ray-project/ray Graph

Graph Summary

ray-project/ray graph connects 3 alternatives, 8 related projects, 1 inferred dependencies, 5 deployment targets, and 3 use cases.

Nodes46

Edges398

Projects33

Dependencies19

Open project knowledge Find alternatives Explore related projects Explain score Compare shortlist

Alternatives3 linked signals Related8 linked signals Dependencies1 linked signals Deployments5 linked signals Use Cases3 linked signals Categories28 linked signals Migrations3 linked signals

Project Context

ray

Maintainerray-project

LicenseApache-2.0

LanguagePython

Recent activityActive in the last week

Deployment Targets

Dependencies

Knowledge Graph

46 nodes / 398 edges

ray-project/ray ↔ deepflowio/deepflowUse deepflowio/deepflow when the user needs an ai observability project with docker, kubernetes, library-only deployment options.

ray-project/ray ↔ olemeyer/rocketplaneIOUse olemeyer/rocketplaneIO when the user needs an ai observability project with docker, kubernetes, library-only deployment options.

ray-project/ray ↔ traceloop/hubUse traceloop/hub when the user needs an ai observability project with docker, kubernetes, library-only deployment options.

ray-project/ray ↔ monoscope-tech/monoscopeUse monoscope-tech/monoscope when the user needs an ai observability project with docker, kubernetes, library-only deployment options.

ray-project/ray ↔ eunomia-bpf/agentsightUse eunomia-bpf/agentsight when the user needs an ai observability project with docker, library-only, local deployment options.

ray-project/ray ↔ apache/hertzbeatUse apache/hertzbeat when the user needs an ai observability project with docker, kubernetes, local deployment options.

Alternatives Network

Replacement candidates

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ray-project/ray ↔ pydantic/logfireUse pydantic/logfire when the user needs an ai observability project with library-only, local, cloud deployment options.

ray-project/ray ↔ traceloop/openllmetryUse traceloop/openllmetry when the user needs an ai observability project with library-only, local, cloud deployment options.

ray-project/ray ↔ evidentlyai/evidentlyUse evidentlyai/evidently when the user needs an ai observability project with docker, library-only, local deployment options.

ray-project/ray ↔ open-telemetry/opentelemetry-pythonUse open-telemetry/opentelemetry-python when the user needs an ai observability project with library-only, local, cloud deployment options.

ray-project/ray ↔ microsoft/promptflowUse microsoft/promptflow when the user needs an ai observability project with library-only, local, cloud deployment options.

ray-project/ray ↔ huangbwww/nga-wolf-watcherUse huangbwww/nga-wolf-watcher when the user needs an ai observability project with library-only, local, cloud deployment options.

Migration Paths

What to verify before switching

JSON

These paths are evidence-backed heuristics, not drop-in compatibility claims.

ray-project/ray -> pydantic/logfireCompatibility: high / estimated cost: medium.Shared: category:ai_observability, deployment:library_only, deployment:local, deployment:cloud, use_case:trace LLM applications, use_case:monitor agent behavior, use_case:debug production AI systems, dependency:LLM provider.Gaps: Deployment targets not listed by target: docker, kubernetes. License changes from Apache-2.0 to MIT.Validate: Review license obligations before migrating production code. Compare API, configuration, license, and dependency requirements. Run the target project's minimal example or test suite. Verify deployment, persistence, and tool-execution behavior in the requested runtime.

ray-project/ray -> traceloop/openllmetryCompatibility: high / estimated cost: medium.Shared: category:ai_observability, deployment:library_only, deployment:local, deployment:cloud, use_case:trace LLM applications, use_case:monitor agent behavior, use_case:debug production AI systems, dependency:LLM provider.Gaps: Deployment targets not listed by target: docker, kubernetes.Validate: Compare API, configuration, license, and dependency requirements. Run the target project's minimal example or test suite. Verify deployment, persistence, and tool-execution behavior in the requested runtime.

ray-project/ray -> evidentlyai/evidentlyCompatibility: medium / estimated cost: medium.Shared: category:ai_observability, deployment:docker, deployment:library_only, deployment:local, deployment:cloud, use_case:trace LLM applications, use_case:monitor agent behavior, use_case:debug production AI systems.Gaps: Deployment targets not listed by target: kubernetes. Language changes from Python to Jupyter Notebook.Validate: Compare API, configuration, license, and dependency requirements. Run the target project's minimal example or test suite. Verify deployment, persistence, and tool-execution behavior in the requested runtime.

Use Cases