Commands below will help you set up and work with Ververica Platform.
scli platform api-token create \
--vvp-url "https://vvp.example.com" \
--vvp-namespace "default" \
--name "cicd" \
--role "editor" \
--save-to-kubernetes-secret "vvp/secret" Sample response:
{
"namespace": "default",
"name": "cicd",
"role": "editor",
"secret": "x§11d091jd1jd9jasd0j"
}scli platform api-token remove \
--vvp-url "https://vvp.example.com" \
--vvp-namespace "default" \
--name "cicd"You can set up your own profile, which will help you to connect to Ververica. Instead of providing common parameters to
each command, you can just pass the profile name with --profile
or export environmental variable as SCLI_PROFILE.
The command below will walk you through an interactive way of setting up a profile:
scli profile add sandboxYou can also set up a profile in a non-interactive way by providing all required parameters as arguments:
scli profile add sandbox \
--vvp-url "https://vvp.streaming-platform.getindata.dev" \
--vvp-namespace "default" \
--vvp-deployment-target "vvp-team1" \
--vvp-api-token "x§11d091jd1jd9jasd0j" \
--docker-registry-url "registry.gitlab.com/flink-jobs"scli platform deployment-target create \
--vvp-url "https://vvp.example.com" \
--vvp-namespace "default" \
--vvp-api-token "x§11d091jd1jd9jasd0j" \
--name "vvp-team1" \
--kubernetes-namespace "vvp" \
--profile "sandbox"Parameters
--vvp-url,--vvp-namespace,--vvp-api-token,--vvp-deployment-targetare optional if they can be read from profile.
Sample response:
{
"name": "vvp-team1"
}scli project deploy \
--vvp-url "https://vvp.example.com" \
--vvp-namespace "default" \
--vvp-api-token "x§11d091jd1jd9jasd0j" \
--vvp-deployment-target "vvp-team1" \
--docker_image_registry "${CI_REGISTRY_IMAGE}" \
--docker-image-tag "${CI_COMMIT_TAG}" \
--docker-image-repository tmp_project \
--profile "sandbox"Parameters
--vvp-url,--vvp-namespace,--vvp-api-token,--vvp-deployment-targetare optional if they can be read from profile.
scli project build \
--docker-image-tag "latest"scli docker login \
--username "user" \
--password "password" \
--docker-registry-url registry.gitlab.com/getindata/Parameters
--docker-image-tagis optional and has default valuelatest.
pipenv
make setup- Install dependencies required to build a wheel packagemake package- Create a wheel package
make install- Install a wheel packagemake install/force- Reinstall a wheel package
In order to actually use these magics, you must install our PIP package:
python3 -m pip install streamingcli --extra-index-url https://__token__:<your_personal_token>@gitlab.com/api/v4/projects/29597698/packages/pypi/simpleIn local development, when streaming-cli repository is checkouted on local machine, you may install the most current version:
python3 -m pip install -e file:///{{path_to_your_repository}}/streaming-cliThe last thing to do is to register in Jupyter with a running IPython in the first cell:
%load_ext streamingcli.jupyter.integrations