Migrate from Open Source Ray
Check your docs version
This version of the Anyscale docs is deprecated. Go to the latest version for up to date information.
Time to move your Ray project to Anyscale? Don't worry. Follow the 2 steps below and make the easy switch.
1. No code change is needed
You do not need to change your Ray application code.
2. Use Anyscale tools to accelerate the development and productionization of Ray workloads
Development tools
Based on your development stage, use the right Anyscale to maximize your productivity.
| Development stage | Open Source Ray | Anyscale Managed Ray |
|---|---|---|
| Iterative development | Laptop, VM, etc. | Laptop or Anyscale Workspace |
| Large scale testing | Jobs API, Ray Client, SSH, etc. | Anyscale Workspace |
| Production environment | Ray jobs or Ray Serve deployments | Anyscale jobs or Anyscale services |
| Debug production issues | Observability stack, SSH, etc. | Anyscale Workspace |
Dependency management and compute configuration.
- In Anyscale, the monolithic cluster config has been split to two configurations, a Cluster Environment and a cluster Compute Config.
- Anyscale will manage the cluster's lifecycle for you. It will launch clusters when needed and shut them down if they have not been used for a while. You can also manually modify the cluster using the web UI, Python SDK or HTTP API.
Migration steps
- Convert application dependencies:
- If you require Debian packages, create a Cluster Environment.
- If you require pip or Conda dependencies, you can create a Cluster Environment to install them, or you can set up a runtime environment.
- Convert Compute Configs: If you need to customize your compute resources, you can create a Compute Config.