ray
Model Serving & MLOpsA unified framework for scaling AI and Python applications from a laptop to a cluster
Features
- Unified runtime for distributed execution of Python code
- AI‑focused libraries: Data, Train, Tune, RLlib, Serve
- Core abstractions – Tasks (stateless functions), Actors (stateful workers), Objects (immutable values)
- Built‑in monitoring via Ray Dashboard and a Distributed Debugger
Security Response History
1 CVE| CVE | Severity | Disclosed | Patched (this tool) | vs Ecosystem Median |
|---|---|---|---|---|
| CVE-2023-4863 KEV |
high
CVSS 8.8
|
2023-09-13 | 2026-02-18 | 2y 5mo / median 2y 4mo |
Recent releases
View all 6 releases →
No immediate action
ray-2.56.0
Security relevant
Routine maintenance and dependency updates.
patches CVE-2023-4863
Open
ray-2.55.1
Bug fix
Minor fixes and improvements.
Full changelog
- Fixes SSH connectivity issue in the
ray-llmimage (#62625 / #62718). - Upgrade apt packages in slim base (#62666 / #62717).
ray-2.55.0
Breaking risk
Breaking changes
- local_mode support removed
- Legacy BlockList, locality_with_output, and callback API removed
- PyArrow 9.0 compatibility checks removed
Security fixes
- jackson-databind upgraded from 2.16.1 to 2.18.6 (GHSA-72hv-8253-57qq)
Notable features
- DataSourceV2 API with scanner/reader framework and file partitioning
- Kafka datasink with confluent-kafka migration and datetime offset support
- 2-phase commit checkpointing with trie recovery
ray-2.54.1
Bug fix
Hanging issue detector disabled to resolve pipeline performance degradation from blocking API calls.
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Install & Platforms
Install via
pip
