MLEM now offers deployment to Kubernetes and Sagemaker with a single command.
Building a docker image from the model or preparing a folder ready for running
docker build in it.
$ pip install mlem[docker]
# or
$ pip install dockerIf you want to build images locally, you may want to install Docker Desktop.
docker build
In the parent page we've seen how to build a Docker Image for a model using a pre-configured builder. Now let's see how this docker image is built.
To run docker build you need to prepare a folder with a Dockerfile and all
necessary content (like a model itself). This is what MLEM does under the hood
as a first step inside of mlem build docker. For your convenience, this
functionality is exposed as a separate builder:
$ mlem build docker_dir --model models/rf \
--server fastapi --target build
⏳️ Loading model from models/rf.mlem
🛠 Building MLEM wheel file...
💼 Adding model files...
🛠 Generating dockerfile...
💼 Adding sources...
💼 Generating requirements file...Now everything is ready and written to build/.
$ tree build/
build/
├── Dockerfile # instructions for `docker build`
├── mlem-0.2.9-py3-none-any.whl # requirements to use the model
├── mlem_requirements.txt # requirements to install MLEM
├── model # model binary
├── model.mlem # MLEM model metafile
├── requirements.txt # requirements to run the model
├── run.sh # script that runs `mlem serve`
└── server.yaml # MLEM server configurationAs you can see, the builder generated everything needed to build a Docker image: Dockerfile, model, requirements, and so on. Now we can execute MLEM build to build an actual Docker image:
$ docker build . -t mlem-model:latest
[+] Building 70.7s (14/14) FINISHED
=> [internal] load build definition from Dockerfile 0.1s
=> => transferring dockerfile: 533B 0.0s
=> [internal] load .dockerignore 0.1s
=> => transferring context: 2B 0.0s
=> [internal] load metadata for docker.io/library/python:3.9.5-slim 0.0s
=> [1/9] FROM docker.io/library/python:3.9.5-slim 0.1s
=> [internal] load build context 0.1s
=> => transferring context: 487.14kB 0.1s
=> [2/9] WORKDIR /app 0.1s
=> [3/9] COPY requirements.txt . 0.0s
=> [4/9] RUN pip install -r requirements.txt 44.1s
=> [5/9] COPY mlem_requirements.txt . 0.0s
=> [6/9] RUN pip install -r mlem_requirements.txt 21.4s
=> [7/9] COPY mlem-0.2.9.dev14+gf47bf34-py3-none-any.whl . 0.0s
=> [8/9] RUN pip install mlem-0.2.9.dev14+gf47bf34-py3-none-any.whl 1.8s
=> [9/9] COPY . ./ 0.0s
=> exporting to image 2.8s
=> => exporting layers 2.8s
=> => writing image sha256:f449c1a69bc4566f61624d75481bf06c52164f05 0.0s
=> => naming to docker.io/library/mlem-model:latest 0.0s$ docker run -p 8080:8080 mlem-model:latest
...Since we're serving the model with FastAPI, now you can open http://localhost:8080/docs in your browser and see the OpenAPI spec.