e:
+            logger.error(f"RDS 로그 저장 실패: {str(e)}")
+            logger.error(f"Traceback: {traceback.format_exc()}")
+            return False
+
+    async def log_start(
+        self,
+        execution_type: str,
+        source_id: int,
+        trace_id: str,
+        log_message: str,
+        run_id: Optional[int] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """시작 로그 저장"""
+        return await self.log_execution(
+            execution_type=execution_type,
+            source_id=source_id,
+            log_level="INFO",
+            log_message=log_message,
+            trace_id=trace_id,
+            run_id=run_id,
+            status="RUNNING",
+            additional_data=additional_data,
+        )
+
+    async def log_success(
+        self,
+        execution_type: str,
+        source_id: int,
+        trace_id: str,
+        log_message: str,
+        duration_ms: int,
+        run_id: Optional[int] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """성공 로그 저장"""
+        return await self.log_execution(
+            execution_type=execution_type,
+            source_id=source_id,
+            log_level="INFO",
+            log_message=log_message,
+            trace_id=trace_id,
+            run_id=run_id,
+            status="SUCCESS",
+            duration_ms=duration_ms,
+            additional_data=additional_data,
+        )
+
+    async def log_error(
+        self,
+        execution_type: str,
+        source_id: int,
+        trace_id: str,
+        log_message: str,
+        error_code: str,
+        duration_ms: Optional[int] = None,
+        run_id: Optional[int] = None,
+        additional_data: Optional[dict] = None,
+    ) -> bool:
+        """에러 로그 저장"""
+        return await self.log_execution(
+            execution_type=execution_type,
+            source_id=source_id,
+            log_level="ERROR",
+            log_message=log_message,
+            trace_id=trace_id,
+            run_id=run_id,
+            status="ERROR",
+            duration_ms=duration_ms,
+            error_code=error_code,
+            additional_data=additional_data,
+        )
diff --git a/apps/pre-processing-service/app/model/execution_log.py b/apps/pre-processing-service/app/model/execution_log.py
new file mode 100644
index 00000000..c1bef2e0
--- /dev/null
+++ b/apps/pre-processing-service/app/model/execution_log.py
@@ -0,0 +1,79 @@
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Optional, Dict, Any
+import json
+
+
+@dataclass
+class ExecutionLog:
+    """execution_log 테이블에 대응하는 데이터 모델"""
+
+    execution_type: str  # task, schedule, job, workflow
+    source_id: int  # 모든 데이터에 대한 ID
+    log_level: str  # INFO, ERROR, WARNING, DEBUG
+    executed_at: datetime
+    log_message: str
+    span_id: str = ""  # 테스트값
+    trace_id: Optional[str] = None
+    run_id: Optional[int] = None
+    status: Optional[str] = None  # SUCCESS, ERROR, RUNNING, PENDING
+    duration_ms: Optional[int] = None
+    error_code: Optional[str] = None
+    reserved1: Optional[str] = None
+    reserved2: Optional[str] = None
+    reserved3: Optional[int] = None
+    reserved4: Optional[Dict[str, Any]] = None  # JSON 데이터
+    reserved5: Optional[datetime] = None
+    id: Optional[int] = None  # auto_increment
+
+    def to_dict(self) -> Dict[str, Any]:
+        """딕셔너리로 변환 (DB 삽입용)"""
+        data = {
+            "execution_type": self.execution_type,
+            "source_id": self.source_id,
+            "log_level": self.log_level,
+            "executed_at": self.executed_at,
+            "log_message": self.log_message,
+            "trace_id": self.trace_id,
+            "run_id": self.run_id,
+            "status": self.status,
+            "duration_ms": self.duration_ms,
+            "error_code": self.error_code,
+            "reserved1": self.span_id,
+            "reserved2": self.reserved2,
+            "reserved3": self.reserved3,
+            "reserved4": json.dumps(self.reserved4) if self.reserved4 else None,
+            "reserved5": self.reserved5,
+        }
+        return {k: v for k, v in data.items() if v is not None}
+
+    def to_loki_format(
+        self, app_name: str = "pre-processing-service"
+    ) -> Dict[str, Any]:
+        """Loki 형식으로 변환"""
+
+        labels = {
+            "app": app_name,
+            "env": "develop",
+            "traceId": self.trace_id or "",
+            "spanId": self.span_id,  # 필요시 추가
+            "executionType": self.execution_type,
+            "sourceId": str(self.source_id),
+            "runId": str(self.run_id) if self.run_id else "",
+        }
+
+        log_data = {
+            "timestamp": int(self.executed_at.timestamp() * 1000000000),  # nanoseconds
+            "level": self.log_level,
+            "message": self.log_message,
+            "execution_type": self.execution_type,
+            "source_id": self.source_id,
+            "status": self.status,
+            "duration_ms": self.duration_ms,
+            "error_code": self.error_code,
+        }
+
+        if self.reserved4:
+            log_data.update(self.reserved4)
+
+        return {"labels": labels, "log": log_data}
diff --git a/apps/pre-processing-service/app/model/schemas.py b/apps/pre-processing-service/app/model/schemas.py
index 18d0d99f..36bef959 100644
--- a/apps/pre-processing-service/app/model/schemas.py
+++ b/apps/pre-processing-service/app/model/schemas.py
@@ -129,11 +129,6 @@ class ResponseSadaguSimilarity(ResponseBase[SadaguSimilarityData]):
 
 
 class RequestSadaguCrawl(RequestBase):
-    tag: str = Field(
-        ...,
-        title="크롤링 태그",
-        description="크롤링 유형을 구분하는 태그 (예: 'detail')",
-    )
     product_url: HttpUrl = Field(
         ..., title="상품 URL", description="크롤링할 상품 페이지의 URL"
     )
@@ -141,7 +136,6 @@ class RequestSadaguCrawl(RequestBase):
 
 # 응답 데이터 모델
 class SadaguCrawlData(BaseModel):
-    tag: str = Field(..., title="크롤링 태그", description="크롤링 유형 태그")
     product_url: str = Field(..., title="상품 URL", description="크롤링된 상품 URL")
     product_detail: Optional[Dict] = Field(
         None, title="상품 상세정보", description="크롤링된 상품의 상세 정보"
diff --git a/apps/pre-processing-service/app/service/crawl_service.py b/apps/pre-processing-service/app/service/crawl_service.py
index f54d4db7..df90ba01 100644
--- a/apps/pre-processing-service/app/service/crawl_service.py
+++ b/apps/pre-processing-service/app/service/crawl_service.py
@@ -38,7 +38,6 @@ async def crawl_product_detail(self, request: RequestSadaguCrawl) -> dict:
 
             # 응답 데이터 구성
             data = {
-                "tag": request.tag,
                 "product_url": str(request.product_url),
                 "product_detail": product_detail,
                 "crawled_at": time.strftime("%Y-%m-%d %H:%M:%S"),
diff --git a/apps/pre-processing-service/app/service/keyword_service.py b/apps/pre-processing-service/app/service/keyword_service.py
index 01d61f37..b6341482 100644
--- a/apps/pre-processing-service/app/service/keyword_service.py
+++ b/apps/pre-processing-service/app/service/keyword_service.py
@@ -2,7 +2,7 @@
 import random
 from app.utils.response import Response
 import httpx
-
+from loguru import logger
 from ..errors.CustomException import InvalidItemDataException
 from ..model.schemas import RequestNaverSearch
 from datetime import date, timedelta
@@ -13,7 +13,7 @@ async def keyword_search(request: RequestNaverSearch) -> dict:
     네이버 검색 요청을 처리하는 비즈니스 로직입니다.
     입력받은 데이터를 기반으로 응답 데이터를 생성하여 딕셔너리로 반환합니다.
     """
-
+    logger.info(f"검색 플랫폼: {request.tag}")
     # 키워드 검색
     if request.tag == "naver":
         trending_keywords = await search_naver_rank()
@@ -25,8 +25,10 @@ async def keyword_search(request: RequestNaverSearch) -> dict:
     if not trending_keywords:
         raise InvalidItemDataException()
 
+    keyword = random.choice(list(trending_keywords.values()))
+    logger.info(f"선택된 키워드: {keyword}, 검색된 키워드 수: {len(trending_keywords)}")
     data = {
-        "keyword": random.choice(list(trending_keywords.values())),
+        "keyword": keyword,
         "total_keyword": trending_keywords,
     }
     return Response.ok(data)
@@ -55,11 +57,13 @@ async def search_naver_rank() -> dict[int, str]:
         "50000009",
     ]
     category = random.choice(categorys)
+    logger.info(f"선택된 카테고리:{category}")
     today = date.today()
     yesterday = today - timedelta(days=1)
 
     # 3. 원하는 포맷(YYYY-MM-DD)으로 변환하기
     end_date = today.strftime("%Y-%m-%d")
+    logger.info(f"실행 날짜: {end_date}")
     start_date = yesterday.strftime("%Y-%m-%d")
 
     keywords_dic = {}
@@ -86,7 +90,9 @@ async def search_naver_rank() -> dict[int, str]:
                 httpx.RequestError,
                 json.JSONDecodeError,
             ) as e:
-                print(f"네이버 데이터랩에서 데이터를 가져오는 데 실패했습니다: {e}")
+                logger.error(
+                    f"네이버 데이터랩에서 데이터를 가져오는 데 실패했습니다: {e}"
+                )
                 raise InvalidItemDataException
         return keywords_dic
 
@@ -112,5 +118,5 @@ async def search_naver_store() -> dict[int, str]:
             return keyword_dict
 
         except (httpx.HTTPStatusError, httpx.RequestError, json.JSONDecodeError) as e:
-            print(f"네이버 스토어에서 데이터를 가져오는 데 실패했습니다: {e}")
+            logger.error(f"네이버 스토어에서 데이터를 가져오는 데 실패했습니다: {e}")
             raise InvalidItemDataException from e
diff --git a/apps/pre-processing-service/poetry.lock b/apps/pre-processing-service/poetry.lock
index bb05b60a..a1729b8b 100644
--- a/apps/pre-processing-service/poetry.lock
+++ b/apps/pre-processing-service/poetry.lock
@@ -1,5 +1,141 @@
 # This file is automatically @generated by Poetry 2.1.4 and should not be changed by hand.
 
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.6.1"
+description = "Happy Eyeballs for asyncio"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+    {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"},
+]
+
+[[package]]
+name = "aiohttp"
+version = "3.12.15"
+description = "Async http client/server framework (asyncio)"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
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+
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 version = "0.7.0"
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 name = "fsspec"
 version = "2025.9.0"
@@ -616,14 +866,14 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.181.0"
+version = "2.182.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -1171,6 +1421,126 @@ docs = ["sphinx"]
 gmpy = ["gmpy2 (>=2.1.0a4) ; platform_python_implementation != \"PyPy\""]
 tests = ["pytest (>=4.6)"]
 
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 [[package]]
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 version = "1.26.1"
@@ -2412,14 +2890,14 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "starlette"
-version = "0.47.3"
+version = "0.48.0"
 description = "The little ASGI library that shines."
 optional = false
 python-versions = ">=3.9"
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 [package.dependencies]
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 [package.dependencies]
 h11 = ">=0.9.0,<1"
 
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+    {file = "yarl-1.20.1-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f6342d643bf9a1de97e512e45e4b9560a043347e779a173250824f8b254bd5ce"},
+    {file = "yarl-1.20.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:56dac5f452ed25eef0f6e3c6a066c6ab68971d96a9fb441791cad0efba6140d3"},
+    {file = "yarl-1.20.1-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c7d7f497126d65e2cad8dc5f97d34c27b19199b6414a40cb36b52f41b79014be"},
+    {file = "yarl-1.20.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:67e708dfb8e78d8a19169818eeb5c7a80717562de9051bf2413aca8e3696bf16"},
+    {file = "yarl-1.20.1-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:595c07bc79af2494365cc96ddeb772f76272364ef7c80fb892ef9d0649586513"},
+    {file = "yarl-1.20.1-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:7bdd2f80f4a7df852ab9ab49484a4dee8030023aa536df41f2d922fd57bf023f"},
+    {file = "yarl-1.20.1-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:c03bfebc4ae8d862f853a9757199677ab74ec25424d0ebd68a0027e9c639a390"},
+    {file = "yarl-1.20.1-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:344d1103e9c1523f32a5ed704d576172d2cabed3122ea90b1d4e11fe17c66458"},
+    {file = "yarl-1.20.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:88cab98aa4e13e1ade8c141daeedd300a4603b7132819c484841bb7af3edce9e"},
+    {file = "yarl-1.20.1-cp313-cp313t-win32.whl", hash = "sha256:b121ff6a7cbd4abc28985b6028235491941b9fe8fe226e6fdc539c977ea1739d"},
+    {file = "yarl-1.20.1-cp313-cp313t-win_amd64.whl", hash = "sha256:541d050a355bbbc27e55d906bc91cb6fe42f96c01413dd0f4ed5a5240513874f"},
+    {file = "yarl-1.20.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:e42ba79e2efb6845ebab49c7bf20306c4edf74a0b20fc6b2ccdd1a219d12fad3"},
+    {file = "yarl-1.20.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:41493b9b7c312ac448b7f0a42a089dffe1d6e6e981a2d76205801a023ed26a2b"},
+    {file = "yarl-1.20.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f5a5928ff5eb13408c62a968ac90d43f8322fd56d87008b8f9dabf3c0f6ee983"},
+    {file = "yarl-1.20.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:30c41ad5d717b3961b2dd785593b67d386b73feca30522048d37298fee981805"},
+    {file = "yarl-1.20.1-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:59febc3969b0781682b469d4aca1a5cab7505a4f7b85acf6db01fa500fa3f6ba"},
+    {file = "yarl-1.20.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d2b6fb3622b7e5bf7a6e5b679a69326b4279e805ed1699d749739a61d242449e"},
+    {file = "yarl-1.20.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:749d73611db8d26a6281086f859ea7ec08f9c4c56cec864e52028c8b328db723"},
+    {file = "yarl-1.20.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9427925776096e664c39e131447aa20ec738bdd77c049c48ea5200db2237e000"},
+    {file = "yarl-1.20.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff70f32aa316393eaf8222d518ce9118148eddb8a53073c2403863b41033eed5"},
+    {file = "yarl-1.20.1-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:c7ddf7a09f38667aea38801da8b8d6bfe81df767d9dfc8c88eb45827b195cd1c"},
+    {file = "yarl-1.20.1-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:57edc88517d7fc62b174fcfb2e939fbc486a68315d648d7e74d07fac42cec240"},
+    {file = "yarl-1.20.1-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:dab096ce479d5894d62c26ff4f699ec9072269d514b4edd630a393223f45a0ee"},
+    {file = "yarl-1.20.1-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:14a85f3bd2d7bb255be7183e5d7d6e70add151a98edf56a770d6140f5d5f4010"},
+    {file = "yarl-1.20.1-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:2c89b5c792685dd9cd3fa9761c1b9f46fc240c2a3265483acc1565769996a3f8"},
+    {file = "yarl-1.20.1-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:69e9b141de5511021942a6866990aea6d111c9042235de90e08f94cf972ca03d"},
+    {file = "yarl-1.20.1-cp39-cp39-win32.whl", hash = "sha256:b5f307337819cdfdbb40193cad84978a029f847b0a357fbe49f712063cfc4f06"},
+    {file = "yarl-1.20.1-cp39-cp39-win_amd64.whl", hash = "sha256:eae7bfe2069f9c1c5b05fc7fe5d612e5bbc089a39309904ee8b829e322dcad00"},
+    {file = "yarl-1.20.1-py3-none-any.whl", hash = "sha256:83b8eb083fe4683c6115795d9fc1cfaf2cbbefb19b3a1cb68f6527460f483a77"},
+    {file = "yarl-1.20.1.tar.gz", hash = "sha256:d017a4997ee50c91fd5466cef416231bb82177b93b029906cefc542ce14c35ac"},
+]
+
+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+propcache = ">=0.2.1"
+
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.11,<3.14"
-content-hash = "d02c427c36a8894fe681d04a4c0c45de45d5793a4d264375992ce1104096f620"
+content-hash = "6e10697924e89b5c0f7c3f6ecd79fb64ac412ac2240f75565d6ea5feb3a89a20"
diff --git a/apps/pre-processing-service/pyproject.toml b/apps/pre-processing-service/pyproject.toml
index c724ee24..672bf645 100644
--- a/apps/pre-processing-service/pyproject.toml
+++ b/apps/pre-processing-service/pyproject.toml
@@ -35,6 +35,7 @@ poetry-core=">=2.1.3,<3.0.0"
 dbutils=">=3.1.2,<4.0.0"
 onnxruntime = "^1.22.1"
 openai = "^1.107.3"
+aiohttp = "^3.12.15"
 
 [build-system]
 requires = ["poetry-core>=2.0.0,<3.0.0"]
diff --git a/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/HttpTaskRunner.java b/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/HttpTaskRunner.java
index 9f497b97..861edd5a 100644
--- a/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/HttpTaskRunner.java
+++ b/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/HttpTaskRunner.java
@@ -6,6 +6,7 @@
 import org.springframework.web.client.RestTemplate;
 
 import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.node.ObjectNode;
 
 import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
@@ -14,35 +15,52 @@
 import site.icebang.domain.workflow.model.Task;
 
 @Slf4j
-@Component("httpTaskRunner")
+@Component("httpTaskRunner") // "httpTaskRunner"라는 이름의 Bean으로 등록
 @RequiredArgsConstructor
 public class HttpTaskRunner implements TaskRunner {
+
   private final RestTemplate restTemplate;
 
+  // private final TaskIoDataRepository taskIoDataRepository; // TODO: 입출력 저장을 위해 주입
+
   @Override
-  public TaskExecutionResult execute(Task task, TaskRun taskRun) {
+  public TaskExecutionResult execute(Task task, TaskRun taskRun, ObjectNode requestBody) {
     JsonNode params = task.getParameters();
-    String url = params.get("url").asText();
-    String method = params.get("method").asText();
-    JsonNode body = params.get("body");
+    if (params == null) {
+      return TaskExecutionResult.failure("Task에 파라미터가 정의되지 않았습니다.");
+    }
+
+    String url = params.path("url").asText();
+    String method = params.path("method").asText("POST"); // 기본값 POST
+
+    if (url.isEmpty()) {
+      return TaskExecutionResult.failure("Task 파라미터에 'url'이 없습니다.");
+    }
 
     try {
-      HttpEntity<String> requestEntity =
-          new HttpEntity<>(
-              body.toString(),
-              new HttpHeaders() {
-                {
-                  setContentType(MediaType.APPLICATION_JSON);
-                }
-              });
-
-      ResponseEntity<String> response =
+      // 1. HTTP 헤더 설정
+      HttpHeaders headers = new HttpHeaders();
+      headers.setContentType(MediaType.APPLICATION_JSON);
+
+      // 2. HTTP 요청 엔티티 생성 (헤더 + 동적 Body)
+      HttpEntity<String> requestEntity = new HttpEntity<>(requestBody.toString(), headers);
+
+      log.debug("HTTP Task 요청: URL={}, Method={}, Body={}", url, method, requestBody.toString());
+
+      // 3. RestTemplate으로 API 호출
+      ResponseEntity<String> responseEntity =
           restTemplate.exchange(
               url, HttpMethod.valueOf(method.toUpperCase()), requestEntity, String.class);
 
-      return TaskExecutionResult.success(response.getBody());
+      String responseBody = responseEntity.getBody();
+      log.debug("HTTP Task 응답: Status={}, Body={}", responseEntity.getStatusCode(), responseBody);
+
+      // TODO: taskIoDataRepository를 사용하여 requestBody와 responseBody를 DB에 저장
+
+      return TaskExecutionResult.success(responseBody);
+
     } catch (RestClientException e) {
-      log.error("HTTP Task 실행 실패: TaskRunId={}, Error={}", taskRun.getId(), e.getMessage());
+      log.error("HTTP Task 실행 중 에러 발생: TaskRunId={}, Error={}", taskRun.getId(), e.getMessage());
       return TaskExecutionResult.failure(e.getMessage());
     }
   }
diff --git a/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/TaskRunner.java b/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/TaskRunner.java
index a2b820bb..9c6ab224 100644
--- a/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/TaskRunner.java
+++ b/apps/user-service/src/main/java/site/icebang/domain/workflow/runner/TaskRunner.java
@@ -1,9 +1,14 @@
 package site.icebang.domain.workflow.runner;
 
+import com.fasterxml.jackson.databind.node.ObjectNode;
+
 import site.icebang.domain.execution.model.TaskRun;
 import site.icebang.domain.workflow.model.Task;
 
+/** 워크플로우의 개별 Task를 실행하는 모든 Runner가 구현해야 할 인터페이스 */
 public interface TaskRunner {
+
+  /** Task 실행 결과를 담는 Record. status: SUCCESS 또는 FAILED message: 실행 결과 또는 에러 메시지 */
   record TaskExecutionResult(String status, String message) {
     public static TaskExecutionResult success(String message) {
       return new TaskExecutionResult("SUCCESS", message);
@@ -14,9 +19,17 @@ public static TaskExecutionResult failure(String message) {
     }
 
     public boolean isFailure() {
-      return "FAILED".equals(status);
+      return "FAILED".equals(this.status);
     }
   }
 
-  TaskExecutionResult execute(Task task, TaskRun taskRun);
+  /**
+   * 특정 Task를 실행합니다.
+   *
+   * @param task 실행할 Task의 정적 정의
+   * @param taskRun 현재 실행에 대한 기록 객체
+   * @param requestBody 동적으로 생성된 요청 데이터
+   * @return Task 실행 결과
+   */
+  TaskExecutionResult execute(Task task, TaskRun taskRun, ObjectNode requestBody);
 }
diff --git a/apps/user-service/src/main/java/site/icebang/domain/workflow/service/WorkflowExecutionService.java b/apps/user-service/src/main/java/site/icebang/domain/workflow/service/WorkflowExecutionService.java
index 086b00de..3d0ca0c5 100644
--- a/apps/user-service/src/main/java/site/icebang/domain/workflow/service/WorkflowExecutionService.java
+++ b/apps/user-service/src/main/java/site/icebang/domain/workflow/service/WorkflowExecutionService.java
@@ -1,11 +1,17 @@
 package site.icebang.domain.workflow.service;
 
+import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 
 import org.springframework.stereotype.Service;
 import org.springframework.transaction.annotation.Transactional;
 
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.fasterxml.jackson.databind.node.ObjectNode;
+
 import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
 
@@ -30,18 +36,17 @@ public class WorkflowExecutionService {
   private final JobRunMapper jobRunMapper;
   private final TaskRunMapper taskRunMapper;
   private final Map<String, TaskRunner> taskRunners;
+  private final ObjectMapper objectMapper; // 📌 JSON 처리를 위해 ObjectMapper 주입
 
-  /**
-   * 워크플로우 실행의 시작점. 전체 과정은 하나의 트랜잭션으로 묶입니다.
-   *
-   * @param workflowId 실행할 워크플로우의 ID
-   */
   @Transactional
   public void executeWorkflow(Long workflowId) {
     log.info("========== 워크플로우 실행 시작: WorkflowId={} ==========", workflowId);
     WorkflowRun workflowRun = WorkflowRun.start(workflowId);
     workflowRunMapper.insert(workflowRun);
 
+    // 📌 1. 워크플로우 전체 실행 동안 데이터를 공유할 컨텍스트 생성
+    Map<String, JsonNode> workflowContext = new HashMap<>();
+
     List<Job> jobs = jobMapper.findJobsByWorkflowId(workflowId);
     log.info("총 {}개의 Job을 순차적으로 실행합니다.", jobs.size());
 
@@ -51,7 +56,8 @@ public void executeWorkflow(Long workflowId) {
       log.info(
           "---------- Job 실행 시작: JobId={}, JobRunId={} ----------", job.getId(), jobRun.getId());
 
-      boolean jobSucceeded = executeTasksForJob(jobRun);
+      // 📌 2. Job 내의 Task들을 실행하고, 컨텍스트를 전달하여 데이터 파이프라이닝 수행
+      boolean jobSucceeded = executeTasksForJob(jobRun, workflowContext);
 
       jobRun.finish(jobSucceeded ? "SUCCESS" : "FAILED");
       jobRunMapper.update(jobRun);
@@ -60,7 +66,7 @@ public void executeWorkflow(Long workflowId) {
         workflowRun.finish("FAILED");
         workflowRunMapper.update(workflowRun);
         log.error("Job 실패로 인해 워크플로우 실행을 중단합니다: WorkflowRunId={}", workflowRun.getId());
-        return; // Job이 실패하면 전체 워크플로우를 중단
+        return;
       }
       log.info("---------- Job 실행 성공: JobRunId={} ----------", jobRun.getId());
     }
@@ -70,13 +76,7 @@ public void executeWorkflow(Long workflowId) {
     log.info("========== 워크플로우 실행 성공: WorkflowRunId={} ==========", workflowRun.getId());
   }
 
-  /**
-   * 특정 Job에 속한 Task들을 순차적으로 실행합니다.
-   *
-   * @param jobRun 실행중인 Job의 기록 객체
-   * @return 모든 Task가 성공하면 true, 하나라도 실패하면 false
-   */
-  private boolean executeTasksForJob(JobRun jobRun) {
+  private boolean executeTasksForJob(JobRun jobRun, Map<String, JsonNode> workflowContext) {
     List<Task> tasks = jobMapper.findTasksByJobId(jobRun.getJobId());
     log.info("Job (JobRunId={}) 내 총 {}개의 Task를 실행합니다.", jobRun.getId(), tasks.size());
 
@@ -92,20 +92,76 @@ private boolean executeTasksForJob(JobRun jobRun) {
         taskRun.finish("FAILED", "지원하지 않는 Task 타입: " + task.getType());
         taskRunMapper.update(taskRun);
         log.error("Task 실행 실패 (미지원 타입): TaskRunId={}, Type={}", taskRun.getId(), task.getType());
-        return false; // 실행할 Runner가 없으므로 실패
+        return false;
       }
 
-      TaskRunner.TaskExecutionResult result = runner.execute(task, taskRun);
+      // 📌 3. Task 실행 전, 컨텍스트를 이용해 동적으로 Request Body를 생성
+      ObjectNode requestBody = prepareRequestBody(task, workflowContext);
+
+      // 📌 4. 동적으로 생성된 Request Body를 전달하여 Task 실행
+      TaskRunner.TaskExecutionResult result = runner.execute(task, taskRun, requestBody);
       taskRun.finish(result.status(), result.message());
       taskRunMapper.update(taskRun);
 
       if (result.isFailure()) {
         log.error("Task 실행 실패: TaskRunId={}, Message={}", taskRun.getId(), result.message());
-        return false; // Task가 실패하면 즉시 중단하고 실패 반환
+        return false;
+      }
+
+      // 📌 5. 성공한 Task의 결과를 다음 Task가 사용할 수 있도록 컨텍스트에 저장
+      try {
+        JsonNode resultJson = objectMapper.readTree(result.message());
+        workflowContext.put(task.getName(), resultJson);
+        // TODO: task_io_data 테이블에 requestBody(INPUT)와 resultJson(OUTPUT) 저장
+      } catch (JsonProcessingException e) {
+        log.error("Task 결과 JSON 파싱 실패: TaskRunId={}", taskRun.getId(), e);
+        taskRun.finish("FAILED", "결과 JSON 파싱 실패");
+        taskRunMapper.update(taskRun);
+        return false;
       }
       log.info("Task 실행 성공: TaskRunId={}", taskRun.getId());
     }
+    return true;
+  }
+
+  /** 워크플로우 컨텍스트와 Task의 input_mapping 설정을 기반으로 API 요청에 사용할 동적인 Request Body를 생성합니다. */
+  private ObjectNode prepareRequestBody(Task task, Map<String, JsonNode> context) {
+    ObjectNode requestBody = objectMapper.createObjectNode();
+    JsonNode params = task.getParameters();
+    if (params == null) return requestBody;
+
+    JsonNode mappingRules = params.get("input_mapping");
+    JsonNode staticBody = params.get("body");
 
-    return true; // 모든 Task가 성공적으로 완료됨
+    // 정적 body가 있으면 우선적으로 복사
+    if (staticBody != null && staticBody.isObject()) {
+      requestBody.setAll((ObjectNode) staticBody);
+    }
+
+    // input_mapping 규칙에 따라 동적으로 값 덮어쓰기/추가
+    if (mappingRules != null && mappingRules.isObject()) {
+      mappingRules
+          .fields()
+          .forEachRemaining(
+              entry -> {
+                String targetField = entry.getKey(); // 예: "keyword"
+                String sourcePath = entry.getValue().asText(); // 예: "키워드 검색 태스크.keyword"
+
+                String[] parts = sourcePath.split("\\.", 2);
+                if (parts.length == 2) {
+                  String sourceTaskName = parts[0];
+                  String sourceFieldPath = parts[1];
+
+                  JsonNode sourceData = context.get(sourceTaskName);
+                  if (sourceData != null) {
+                    JsonNode valueToSet = sourceData.at("/" + sourceFieldPath.replace('.', '/'));
+                    if (!valueToSet.isMissingNode()) {
+                      requestBody.set(targetField, valueToSet);
+                    }
+                  }
+                }
+              });
+    }
+    return requestBody;
   }
 }
diff --git a/apps/user-service/src/main/resources/application-develop.yml b/apps/user-service/src/main/resources/application-develop.yml
index 336d62ae..9de00956 100644
--- a/apps/user-service/src/main/resources/application-develop.yml
+++ b/apps/user-service/src/main/resources/application-develop.yml
@@ -23,12 +23,30 @@ spring:
     minimum-idle: 5
     pool-name: HikariCP-MyBatis
 
+  quartz:
+    job-store-type: jdbc
+    auto-startup: true
+    # 📌 Quartz 전용 DataSource 설정을 여기에 추가
+    datasource:
+      url: jdbc:mariadb://localhost:3306/pre_process
+      username: mariadb
+      password: qwer1234
+      driver-class-name: org.mariadb.jdbc.Driver
+      hikari:
+        pool-name: HikariCP-Quartz
+        maximum-pool-size: 5 # Quartz 전용 풀은 더 작게 설정
+    # 📌 Quartz의 자동 스키마 생성 기능 사용
+    jdbc:
+      initialize-schema: never
+      platform: mysql # MariaDB는 mysql 스크립트와 호환
+
   sql:
     init:
       mode: always
       schema-locations:
         - classpath:sql/00-drop-maria.sql
         - classpath:sql/01-schema.sql
+        - classpath:sql/02-quartz-schema.sql
       data-locations:
         - classpath:sql/00-truncate.sql
         - classpath:sql/01-insert-internal-users.sql
@@ -36,23 +54,9 @@ spring:
         - classpath:sql/03-insert-workflow.sql
       encoding: UTF-8
 
-#  # Spring Quartz 스케줄러 설정
-#  quartz:
-#    job-store-type: jdbc
-#    auto-startup: true
-#    jdbc:
-#      initialize-schema: embedded # 운영 환경을 기준으로 기본값 설정
-#    properties:
-#      org.quartz.scheduler.instanceId: AUTO
-#      org.quartz.jobStore.class: org.quartz.impl.jdbcjobstore.JobStoreTX
-#      org.quartz.jobStore.driverDelegateClass: org.quartz.impl.jdbcjobstore.StdJDBCDelegate
-#      org.quartz.jobStore.tablePrefix: QRTZ_ # Quartz 테이블 접두사
-#      org.quartz.threadPool.class: org.quartz.simpl.SimpleThreadPool
-#      org.quartz.threadPool.threadCount: 5 # 개발 환경 스레드 수
-
 mybatis:
   mapper-locations: classpath:mybatis/mapper/**/*.xml
-  type-aliases-package: site.icebang.dto
+  type-aliases-package: site.icebang.domain
   configuration:
     map-underscore-to-camel-case: true
 
diff --git a/apps/user-service/src/main/resources/application.yml b/apps/user-service/src/main/resources/application.yml
index 706eceea..b3b2dcba 100644
--- a/apps/user-service/src/main/resources/application.yml
+++ b/apps/user-service/src/main/resources/application.yml
@@ -16,5 +16,5 @@ mybatis:
 # 외부 API 연동을 위한 설정 섹션
 api:
   fastapi:
-    url: http://pre-processing-service:8000  # FastAPI 서버의 기본 URL
+    url: ${FASTAPI_SERVER_HOST:-http://127.0.0.1:8000}
     timeout: 10000  # API 요청 타임아웃 (밀리초 단위)
\ No newline at end of file
diff --git a/apps/user-service/src/main/resources/sql/02-quartz-schema.sql b/apps/user-service/src/main/resources/sql/02-quartz-schema.sql
new file mode 100644
index 00000000..b0bce890
--- /dev/null
+++ b/apps/user-service/src/main/resources/sql/02-quartz-schema.sql
@@ -0,0 +1,172 @@
+--
+-- In your Quartz properties file, you'll need to set
+-- org.quartz.jobStore.driverDelegateClass = org.quartz.impl.jdbcjobstore.StdJDBCDelegate
+--
+
+CREATE TABLE QRTZ_JOB_DETAILS
+(
+    SCHED_NAME        VARCHAR(120) NOT NULL,
+    JOB_NAME          VARCHAR(200) NOT NULL,
+    JOB_GROUP         VARCHAR(200) NOT NULL,
+    DESCRIPTION       VARCHAR(250) NULL,
+    JOB_CLASS_NAME    VARCHAR(250) NOT NULL,
+    IS_DURABLE        VARCHAR(1)   NOT NULL,
+    IS_NONCONCURRENT  VARCHAR(1)   NOT NULL,
+    IS_UPDATE_DATA    VARCHAR(1)   NOT NULL,
+    REQUESTS_RECOVERY VARCHAR(1)   NOT NULL,
+    JOB_DATA          BLOB         NULL,
+    PRIMARY KEY (SCHED_NAME, JOB_NAME, JOB_GROUP)
+);
+
+CREATE TABLE QRTZ_TRIGGERS
+(
+    SCHED_NAME     VARCHAR(120) NOT NULL,
+    TRIGGER_NAME   VARCHAR(200) NOT NULL,
+    TRIGGER_GROUP  VARCHAR(200) NOT NULL,
+    JOB_NAME       VARCHAR(200) NOT NULL,
+    JOB_GROUP      VARCHAR(200) NOT NULL,
+    DESCRIPTION    VARCHAR(250) NULL,
+    NEXT_FIRE_TIME BIGINT(13)   NULL,
+    PREV_FIRE_TIME BIGINT(13)   NULL,
+    PRIORITY       INTEGER      NULL,
+    TRIGGER_STATE  VARCHAR(16)  NOT NULL,
+    TRIGGER_TYPE   VARCHAR(8)   NOT NULL,
+    START_TIME     BIGINT(13)   NOT NULL,
+    END_TIME       BIGINT(13)   NULL,
+    CALENDAR_NAME  VARCHAR(200) NULL,
+    MISFIRE_INSTR  SMALLINT(2)  NULL,
+    JOB_DATA       BLOB         NULL,
+    PRIMARY KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP),
+    FOREIGN KEY (SCHED_NAME, JOB_NAME, JOB_GROUP)
+        REFERENCES QRTZ_JOB_DETAILS (SCHED_NAME, JOB_NAME, JOB_GROUP)
+);
+
+CREATE TABLE QRTZ_SIMPLE_TRIGGERS
+(
+    SCHED_NAME      VARCHAR(120) NOT NULL,
+    TRIGGER_NAME    VARCHAR(200) NOT NULL,
+    TRIGGER_GROUP   VARCHAR(200) NOT NULL,
+    REPEAT_COUNT    BIGINT(7)    NOT NULL,
+    REPEAT_INTERVAL BIGINT(12)   NOT NULL,
+    TIMES_TRIGGERED BIGINT(10)   NOT NULL,
+    PRIMARY KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP),
+    FOREIGN KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+        REFERENCES QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+);
+
+CREATE TABLE QRTZ_CRON_TRIGGERS
+(
+    SCHED_NAME      VARCHAR(120) NOT NULL,
+    TRIGGER_NAME    VARCHAR(200) NOT NULL,
+    TRIGGER_GROUP   VARCHAR(200) NOT NULL,
+    CRON_EXPRESSION VARCHAR(120) NOT NULL,
+    TIME_ZONE_ID    VARCHAR(80),
+    PRIMARY KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP),
+    FOREIGN KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+        REFERENCES QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+);
+
+CREATE TABLE QRTZ_SIMPROP_TRIGGERS
+(
+    SCHED_NAME    VARCHAR(120)   NOT NULL,
+    TRIGGER_NAME  VARCHAR(200)   NOT NULL,
+    TRIGGER_GROUP VARCHAR(200)   NOT NULL,
+    STR_PROP_1    VARCHAR(512)   NULL,
+    STR_PROP_2    VARCHAR(512)   NULL,
+    STR_PROP_3    VARCHAR(512)   NULL,
+    INT_PROP_1    INT            NULL,
+    INT_PROP_2    INT            NULL,
+    LONG_PROP_1   BIGINT         NULL,
+    LONG_PROP_2   BIGINT         NULL,
+    DEC_PROP_1    NUMERIC(13, 4) NULL,
+    DEC_PROP_2    NUMERIC(13, 4) NULL,
+    BOOL_PROP_1   VARCHAR(1)     NULL,
+    BOOL_PROP_2   VARCHAR(1)     NULL,
+    PRIMARY KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP),
+    FOREIGN KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+        REFERENCES QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+);
+
+CREATE TABLE QRTZ_BLOB_TRIGGERS
+(
+    SCHED_NAME    VARCHAR(120) NOT NULL,
+    TRIGGER_NAME  VARCHAR(200) NOT NULL,
+    TRIGGER_GROUP VARCHAR(200) NOT NULL,
+    BLOB_DATA     BLOB         NULL,
+    PRIMARY KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP),
+    FOREIGN KEY (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+        REFERENCES QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP)
+);
+
+CREATE TABLE QRTZ_CALENDARS
+(
+    SCHED_NAME    VARCHAR(120) NOT NULL,
+    CALENDAR_NAME VARCHAR(200) NOT NULL,
+    CALENDAR      BLOB         NOT NULL,
+    PRIMARY KEY (SCHED_NAME, CALENDAR_NAME)
+);
+
+
+CREATE TABLE QRTZ_PAUSED_TRIGGER_GRPS
+(
+    SCHED_NAME    VARCHAR(120) NOT NULL,
+    TRIGGER_GROUP VARCHAR(200) NOT NULL,
+    PRIMARY KEY (SCHED_NAME, TRIGGER_GROUP)
+);
+
+CREATE TABLE QRTZ_FIRED_TRIGGERS
+(
+    SCHED_NAME        VARCHAR(120) NOT NULL,
+    ENTRY_ID          VARCHAR(95)  NOT NULL,
+    TRIGGER_NAME      VARCHAR(200) NOT NULL,
+    TRIGGER_GROUP     VARCHAR(200) NOT NULL,
+    INSTANCE_NAME     VARCHAR(200) NOT NULL,
+    FIRED_TIME        BIGINT(13)   NOT NULL,
+    SCHED_TIME        BIGINT(13)   NOT NULL,
+    PRIORITY          INTEGER      NOT NULL,
+    STATE             VARCHAR(16)  NOT NULL,
+    JOB_NAME          VARCHAR(200) NULL,
+    JOB_GROUP         VARCHAR(200) NULL,
+    IS_NONCONCURRENT  VARCHAR(1)   NULL,
+    REQUESTS_RECOVERY VARCHAR(1)   NULL,
+    PRIMARY KEY (SCHED_NAME, ENTRY_ID)
+);
+
+CREATE TABLE QRTZ_SCHEDULER_STATE
+(
+    SCHED_NAME        VARCHAR(120) NOT NULL,
+    INSTANCE_NAME     VARCHAR(200) NOT NULL,
+    LAST_CHECKIN_TIME BIGINT(13)   NOT NULL,
+    CHECKIN_INTERVAL  BIGINT(13)   NOT NULL,
+    PRIMARY KEY (SCHED_NAME, INSTANCE_NAME)
+);
+
+CREATE TABLE QRTZ_LOCKS
+(
+    SCHED_NAME VARCHAR(120) NOT NULL,
+    LOCK_NAME  VARCHAR(40)  NOT NULL,
+    PRIMARY KEY (SCHED_NAME, LOCK_NAME)
+);
+
+CREATE INDEX IDX_QRTZ_J_REQ_RECOVERY ON QRTZ_JOB_DETAILS (SCHED_NAME, REQUESTS_RECOVERY);
+CREATE INDEX IDX_QRTZ_J_GRP ON QRTZ_JOB_DETAILS (SCHED_NAME, JOB_GROUP);
+
+CREATE INDEX IDX_QRTZ_T_J ON QRTZ_TRIGGERS (SCHED_NAME, JOB_NAME, JOB_GROUP);
+CREATE INDEX IDX_QRTZ_T_JG ON QRTZ_TRIGGERS (SCHED_NAME, JOB_GROUP);
+CREATE INDEX IDX_QRTZ_T_C ON QRTZ_TRIGGERS (SCHED_NAME, CALENDAR_NAME);
+CREATE INDEX IDX_QRTZ_T_G ON QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_GROUP);
+CREATE INDEX IDX_QRTZ_T_STATE ON QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_STATE);
+CREATE INDEX IDX_QRTZ_T_N_STATE ON QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP, TRIGGER_STATE);
+CREATE INDEX IDX_QRTZ_T_N_G_STATE ON QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_GROUP, TRIGGER_STATE);
+CREATE INDEX IDX_QRTZ_T_NEXT_FIRE_TIME ON QRTZ_TRIGGERS (SCHED_NAME, NEXT_FIRE_TIME);
+CREATE INDEX IDX_QRTZ_T_NFT_ST ON QRTZ_TRIGGERS (SCHED_NAME, TRIGGER_STATE, NEXT_FIRE_TIME);
+CREATE INDEX IDX_QRTZ_T_NFT_MISFIRE ON QRTZ_TRIGGERS (SCHED_NAME, MISFIRE_INSTR, NEXT_FIRE_TIME);
+CREATE INDEX IDX_QRTZ_T_NFT_ST_MISFIRE ON QRTZ_TRIGGERS (SCHED_NAME, MISFIRE_INSTR, NEXT_FIRE_TIME, TRIGGER_STATE);
+CREATE INDEX IDX_QRTZ_T_NFT_ST_MISFIRE_GRP ON QRTZ_TRIGGERS (SCHED_NAME, MISFIRE_INSTR, NEXT_FIRE_TIME, TRIGGER_GROUP, TRIGGER_STATE);
+
+CREATE INDEX IDX_QRTZ_FT_TRIG_INST_NAME ON QRTZ_FIRED_TRIGGERS (SCHED_NAME, INSTANCE_NAME);
+CREATE INDEX IDX_QRTZ_FT_INST_JOB_REQ_RCVRY ON QRTZ_FIRED_TRIGGERS (SCHED_NAME, INSTANCE_NAME, REQUESTS_RECOVERY);
+CREATE INDEX IDX_QRTZ_FT_J_G ON QRTZ_FIRED_TRIGGERS (SCHED_NAME, JOB_NAME, JOB_GROUP);
+CREATE INDEX IDX_QRTZ_FT_JG ON QRTZ_FIRED_TRIGGERS (SCHED_NAME, JOB_GROUP);
+CREATE INDEX IDX_QRTZ_FT_T_G ON QRTZ_FIRED_TRIGGERS (SCHED_NAME, TRIGGER_NAME, TRIGGER_GROUP);
+CREATE INDEX IDX_QRTZ_FT_TG ON QRTZ_FIRED_TRIGGERS (SCHED_NAME, TRIGGER_GROUP);
\ No newline at end of file
diff --git a/apps/user-service/src/main/resources/sql/03-insert-workflow.sql b/apps/user-service/src/main/resources/sql/03-insert-workflow.sql
index dd2ddb15..bff80749 100644
--- a/apps/user-service/src/main/resources/sql/03-insert-workflow.sql
+++ b/apps/user-service/src/main/resources/sql/03-insert-workflow.sql
@@ -1,120 +1,58 @@
--- 워크플로우 관련 데이터 삽입
-
--- 카테고리 삽입
-INSERT INTO `category` (`name`, `description`) VALUES
-                                                   ('마케팅', '마케팅 관련 자동화 워크플로우'),
-                                                   ('콘텐츠', '콘텐츠 생성 및 관리'),
-                                                   ('데이터 수집', '웹 크롤링 및 데이터 수집 관련');
-
--- 워크플로우 생성
-INSERT INTO `workflow` (`name`, `description`, `is_enabled`, `created_by`) VALUES
-    ('트렌드_블로그_자동화', '트렌드 검색부터 블로그 글 작성까지 전체 자동화 프로세스', TRUE, 1);
-
--- Job 생성
-INSERT INTO `job` (`name`, `description`, `is_enabled`, `created_by`) VALUES
-                                                                          ('트렌드_검색_작업', '최신 트렌드 키워드 검색 및 분석', TRUE, 1),
-                                                                          ('싸다구_크롤링_작업', '싸다구 사이트에서 관련 상품 정보 크롤링', TRUE, 1),
-                                                                          ('블로그_글_작성_작업', '수집된 데이터를 바탕으로 블로그 글 자동 생성', TRUE, 1);
-
--- Task 생성
-INSERT INTO `task` (`name`, `type`, `parameters`) VALUES
--- 트렌드 검색 관련 태스크
-('구글_트렌드_검색', 'API_CALL', JSON_OBJECT(
-        'api_endpoint', 'https://trends.googleapis.com/trends/api',
-        'search_region', 'KR',
-        'timeframe', 'now 7-d',
-        'category', '0'
-                          )),
-('네이버_트렌드_검색', 'API_CALL', JSON_OBJECT(
-        'api_endpoint', 'https://datalab.naver.com/keyword/trendSearch.naver',
-        'period', 'week',
-        'device', 'pc'
-                           )),
-('키워드_분석_및_필터링', 'DATA_PROCESSING', JSON_OBJECT(
-        'min_score', 50,
-        'max_keywords', 10,
-        'filter_rules', JSON_ARRAY('adult_content', 'spam_keywords')
-                                    )),
-
--- 싸다구 크롤링 관련 태스크
-('싸다구_상품_검색', 'WEB_SCRAPING', JSON_OBJECT(
-        'base_url', 'https://www.ssg.com',
-        'search_path', '/search.ssg',
-        'max_pages', 3,
-        'delay_ms', 2000
-                              )),
-('상품_정보_추출', 'DATA_EXTRACTION', JSON_OBJECT(
-        'extract_fields', JSON_ARRAY('title', 'price', 'rating', 'review_count', 'image_url'),
-        'data_validation', true
-                                )),
-('가격_비교_분석', 'DATA_ANALYSIS', JSON_OBJECT(
-        'comparison_sites', JSON_ARRAY('쿠팡', '11번가', '옥션'),
-        'price_threshold', 0.1
-                              )),
-
--- 블로그 글 작성 관련 태스크
-('블로그_템플릿_선택', 'TEMPLATE_PROCESSING', JSON_OBJECT(
-        'template_type', 'product_review',
-        'style', 'conversational',
-        'target_length', 1500
-                                      )),
-('AI_콘텐츠_생성', 'AI_GENERATION', JSON_OBJECT(
-        'model', 'gpt-4',
-        'temperature', 0.7,
-        'max_tokens', 2000,
-        'prompt_template', '트렌드 키워드와 상품 정보를 바탕으로 자연스러운 블로그 글을 작성해주세요.'
-                               )),
-('콘텐츠_검수_및_최적화', 'CONTENT_REVIEW', JSON_OBJECT(
-        'seo_optimization', true,
-        'readability_check', true,
-        'plagiarism_check', true
-                                   )),
-('블로그_플랫폼_발행', 'PUBLISHING', JSON_OBJECT(
-        'platforms', JSON_ARRAY('네이버 블로그', '티스토리', '브런치'),
-        'schedule_publish', false,
-        'auto_tags', true
-                             ));
+-- 기존 워크플로우 관련 데이터 삭제
+DELETE FROM `job_task`;
+DELETE FROM `workflow_job`;
+DELETE FROM `task`;
+DELETE FROM `job`;
+DELETE FROM `workflow`;
+DELETE FROM `schedule`;
+
+-- 워크플로우 생성 (ID: 1)
+INSERT INTO `workflow` (`id`, `name`, `description`) VALUES
+    (1, '상품 분석 및 블로그 자동 발행', '키워드 검색부터 상품 분석 후 블로그 발행까지의 자동화 프로세스');
+
+-- Job 생성 (ID: 1, 2)
+INSERT INTO `job` (`id`, `name`, `description`) VALUES
+                                                    (1, '상품 분석', '키워드 검색, 상품 크롤링 및 유사도 분석 작업'),
+                                                    (2, '블로그 콘텐츠 생성', '분석 데이터를 기반으로 RAG 콘텐츠 생성 및 발행 작업');
+
+-- Task 생성 (ID: 1 ~ 7)
+INSERT INTO `task` (`id`, `name`, `type`, `parameters`) VALUES
+                                                            -- Job 1의 Task들
+                                                            (1, '키워드 검색 태스크', 'HTTP', JSON_OBJECT(
+                                                                    'url', 'http://127.0.0.1:8000/keywords/search',
+                                                                    'method', 'POST',
+                                                                    'body', JSON_OBJECT('tag', 'naver') -- 초기 입력값은 정적으로 정의
+                                                                                      )),
+                                                            (2, '상품 검색 태스크', 'HTTP', JSON_OBJECT(
+                                                                    'url', 'http://127.0.0.1:8000/products/search',
+                                                                    'method', 'POST',
+                                                                    'input_mapping', JSON_OBJECT('keyword', '키워드 검색 태스크.keyword') -- "키워드 검색 태스크"의 결과에서 "keyword" 필드를 가져와 매핑
+                                                                                     )),
+                                                            (3, '상품 매칭 태스크', 'HTTP', JSON_OBJECT(
+                                                                    'url', 'http://127.0.0.1:8000/products/match',
+                                                                    'method', 'POST',
+                                                                    'input_mapping', JSON_OBJECT(
+                                                                            'keyword', '키워드 검색 태스크.keyword',
+                                                                            'search_results', '상품 검색 태스크.search_results'
+                                                                                     )
+                                                                                     )),
+                                                            (4, '상품 유사도 분석 태스크', 'HTTP', JSON_OBJECT('url', 'http://127.0.0.1:8000/products/similarity', 'method', 'POST')),
+                                                            (5, '상품 정보 크롤링 태스크', 'HTTP', JSON_OBJECT('url', 'http://127.0.0.1:8000/products/crawl', 'method', 'POST')),
+
+                                                            -- Job 2의 Task들
+                                                            (6, '블로그 RAG 생성 태스크', 'HTTP', JSON_OBJECT('url', 'http://127.0.0.1:8000/blogs/rag/create', 'method', 'POST')),
+                                                            (7, '블로그 발행 태스크', 'HTTP', JSON_OBJECT('url', 'http://127.0.0.1:8000/blogs/publish', 'method', 'POST'));
 
 -- 워크플로우-Job 연결
-INSERT INTO `workflow_job` (`workflow_id`, `job_id`) VALUES
-                                                         (1, 1),  -- 트렌드_블로그_자동화 + 트렌드_검색_작업
-                                                         (1, 2),  -- 트렌드_블로그_자동화 + 싸다구_크롤링_작업
-                                                         (1, 3);  -- 트렌드_블로그_자동화 + 블로그_글_작성_작업
+INSERT INTO `workflow_job` (`workflow_id`, `job_id`, `execution_order`) VALUES
+                                                                            (1, 1, 1),
+                                                                            (1, 2, 2);
 
--- Job-Task 연결 (실행 순서 포함)
--- 트렌드 검색 작업의 태스크들
+-- Job-Task 연결
 INSERT INTO `job_task` (`job_id`, `task_id`, `execution_order`) VALUES
-                                                                    (1, 1, 1),  -- 구글_트렌드_검색
-                                                                    (1, 2, 2),  -- 네이버_트렌드_검색
-                                                                    (1, 3, 3);  -- 키워드_분석_및_필터링
-
--- 싸다구 크롤링 작업의 태스크들
-INSERT INTO `job_task` (`job_id`, `task_id`, `execution_order`) VALUES
-                                                                    (2, 4, 1),  -- 싸다구_상품_검색
-                                                                    (2, 5, 2),  -- 상품_정보_추출
-                                                                    (2, 6, 3);  -- 가격_비교_분석
-
--- 블로그 글 작성 작업의 태스크들
-INSERT INTO `job_task` (`job_id`, `task_id`, `execution_order`) VALUES
-                                                                    (3, 7, 1),  -- 블로그_템플릿_선택
-                                                                    (3, 8, 2),  -- AI_콘텐츠_생성
-                                                                    (3, 9, 3),  -- 콘텐츠_검수_및_최적화
-                                                                    (3, 10, 4); -- 블로그_플랫폼_발행
-
--- 스케줄 설정 (매일 오전 8시 실행)
-INSERT INTO `schedule` (`workflow_id`, `cron_expression`, `parameters`, `is_active`, `created_by`) VALUES
-    (1, '0 0 8 * * *', JSON_OBJECT(
-            'timezone', 'Asia/Seoul',
-            'retry_count', 3,
-            'timeout_minutes', 60,
-            'notification_email', 'admin@icebang.site'
-                     ), TRUE, 1);
+                                                                    (1, 1, 1), (1, 2, 2), (1, 3, 3), (1, 4, 4), (1, 5, 5),
+                                                                    (2, 6, 1), (2, 7, 2);
 
--- 사용자별 설정 (관리자용)
-INSERT INTO `user_config` (`user_id`, `type`, `name`, `json`, `is_active`) VALUES
-    (1, 'workflow_preference', '트렌드_블로그_설정', JSON_OBJECT(
-            'preferred_keywords', JSON_ARRAY('테크', 'IT', '트렌드', '리뷰'),
-            'blog_style', 'casual',
-            'auto_publish', false,
-            'notification_enabled', true
-                                             ), TRUE);
\ No newline at end of file
+-- 스케줄 설정 (매일 오전 8시)
+INSERT INTO `schedule` (`workflow_id`, `cron_expression`, `is_active`) VALUES
+    (1, '0 0 8 * * ?', TRUE);
\ No newline at end of file
diff --git a/docker/local/promtail-config.yml b/docker/local/promtail-config.yml
index a55c64db..687e1251 100644
--- a/docker/local/promtail-config.yml
+++ b/docker/local/promtail-config.yml
@@ -46,4 +46,39 @@ scrape_configs:
           level:
           thread:
           logger:
-          spanId:
\ No newline at end of file
+          spanId:
+
+  - job_name: pre-processing-logs
+    static_configs:
+      - targets:
+          - localhost
+        labels:
+          job: pre-processing
+          app: pre-processing
+          env: develop
+          __path__: /logs/develop/pre-processing-app.log
+    pipeline_stages:
+      - regex:
+          expression: '^\[(?P<traceId>[^\]]*)\] (?P<timestamp>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d{3}) \| (?P<level>\w+) \| (?P<logger>[^:]+:[^:]+:\d+) \| (?P<message>.*)$'
+      - labels:
+          traceId:
+          level:
+          logger:
+
+  - job_name: pre-processing-errors
+    static_configs:
+      - targets:
+          - localhost
+        labels:
+          job: pre-processing-errors
+          app: pre-processing
+          env: develop
+          log_type: error
+          __path__: /logs/develop/pre-processing-app-error.log
+    pipeline_stages:
+      - regex:
+          expression: '^\[(?P<traceId>[^\]]*)\] (?P<timestamp>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d{3}) \| (?P<level>\w+) \| (?P<logger>[^:]+:[^:]+:\d+) \| (?P<message>.*)$'
+      - labels:
+          traceId:
+          level:
+          logger:
diff --git a/docker/production/docker-compose.yml b/docker/production/docker-compose.yml
index deff1ca4..544b4355 100644
--- a/docker/production/docker-compose.yml
+++ b/docker/production/docker-compose.yml
@@ -49,26 +49,11 @@ services:
     env_file:
       - .env.prod
 
-  pre-processing-service:
-    image: ghcr.io/kernel180-be12/final-4team-icebang/pre-processing-service:latest
-    container_name: pre-processing-service
-    restart: on-failure:3
-    ports:
-      - "8000:8000"
-    networks:
-      - app-network
-    env_file:
-      - .env.prod
-    volumes:
-      - onnx_models:/app/models  # ONNX 모델 저장용 볼륨
-
 volumes:
   caddy_data:
   caddy_config:
   logs_volume:
     driver: local
-  onnx_models:
-    driver: local
 
 networks:
   app-network:
diff --git a/docker/produdction-fastapi/docker-compose.yml b/docker/produdction-fastapi/docker-compose.yml
new file mode 100644
index 00000000..2092e3ca
--- /dev/null
+++ b/docker/produdction-fastapi/docker-compose.yml
@@ -0,0 +1,37 @@
+version: "3.9"
+
+services:
+  pre-processing-service:
+    image: ghcr.io/kernel180-be12/final-4team-icebang/pre-processing-service:latest
+    container_name: pre-processing-service
+    restart: on-failure:3
+    ports:
+      - "80:8000"
+    volumes:
+      - ./models:/app/models
+      - logs_volume:/logs
+    depends_on:
+      - promtail
+    env_file:
+      - .env.prod
+
+  promtail:
+    image: grafana/promtail:2.9.0
+    container_name: promtail
+    restart: unless-stopped
+    volumes:
+      - ./promtail-config.yml:/etc/promtail/config.yml:ro
+      - logs_volume:/logs
+    command:
+      - -config.file=/etc/promtail/config.yml
+      - -config.expand-env=true
+    ulimits:
+      nofile:
+        soft: 65535
+        hard: 65535
+    env_file:
+      - .env.prod
+
+volumes:
+  logs_volume:
+    driver: local
diff --git a/docker/produdction-fastapi/promtail-config.yml b/docker/produdction-fastapi/promtail-config.yml
new file mode 100644
index 00000000..b44fee00
--- /dev/null
+++ b/docker/produdction-fastapi/promtail-config.yml
@@ -0,0 +1,47 @@
+server:
+  http_listen_port: 9080
+  grpc_listen_port: 0
+
+positions:
+  filename: /tmp/positions.yaml
+
+clients:
+  - url: https://${LOKI_USERNAME}:${LOKI_PASSWORD}@${LOKI_HOST}/loki/api/v1/push
+
+scrape_configs:
+  - job_name: pre-processing-logs
+    static_configs:
+      - targets:
+          - localhost
+        labels:
+          job: pre-processing
+          app: pre-processing
+          env: production
+          __path__: /logs/production/app.log
+    pipeline_stages:
+      - regex:
+          expression:
+      - labels:
+          traceId:
+          level:
+          thread:
+          logger:
+
+  - job_name: pre-processing-errors
+    static_configs:
+      - targets:
+          - localhost
+        labels:
+          job: pre-processing-errors
+          app: pre-processing
+          env: production
+          log_type: error
+          __path__: /logs/production/error.log
+    pipeline_stages:
+      - regex:
+          expression:
+      - labels:
+          traceId:
+          level:
+          thread:
+          logger: