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How do I...?
Links to common use cases, workflows and tasks using ZenML.
Last Updated: October 17, 2023
Some common questions that we get asked are:
- contribute to ZenML's open-source codebase?
- custom components: adding them to ZenML?
- dependency clashes mitigation with ZenML?
- deploy cloud infrastructure and/or MLOps stacks?
ZenML is designed to be stack-agnostic, so you can use it with any cloud infrastructure or MLOps stack. Each of the documentation pages for stack components explain how to deploy these components on the most popular cloud providers.
We also build and maintain the
mlstackspackage and library which offers a dedicated way to spin up infrastructure for your ZenML pipelines. It's fully integrated into ZenML's CLI and is a great way to get started with deploying your infrastructure. ZenML also publishes and maintains modules on the Terraform Registry (which are used by
mlstacksunder the hood) which you can also use as a standalone solution if you are familiar with Terraform.
- deploy ZenML on my internal company cluster?
- hyperparameter tuning?
- reset things when something goes wrong?
To reset your ZenML client, you can run
zenml cleanwhich will wipe your local metadata database and reset your client. Note that this is a destructive action, so feel free to reach out to us on Slack before doing this if you are unsure.
- steps that create other steps AKA dynamic pipelines and steps?
Please read our general information on how to compose steps + pipelines together to start with. You might also find the code examples in our guide to implementing hyperparameter tuning which is related to this topic.
- templates: using starter code with ZenML?
Project templates allow you to get going quickly with ZenML. We recommend the Starter template (
starter) for most use cases which gives you a basic scaffold and structure around which you can write your own code. You can also build templates for others inside a Git repository and use them with ZenML's templates functionality.
- upgrade my ZenML client and/or server?
Upgrading your ZenML client package is as simple as running
pip install --upgrade zenmlin your terminal. For upgrading your ZenML server, please refer to the dedicated documentation section which covers most of the ways you might do this as well as common troubleshooting steps.
- use a <YOUR_COMPONENT_GOES_HERE> stack component?