FaaS Docker Image

Dataloop enables you to deploy in the FaaS module a custom docker image, to enrich your application with literally
anything required for your project. Deploying a docker image is as easy as providing the Docker image path when
deploying the service:

Copy

Copied

service = package.deploy(service_name='my-service',
                         runtime=dl.KubernetesRuntime(
                             runner_image='docker.io/python:3.8'
                         ))

or if you want to update an existing service:

Copy

Copied

service = dl.services.get('service-id-or-name')
service.runtime.runner_image = 'python:3.8'
service.update()

Our Docker Image

We have our list of docker images publicly available in Dockerhub
You can see the env of each docker on the dockerfile here

Public Docker Images

You can use any public docker image, and on runtime, the Dataloop agent will install:

Package requirements
dtlpy package (version as defined on the service)
dtlpy-agent (same version as the SDK)

For example, using docker.io/python:3.9.13 will run the function with Python 3.9.

Build Your Own Docker Image

If you want other environment or need to add some apt-get installation, you can create any docker image and use it directly.
You will need to set the HOME directory to /tmp and install the python packages with --user (or as USER 1000).
For instance:

Copy

Copied

FROM dockerhub.io/dataloopai/dtlpy-agent:latest.gpu.cuda11.5.py3.8.opencv  
  
RUN apt update && apt install -y zip ffmpeg  
  
USER 1000  
ENV HOME=/tmp  
RUN pip3 install --user \  
    dtlpy==1.54.10 \  
    dtlpy-agent==1.54.10 \  
    torch \  
    torchvision \  
    imgaug \  
    scikit-image==0.17.2

Using Private Docker Registry

To connect a private registry, you'll need to add the docker container registry credentials as an Organization Secret and just create use the runner image.

Docker Hub

You'll need to create the organization secret with the following credentials and encode everything as follows:

Copy

Copied

import base64
import json
# Credentials
username = '<dokcer hub user name>'
password = '<docker hub password>'
mail = '<email>'
# Create auth token
auth_decoded = username + ":" + password
auth_decoded_bytes = auth_decoded.encode('ascii')
base64_auth_message_bytes = base64.b64encode(auth_decoded_bytes)
base64_auth_message = base64_auth_message_bytes.decode('ascii')
cred_payload = {
    "auths": {
        "docker.io": {
            "username": username,
            "password": password,
            "email": mail,
            "auth": base64_auth_message
        }
    }
}
encoded_cred = base64.b64encode(json.dumps(cred_payload).encode()).decode()
print(encoded_cred)

Now create the integration secret for the organization

Copy

Copied

org = dl.organizations.get(organization_name='<my organization name>')
secret = org.integrations.create(integrations_type='private-registry',
                                 name='<my dockerhub secret>',
                                 options={"name": "_json_key",
                                          "spec": {"password": encoded_cred}})

That's it, now you can just add the container url to the dl.Service (runner_image in the runtime class) and run the service.