Ray

Ray

Anyscale
+
+

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About

Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.

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

Companies, professionals and developers in search of a solution to simplify model deployment

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
Open source. Consumption-based.
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

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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

BentoML
United States
www.bentoml.com

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

Categories

Categories

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Apache Airflow
Kubernetes
PyTorch
TensorFlow
Amazon EKS
Azure Functions
Azure Kubernetes Service (AKS)
Dask
Databricks
Flyte
Google Cloud Platform
Google Compute Engine
Grafana Cloud
H2O.ai
Heroku
Keras
LanceDB
Prometheus

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Apache Airflow
Kubernetes
PyTorch
TensorFlow
Amazon EKS
Azure Functions
Azure Kubernetes Service (AKS)
Dask
Databricks
Flyte
Google Cloud Platform
Google Compute Engine
Grafana Cloud
H2O.ai
Heroku
Keras
LanceDB
Prometheus
Claim BentoML and update features and information
Claim BentoML and update features and information
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