feat: Add mlops serving pattern cookbook

MLOps/serving_patterns/README.md

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+# Serving patterns
+
+.</br>
+├── [chapter 4. 추론 시스템 만들기](./)</br>
+   ├── [web single pattern](./web_single_pattern)</br>
+   ├── [synchronous inference pattern](./synchronous_pattern)</br>
+   ├── [asynchronous inference pattern](./asynchronous_pattern)</br>
+   ├── [batc inference pattern](./batch_pattern)</br>
+   ├── [preprocess and prediction pattern](./prep_pred_pattern)</br>
+   ├── [horizontal microservice pattern](./horizontal_microservice_pattern)</br>
+   ├── [sync and async pattern](./sync_async_pattern)</br>
+   ├── [pattern cache pattern](./prediction_cache_pattern)</br>
+   ├── [data cache pattern](./data_cache_pattern)</br>
+   ├── [prediction template pattern](./template_pattern)</br>
+   └── [Edge AI pattern](./edge_ai_pattern)</br>

MLOps/serving_patterns/asynchronous_pattern/.dockerignore

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+dockerfile
+Dockerfile
+.dockerignore
+log
+tmp
+*.sqlite3
+*.sqlite3-journal
+__pycache__
+.pytest_cache
+*.dvc
+dvc.yaml
+dvc.lock

MLOps/serving_patterns/asynchronous_pattern/Dockerfile.backend

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+FROM python:3.8-slim
+
+ENV MODEL_DIR imagenet_inception_v3
+ENV PROJECT_DIR asynchronous_pattern
+WORKDIR /${PROJECT_DIR}
+ADD ./requirements_backend.txt /${PROJECT_DIR}/
+RUN apt-get -y update && \
+    apt-get -y install apt-utils gcc && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/* && \
+    pip install --no-cache-dir -r requirements_backend.txt
+
+COPY ./src/ /${PROJECT_DIR}/src/
+COPY ./${MODEL_DIR}/data/ /${PROJECT_DIR}/data/
+
+ENV LOG_LEVEL DEBUG
+ENV LOG_FORMAT TEXT
+
+CMD [ "python", "-m", "src.app.backend.prediction_batch" ]

MLOps/serving_patterns/asynchronous_pattern/Dockerfile.proxy

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+FROM python:3.8-slim
+
+ENV MODEL_DIR imagenet_inception_v3
+ENV PROJECT_DIR asynchronous_pattern
+WORKDIR /${PROJECT_DIR}
+ADD ./requirements_proxy.txt /${PROJECT_DIR}/
+RUN apt-get -y update && \
+    apt-get -y install apt-utils gcc && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/* && \
+    pip install --no-cache-dir -r requirements_proxy.txt
+
+COPY ./src/ /${PROJECT_DIR}/src/
+COPY ./${MODEL_DIR}/data/ /${PROJECT_DIR}/data/
+
+ENV LOG_LEVEL DEBUG
+ENV LOG_FORMAT TEXT
+
+COPY ./run.sh /${PROJECT_DIR}/run.sh
+RUN chmod +x /${PROJECT_DIR}/run.sh
+CMD [ "./run.sh" ]

MLOps/serving_patterns/asynchronous_pattern/README.md

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+# 비동기 추론 패턴
+
+## 목적
+
+비동기 추론 API 를 제공합니다.
+
+## 전제
+
+- Python 3.8 이상
+- Docker
+- Docker compose
+
+## 사용법
+
+0. 현재 디렉토리
+
+```sh
+$ pwd
+~/ml-system-in-actions/chapter4_serving_patterns/asynchronous_pattern
+```
+
+1. 비동기 추론을 위한 Docker 이미지 빌드
+
+```sh
+$ make build_all
+# 실행 커맨드
+# docker build \
+#     -t shibui/ml-system-in-actions:asynchronous_pattern_asynchronous_proxy_0.0.1 \
+#     -f ./Dockerfile.proxy .
+# docker build \
+#     -t shibui/ml-system-in-actions:asynchronous_pattern_imagenet_inception_v3_0.0.1 \
+#     -f ./imagenet_inception_v3/Dockerfile .
+# docker build \
+#     -t shibui/ml-system-in-actions:asynchronous_pattern_asynchronous_backend_0.0.1 \
+#     -f ./Dockerfile.backend .
+```
+
+2. Docker compose 로 각 서비스 기동
+
+```sh
+$ make c_up
+# 실행 커맨드
+# docker-compose \
+#     -f ./docker-compose.yml \
+#     up -d
+```
+
+3. 기동한 API 에 요청
+
+```sh
+# 헬스 체크
+$ curl localhost:8000/health
+# 출력
+# {"health":"ok"}
+
+# 메타 데이터
+$ curl localhost:8000/metadata
+# 출력
+# {
+#   "model_spec": {
+#     "name": "inception_v3",
+#     "signature_name": "",
+#     "version": "0"
+#   },
+#   "metadata": {
+#     "signature_def": {
+#       "signature_def": {
+#         "serving_default": {
+#           "inputs": {
+#             "image": {
+#               "dtype": "DT_STRING",
+#               "tensor_shape": {
+#                 "dim": [
+#                   {
+#                     "size": "-1",
+#                     "name": ""
+#                   }
+#                 ],
+#                 "unknown_rank": false
+#               },
+#               "name": "serving_default_image:0"
+#             }
+#           },
+#           "outputs": {
+#             "output_0": {
+#               "dtype": "DT_STRING",
+#               "tensor_shape": {
+#                 "dim": [],
+#                 "unknown_rank": true
+#               },
+#               "name": "StatefulPartitionedCall:0"
+#             }
+#           },
+#           "method_name": "tensorflow/serving/predict"
+#         },
+#         "__saved_model_init_op": {
+#           "inputs": {},
+#           "outputs": {
+#             "__saved_model_init_op": {
+#               "dtype": "DT_INVALID",
+#               "tensor_shape": {
+#                 "dim": [],
+#                 "unknown_rank": true
+#               },
+#               "name": "NoOp"
+#             }
+#           },
+#           "method_name": ""
+#         }
+#       }
+#     }
+#   }
+# }
+
+# 라벨 목록
+$ curl localhost:8000/label
+# 출력
+# [
+#   "background",
+#   "tench",
+#   "goldfish",
+# ...
+#   "bolete",
+#   "ear",
+#   "toilet tissue"
+# ]
+
+# 테스트 데이터로 추론 요청
+$ curl localhost:8000/predict/test
+# 출력
+# {
+#   "job_id": "f22689"
+# }
+
+
+# 이미지를 요청
+$ (echo \
+    -n '{"image_data": "'; \
+    base64 imagenet_inception_v3/data/cat.jpg; \
+    echo '"}') | \
+   curl \
+    -X POST \
+    -H "Content-Type: application/json" \
+    -d @- \
+    localhost:8000/predict
+# 출력
+# {
+#   "job_id":"2f49aa"
+# }
+
+# 이미지 요청의 작업 ID 로부터 추론 결과를 요청
+$ curl localhost:8000/job/2f49aa
+# 출력
+# {
+#   "2f49aa": {
+#     "prediction": "Siamese cat"
+#   }
+# }
+```
+
+4. Docker compose 정지
+
+```sh
+$ make c_down
+# 실행 커맨드
+# docker-compose \
+#     -f ./docker-compose.yml \
+#     down
+```

MLOps/serving_patterns/asynchronous_pattern/docker-compose.yml

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+version: "3"
+
+services:
+  asynchronous_proxy:
+    container_name: asynchronous_proxy
+    image: shibui/ml-system-in-actions:asynchronous_pattern_asynchronous_proxy_0.0.1
+    restart: always
+    environment:
+      - PLATFORM=docker_compose
+      - QUEUE_NAME=tfs_queue
+      - API_ADDRESS=imagenet_inception_v3
+    ports:
+      - "8000:8000"
+    command: ./run.sh
+    depends_on:
+      - redis
+      - imagenet_inception_v3
+      - asynchronous_backend
+
+  imagenet_inception_v3:
+    container_name: imagenet_inception_v3
+    image: shibui/ml-system-in-actions:asynchronous_pattern_imagenet_inception_v3_0.0.1
+    restart: always
+    environment:
+      - PORT=8500
+      - REST_API_PORT=8501
+    ports:
+      - "8500:8500"
+      - "8501:8501"
+    entrypoint: ["/usr/bin/tf_serving_entrypoint.sh"]
+
+  asynchronous_backend:
+    container_name: asynchronous_backend
+    image: shibui/ml-system-in-actions:asynchronous_pattern_asynchronous_backend_0.0.1
+    restart: always
+    environment:
+      - PLATFORM=docker_compose
+      - QUEUE_NAME=tfs_queue
+      - API_ADDRESS=imagenet_inception_v3
+    entrypoint: ["python", "-m", "src.app.backend.prediction_batch"]
+    depends_on:
+      - redis
+
+  redis:
+    container_name: asynchronous_redis
+    image: "redis:latest"
+    ports:
+      - "6379:6379"

MLOps/serving_patterns/asynchronous_pattern/imagenet_inception_v3/Dockerfile

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+FROM tensorflow/tensorflow:2.5.1 as builder
+
+ARG SERVER_DIR=imagenet_inception_v3
+ENV PROJECT_DIR asynchronous_pattern
+WORKDIR /${PROJECT_DIR}
+ADD ./${SERVER_DIR}/requirements.txt /${PROJECT_DIR}/
+
+COPY ./${SERVER_DIR}/extract_inception_v3.py /${PROJECT_DIR}/extract_inception_v3.py
+COPY ./${SERVER_DIR}/data/image_net_labels.json /${PROJECT_DIR}/data/image_net_labels.json
+
+RUN apt-get -y update && \
+    apt-get -y install apt-utils gcc && \
+    pip install  --no-cache-dir -r requirements.txt && \
+    touch __init__.py && \
+    python -m extract_inception_v3
+
+
+FROM tensorflow/serving:2.5.2
+
+ARG SERVER_DIR=imagenet_inception_v3
+ENV PROJECT_DIR asynchronous_pattern
+ENV MODEL_BASE_PATH /${PROJECT_DIR}/saved_model/inception_v3
+ENV MODEL_NAME inception_v3
+
+COPY --from=builder /${PROJECT_DIR}/saved_model/inception_v3 ${MODEL_BASE_PATH}
+EXPOSE 8500
+EXPOSE 8501
+
+COPY ./${SERVER_DIR}/tf_serving_entrypoint.sh /usr/bin/tf_serving_entrypoint.sh
+RUN chmod +x /usr/bin/tf_serving_entrypoint.sh
+ENTRYPOINT ["/usr/bin/tf_serving_entrypoint.sh"]