# Server as job coordinator?

**URL:** <https://discuss.flower.ai/t/server-as-job-coordinator/106>\
**Category:** Flower Framework\
**Created:** [February 28, 2024, 1:29pm UTC](https://discuss.flower.ai/t/server-as-job-coordinator/106 "2024-02-28T13:29:04Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![flower](https://dub1.discourse-cdn.com/flex013/user_avatar/discuss.flower.ai/flower/32/17_2.png) [@flower](https://discuss.flower.ai/u/flower)\
**Post date:** [February 28, 2024, 1:29pm UTC](https://discuss.flower.ai/t/server-as-job-coordinator/106/1 "2024-02-28T13:29:04Z")

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\*This question was migrated from Github Discussions.

**Original Question:**  
It appears that the current design assumes that a single strategy is passed to the Server at initialization. Is is possible to, instead, use the server as a job coordinator such that multiple FL jobs are submitted and managed by a single central server?

In a many to many topology where many data scientists want to submit multiple FL jobs to a distributed pool of workers it would be a requirement that each worker in the pool only need to know about a single central server and each data scientist could be furnished with a client that can be configured with a single central server as well.

Is this either possible today or planned on the Flower roadmap?

**Answer:**  
Hi, thanks for the question! Job coordination / multitenancy is currently is not yet supported in a user-friendly way. It’s one of the top features on our roadmap and we’re already exploring different design approaches for it, our goal is (as always) to provide a very user-friendly implementation.

That being said, there are a couple of workarounds that people have successfully used:

1. Use a custom strategy that orchestrates the different jobs (fairly easy to implement)
2. Use MLCube in combination with a custom strategy
3. Start multiple Flower server and orchestrate them through an external script