Ray Releases

GET https://watchchangelog.com/api/v1/entries?source=ray.releases

{
  "source": "ray.releases",
  "vendor": "Anyscale",
  "id": "tag:github.com,2008:Repository/71932349/ray-2.58.0",
  "published_at": "2026-08-23T05:42:08.000Z",
  "title": "Ray-2.58.0",
  "url": "https://github.com/ray-project/ray/releases/tag/ray-2.58.0",
  "summary": "Highlights Ray Serve LLM: In this release we've completed KV cache and token aware request routing, which was previewed in 2.57. Tokenization now happens in-process on the LLMRouter ingress replica, the routing decision is made there, tokens are transmitted out-of-band so the engine does not re-tokenize, KV lifecycle events are broadcast to every ingress replica ( #64642 , #64920 , #64949 , #65010 , #65095 ). KV cache and token aware routing is also aware of CPU KV caches, so offloaded KV cache blocks count toward a replica's cache hit ( #65063 ). Ray Core: We enabled the capability to offload task events from. With RAY_enable_task_events_to_dashboard_head on, the task event buffer is replaced by the ray event recorder, events are exported from the aggregator agent to a task events head that keeps an in-memory store, and the state APIs and ray.timeline read from it ( #64835 , #65028 , #65123 , #65160 , #65218 ). Enabling the feature removes task event ingestion and serving from the GCS hot path. Ray Data: We’ve added Databricks integrations for writing to DeltaLake, with Catalog support. We’ve also shipped a new shuffle v2 backend, featuring improved performance for joins and aggregations. Sandboxing: We've also added experimental Ray Sandbox, which runs task and actor code under gVisor and can run Docker-built images directly ( #64964 , #65570 ). TPU Support: Ray Train adds support for TorchTPU backend ( #64796 ), and Ray Core adds SubslicePlacementGroup for gang scheduling on TPU subslices, single-host TPU support in SlicePlacementGroup , and resource accounting for tpu7x and multi-core chips ( #64578 , #64079 , #64058 ). This lets TPU slices and subslices be reserved and trained on without external gang-scheduling glue. Ray Data 🎉 New Features Add Dataset.with_columns for multi-column expression projection ( #63858 ) Add write_delta for Delta Lake, with catalog support ( #64923 , #65079 ) Add Torch inference API ( #65157 ) Promote hash shuffle v2 to a selectable shuffle strategy, with aggregation support, vectorized aggregation, and block splitting during aggregation ( #64953 , #64652 , #64956 , #65329 , #64897 ) Add ignore_missing_paths and skip_paths to read_parquet on DatasourceV2 ( #65118 ) Add delta_timestamps (temporal windows) to read_lerobot ( #64877 ) Collect cluster usage metrics by sampling in background threads during execution ( #64686 ) Tolerate actor deaths during init via DataContext.max_consecutive_actor_init_deaths ( #64846 ) Expose RAY_DATA_HASH_SHUFFLE_MAP_TASK_TARGET_INPUT_BYTES in DataContext ( #65103 ) 💫 Enhancements Generate sortable, collision-resistant dataset IDs ( #65075 ) Push Limit into ReadFiles when it sits directly on it, and extract FileIndexer.list_file_infos ( #65167 , #65168 ) Use BlockRefCounter for object store memory estimation and remove BlockRefCounter.clear() ( #64456 , #64521 ) Fail execution if no operator makes progress within a timeout, instead of hanging ( #65349 ) Improve BatchIterator and iter_torch_batches , and allow a custom collate_fn with a custom device ( #64994 , #64967 ) Skip downstream-capacity backpressure for eligible materializers ( #64844 ) Shard exact download partitioning ( #64066 ) Bump the sort_reduce memory multiplier to 3x and stop using estimated_input_blocks as the shuffle partition count ( #65176 , #65296 , #65335 ) Disable cluster autoscaling when PlacementGroupSchedulingStrategy is in use ( #64417 ) Propagate the operator name to shuffle tasks ( #64802 ) Rename reports_custom_op_stats to should_report_custom_op_stats across all MapTransformFn variants ( #64461 , #64515 ) Rename allocated to reserved and add type aliases in the autoscaling coordinator ( #64997 , #65096 ) Deprecate ray_remote_args_fn and Dataset.zip ( #64963 , #65111 ) 🔨 Fixes Fix an RCE where read_lance or nested pickle objects could execute arbitrary code ( #64881 ) Stop converting Arrow null columns to null[pyarrow] in to_pandas ( #65187 ) Fix iter_torch_batches device resolution and typing ( #65059 , #64947 ) Propagate isolate_read_workers to DatasourceV2 ( #65191 ) Avoid signalling epoch end for failed attempts ( #65082 ) Add tf-keras to the text_embedding pip packages ( #64889 ) 📖 Documentation Fix the stale use_datasource_v2 docstring default and an incorrect default_map_logical_memory_enabled reference ( #65155 , #65091 ) Ray Serve 🎉 New Features Configurable status code and Retry-After header for backpressure rejections ( #65193 , #65319 ) Add dependency-ordered shutdown for deployments ( #64922 ) Add an optional tie-break key to best-fit node scheduling ( #64914 ) Scale ingress request router replicas per proxy node ( #64724 ) 💫 Enhancements Reconcile health checks from a dirty set, sweeping RUNNING replicas round-robin instead of every tick ( #64690 ) Gate the rank-consistency check on replica membership changes ( #64911 ) Read the multiplex marker statically so probing cannot initialize handles ( #65064 ) Type CreatePlacementGroupRequest.runtime_env as a dict ( #64892 ) Add a deployment-state accessor for testing ( #64790 ) 🔨 Fixes Fix the Serve replica ASGIService bypassing token authentication ( #65189 ) Fix the proxy update loop getting stuck when a proxy's node is removed ( #64403 ) Ray Train 🎉 New Features Ray Train Integrates with TorchTPU backend ( #64796 ) Add a public preemption API and a controller PreemptingState ( #64360 ) Add data ingest metrics to the Train dashboard ( #64523 ) 💫 Enhancements Make Train V1 and V2 use the autoscaling coordinator ( #64824 ) Expand the contains_tensor check and add a serialization check for the results return value ( #64930 ) Pin PlacementGroupCleaner to the head node ( #64705 ) 🔨 Fixes Fix Torch environment setup for V1 worker groups ( #65005 ) Ray Tune 🔨 Fixes Fix HyperOptSearch dropping tune.choice categories that are constant dicts ( #64537 ) Deflake test_multi_trial_reuse_with_failing and decide test_experiment_restore completion from measured progress ( #64526 , #65212 ) Ray LLM 🎉 New Features KV-cache-aware routing: move tokenization into the LLMRouter ingress replica, decide KV/token routing there, broadcast KV lifecycle events to all ingress replicas, and make selection and reservation atomic ( #64642 , #64920 , #64949 , #65010 ) Enable KV cache offloading, make KV routing aware of CPU KV caches, and transmit tokens out-of-band so the engine skips tokenization ( #65063 , #65095 ) Add a KV cache offload/reload dashboard and a Ray Serve LLM SGLang metrics dashboard ( #65122 , #64797 ) 💫 Enhancements Upgrade to vLLM 0.26.0 ( #65045 ) Route direct-streaming ingress to the co-located router ( #64489 ) Reuse vLLM's resolved HF config in apply_checkpoint_info ( #62962 ) Preserve mapping-valued vLLM frontend arguments ( #65146 ) 📖 Documentation Document loading models from Azure storage, including az:// Blob streaming with RunAI Streamer ( #64819 , #64825 ) Ray RLlib 🔨 Fixes Fix TQC critic divergence by stopping actor-loss gradients from leaking into the critics ( #65125 ) Fix squashed-Gaussian log-prob corruption for saturated policies ( #65036 ) Use the target_qf_twin head in IQL target prediction ( #64932 ) Properly enforce use_kl_loss in the PPO Torch and TF policies ( #61562 ) Fix a KeyError in the multi-agent module-to-env connector ( #64803 ) Fix the API-doc consistency check for the new reverse/dedup policies, and deflake the test_env_runner callback-count tests ( #64807 , #64989 ) Ray Core 🎉 New Features Ray Sandbox (experimental): run task and actor code under gVisor, and run Docker-built images out of the box ( #64964 , #65397 , #65570 , #65622 ) Move task events out of the GCS: the ray event recorder replaces the task event buffer, the aggregator agent exports to a task events head with an in-memory store, and the state APIs and ray.timeline are rerouted to it, with reconciliation on worker death and job completion ( #64835 , #65028 , #65057 , #65123 , #65141 , #65160 , #65218 , #65247 , #65288 ) Add SubslicePlacementGroup for gang scheduling on TPU subslices, support single-host TPUs in SlicePlacementGroup , and add a per_slice_pgs parameter ( #64578 , #64079 , #64072 ) Introduce a native, lightweight C++ leader election client for active-passive GCS ( #63773 ) Add Apple silicon GPU ( mps ) support and an Intel GPU ZE_AFFINITY_MASK mapping ( #38464 , #64440 ) Add worker lifecycle events to the events export pipeline ( #64887 ) Add GPU UUID to the labels of GPU metrics ( #65113 ) Enable resource accounting for tpu7x and multi-core chips, add gb200 / gb300 accelerator constants, and add TTNPU custom accelerator resources ( #64058 , #65009 , #61554 ) Support cross-device transfers in RDT NIXL ( #64815 ) 💫 Enhancements Publish node death before persisting it and drop RocksDB soft durability (REP-64) ( #64702 ) Make RedisContext::Connect non-fatal on connection failure ( #64299 ) Move the pending resource load pull off the GCS main io_context ( #65024 ) Subscribe only to the specific owner worker's death for generator backpressure, and only when actor-level backpressure is enabled ( #65195 , #65136 ) Evict dead actors from ActorPool instead of recycling them ( #64646 ) Rename label_domain to topology strategy in the scheduling policy ( #64384 ) Warn on use of the deprecated dynamic generator ( #64749 ) Add object resolution debug logging for lineage reconstruction ( #64853 ) Block only on the CUDA stream used to create tensors in RDT ( #64823 ) Preserve StateSchema column order in filter_fields ( #65052 ) Prepare StreamResponse on an empty log stream ( #62296 ) Refine ObjectRefStreamEndOfStreamError from _get_next_ref_n ( #64602 ) Drop a redundant FunctionDescriptor rebuild in CallSiteString ( #64874 ) Upgrade bundled dependencies: log4j 2.25.4, jackson-databind 2.18.8 ( CVE-2026-54512 , CVE-2026-54513 ), gson 2.11.0, aiohttp, idna, and azure ( #64269 , #64575 , #64273 , #65131 , #64056 , #65046 ) 🔨 Fixes Give canceled_tasks_ its own mutex to break a lock-order cycle ( #65393 , #65620 ) Fix a GIL/mutex deadlock in actor-level backpressure with sync and async streaming generators ( #64896 ) Fix a deadlock between metric registration and collect() in OpenTelemetryMetricRecorder ( #64946 ) Report shutdown from check_signals instead of exiting the process ( #65184 , #65400 ) Fix a Python 3.14 async-actor memory leak by re-anchoring stack protection to fiber stacks ( #64772 ) Keep only the latest object-location pubsub snapshot to fix an owner memory leak ( #65133 ) Fix a spurious OwnerDiedError during graceful raylet shutdown ( #64899 ) Fail ray.get on refs from a non-restartable streaming generator when those objects are lost ( #64756 ) Serve the spilled copy when Push hits a stale local_objects_ mirror ( #64916 ) Fix spill_manager_objects_bytes reporting the restored object count instead of restored bytes ( #65013 ) Forward node-pinned actors to the pinned node in GCS actor scheduling ( #64951 ) Fix a leaked named actor and name conflict when registration times out ( #64948 ) Fix a set-before-register race in RDTManager that could SIGSEGV ( #64558 ) Fix task log info fields in lifecycle events ( #65190 ) Guard Status::operator<< against an OK status, and fix UB in StatusOr swap and assignment on error-state operands ( #64983 , #64799 ) Compare all ResourceRequest fields in operator== ( #64838 ) Verify VFIO groups are backed by Google TPU PCI devices, and use POSIX paths for VFIO sysfs vendor checks on Windows ( #65105 , #65182 ) 📖 Documentation Document the embedded RocksDB GCS backend ( #64731 ) Clarify actor class state isolation and the Ray Core walkthrough benchmark setup ( #64597 , #64529 ) Document how to set up placement group topology strategy on Kubernetes ( #64117 ) Dashboard 🎉 New Features Capture Kubernetes Pod events in the Ray Dashboard head ( #63937 ) 💫 Enhancements Hide the GPU and GRAM columns when no GPUs are present ( #64567 ) Update axios to ^1.18.0 ( #65130 ) 🔨 Fixes Fix the profiling status check so it works behind a reverse proxy ( #65126 ) Fix a dashboard startup crash from an unguarded kubernetes import ( #64962 ) 📖 Documentation Add a user guide for Kubernetes events in the Ray Dashboard ( #64734 ) Ray Wheels and Images 🎉 New Features Enable Windows py3.13 and py3.14 wheel builds ( #64970 ) Publish arm64 Ray LLM images ( #65002 ) Add a ray-torch release test image (py3.14, cu12.8) and a hello_world_py314 smoke release test ( #65114 , #64857 ) 💫 Enhancements Bump the Anyscale CLI to 0.26.105 and bake pybase64 into the ML release-test image ( #64980 , #64791 ) Recompile dependency lock files on dependabot PRs, and regenerate the ray-torch py3.14 lock for aiohttp 3.14.3 ( #65056 , #65343 , #65378 ) Pin grpcio to 1.75.0 in test deps to avoid the grpc.aio performance regression ( #65112 ) Give ray-wheel-minimal-build a distinct wanda image name ( #65318 , #65383 ) Move cu130 job tests off g4dn.4xlarge to g6.4xlarge ( #65213 ) Bump the version to 2.58.0 and publish 2.56.0 perf metrics ( #65252 , #64196 ) 🔨 Fixes Fix org_lzma_lzma download failures by using the SourceForge redirector ( #64906 ) Install the data CI depset after conda ffmpeg so removed packages are restored ( #65334 , #65341 ) Drop -Wl,-pie from the vendored RocksDB WITH_TSAN link flags ( #64917 ) Floor peft>=0.18 for transformers 5.x in the huggingface_accelerate release test ( #65062 ) Documentation Add initial documentation for Ray sandboxing ( #65503 , #65573 ) Update the Ray History Server docs for RAY_ROOT_DIR -> STORAGE_ROOT_DIR and use a RayJob sample YAML ( #65139 , #65441 , #65510 , #65505 , #65531 ) Add a contributor guide for editing and managing Python dependencies ( #63547 ) Clarify the API deprecation policy ( #65093 ) Document the safe-to-evict annotation for the Ray head Pod, and autoscaler v1 restartPolicy behavior ( #64907 , #64900 ) Update the Gaudi tutorials and examples to the latest versions ( #58861 ) Correct the TLS verification comments and the metric cardinality default comments ( #61977 , #64478 ) Route API reference pages and autodoc machinery to the API-surface checks, ignore inherited API annotations, walk ray.data.llm as its own head module, and reserve the doc tag for doc validation ( #64812 , #65196 , #65040 , #64775 , #65208 ) Scope API signature bold weight to the object name, and reclassify sphinx unknown-document and docutils-inline-markup as judgment ( #64933 , #64839 ) Fix minor typos, bump the docs template build-id pins, and add Douglas Strodtman to the committer list ( #64864 , #65041 , #65092 ) Thanks Many thanks to all those who contributed to this release! @bveeramani , @yjaw , @sampan-s-nayak , @spencer-p , @iaalm , @risjai , @kahlun , @liulehui , @eicherseiji , @jhasm , @ronny-anyscale , @KuongB , @Ranoobaba , @Sparks0219 , @alimaazamat , @yuhuan130 , @jeffreywang88 , @AarryaSaraf , @johntomcat7408-cmyk , @tqKhanh1712 , @praneethkaturi , @elliot-barn , @tanmayrauth , @skpark-rh , @YashwanthRanjanSingaravel , @Yicheng-Lu-llll , @pseudo-rnd-thoughts , @nadongjun , @vineethsaivs , @owenowenisme , @saitejabandaru-in , @RocMarshal , @karticam , @win5923 , @Hyunoh-Yeo , @dragongu , @YoyinZyc , @chiayi , @HrushiYadav , @martinlhw , @sai-miduthuri , @dstrodtman , @JasonLi1909 , @2uchan , @mukktinaadh , @coqian , @ayushk7102 , @LuciferYang , @NripeshN , @MortalHappiness , @verma-divyanshu-git , @ans9868 , @johntaylor-cell , @prasad-anyscale , @edoakes , @ShockYoungCHN , @fscnick , @JiangJiaWei1103 , @subpath , @shivamsingh-007 , @RinZ27 , @richabanker , @iamjustinhsu , @malsbat , @andrewsykim , @ryanaoleary , @vinay7373 , @Kunchd , @petern48 , @kyuds , @rueian , @rayhhome , @xyuzh , @hao-aaron , @CaiZhanqi , @kalyanamdewri , @abhishekverma-ray , @khluu , @nh-atuan , @odncode , @robertnishihara , @machichima , @Arkit003 , @goutamvenkat-anyscale , @ArturNiederfahrenhorst , @Myasuka",
  "tags": [
    "Anyscale",
    "ray.releases",
    "ml-framework",
    "distributed",
    "python"
  ]
}