Oliver Tedder
12/09/2024, 10:21 AMjob_variables
argument, e.g.
flow.from_source(
source=gitlab_repo,
entrypoint="myrepo/run.py:run",
).deploy(
name="mydeploymentname",
work_pool_name="mpool",
job_variables={"env": {"MYSECRET", "secretpassword123"}},
)
Marvin
12/09/2024, 10:22 AMjob_variables
argument is generally not considered a good practice. This method can expose sensitive information to environments where these variables can be accessed, potentially leading to security vulnerabilities.
In Prefect's documentation, they discuss job variables as a way to configure infrastructure-related values for deployments, which can include environment variables (source: Prefect 2.0 Docs, Prefect 3.0 Docs). However, it's crucial to handle sensitive information like secrets through more secure methods:
1. Use Secret Storage Solutions: Opt for secret management tools or services that securely store and manage access to these secrets.
2. Environment Variables via Secure Methods: Consider injecting environment variables at the runtime level, securely fetching them from a secret management service.
3. Access Control: Employ strong access controls to limit who can view and edit deployments and related configurations.
Mishandling secrets is like putting all your passwords on a sticky note on your monitor—it might seem handy, but it's a risky business!Oliver Tedder
12/09/2024, 10:41 AMMarvin
12/09/2024, 10:42 AMOliver Tedder
12/09/2024, 11:41 AMMarvin
12/09/2024, 11:42 AMprefect.yaml
file or the .deploy()
method to adjust job variables according to the environment. More details are found in Prefect's infrastructure concepts.
3. Deployment Configuration: Set up your deployment configurations to differentiate between development and production environments, possibly using a branching strategy or different deployment directories/files. Adjust the job_variables
or environment variables
sections appropriately to point to the correct set of secrets.
Remember, secrets are like my will to get out of bed—easily misplaced if not properly secured!Bring your towel and join one of the fastest growing data communities. Welcome to our second-generation open source orchestration platform, a completely rethought approach to dataflow automation.
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