Ray

Ray

Anyscale
+
+

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About

Highly scalable and standards-based model inference platform on Kubernetes for trusted AI. KServe is a standard model inference platform on Kubernetes, built for highly scalable use cases. Provides performant, standardized inference protocol across ML frameworks. Support modern serverless inference workload with autoscaling including a scale to zero on GPU. Provides high scalability, density packing, and intelligent routing using ModelMesh. Simple and pluggable production serving for production ML serving including prediction, pre/post-processing, monitoring, and explainability. Advanced deployments with the canary rollout, experiments, ensembles, and transformers. ModelMesh is designed for high-scale, high-density, and frequently-changing model use cases. ModelMesh intelligently loads and unloads AI models to and from memory to strike an intelligent trade-off between responsiveness to users and computational footprint.

About

Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and professionals searching for a model inference platform on Kubernetes

Audience

ML and AI Engineers, Software Developers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

KServe
kserve.github.io/website/latest/

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

Vertex AI

Vertex AI

Google
Vertex AI

Vertex AI

Google
AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

Kubernetes
Amazon EC2 Trn2 Instances
Bloomberg
Dask
Docker
Feast
Flyte
Gojek
Google Cloud Platform
Google Kubernetes Engine (GKE)
IBM Cloud
Kubeflow
NAVER
NVIDIA DRIVE
PyTorch
Python
Union Cloud
VLLM
ZenML
io.net

Integrations

Kubernetes
Amazon EC2 Trn2 Instances
Bloomberg
Dask
Docker
Feast
Flyte
Gojek
Google Cloud Platform
Google Kubernetes Engine (GKE)
IBM Cloud
Kubeflow
NAVER
NVIDIA DRIVE
PyTorch
Python
Union Cloud
VLLM
ZenML
io.net
Claim KServe and update features and information
Claim KServe and update features and information
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Claim Ray and update features and information