# Running ray tune on an already existing cluster

**URL:** <https://discuss.ray.io/t/running-ray-tune-on-an-already-existing-cluster/5103>\
**Category:** Ray Tune\
**Created:** [February 17, 2022, 9:53am UTC](https://discuss.ray.io/t/running-ray-tune-on-an-already-existing-cluster/5103 "2022-02-17T09:53:26Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![pamparana](https://avatars.discourse-cdn.com/v4/letter/p/df788c/32.png) [@pamparana](https://discuss.ray.io/u/pamparana)\
**Post date:** [February 17, 2022, 9:53am UTC](https://discuss.ray.io/t/running-ray-tune-on-an-already-existing-cluster/5103/1 "2022-02-17T09:53:26Z")

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We have a ray cluster running but the required packages for a particular ML project may not be installed there already.

Now, I want to run a hyper parameter tuning experiment using this Ray cluster. However, before I make a call to `tune.run`, I would need to prepare the cluster so that all the prerequisites and the dependencies are installed.

I was wondering what would be a good way to achieve that? We use `poetry` for package management but `pip` is also an option. I am having trouble figuring out how to get my dependencies on all the `ray` nodes so that the tuning experiments can run fine.

**EDIT** So runtime environment can be specified directly in the ray init command. I think this will suffice for now.

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**Author:** ![amogkam](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/amogkam/32/17_2.png) [@amogkam](https://discuss.ray.io/u/amogkam)\
**Post date:** [February 19, 2022, 2:39am UTC](https://discuss.ray.io/t/running-ray-tune-on-an-already-existing-cluster/5103/2 "2022-02-19T02:39:57Z")

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Yes runtime environments would be your best bet here!