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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Deploy your machine learning model in the cloud within minutes using a consolidated packaging format that supports both online and offline operations across various platforms. Experience a performance boost with throughput that is 100 times greater than traditional flask-based model servers, achieved through our innovative micro-batching technique. Provide exceptional prediction services that align seamlessly with DevOps practices and integrate effortlessly with widely-used infrastructure tools. The unified deployment format ensures high-performance model serving while incorporating best practices for DevOps. This service utilizes the BERT model, which has been trained with the TensorFlow framework to effectively gauge the sentiment of movie reviews. Our BentoML workflow eliminates the need for DevOps expertise, automating everything from prediction service registration to deployment and endpoint monitoring, all set up effortlessly for your team. This creates a robust environment for managing substantial ML workloads in production. Ensure that all models, deployments, and updates are easily accessible and maintain control over access through SSO, RBAC, client authentication, and detailed auditing logs, thereby enhancing both security and transparency within your operations. With these features, your machine learning deployment process becomes more efficient and manageable than ever before.

Description

dstack simplifies GPU infrastructure management for machine learning teams by offering a single orchestration layer across multiple environments. Its declarative, container-native interface allows teams to manage clusters, development environments, and distributed tasks without deep DevOps expertise. The platform integrates natively with leading GPU cloud providers to provision and manage VM clusters while also supporting on-prem clusters through Kubernetes or SSH fleets. Developers can connect their desktop IDEs to powerful GPUs, enabling faster experimentation, debugging, and iteration. dstack ensures that scaling from single-instance workloads to multi-node distributed training is seamless, with efficient scheduling to maximize GPU utilization. For deployment, it supports secure, auto-scaling endpoints using custom code and Docker images, making model serving simple and flexible. Customers like Electronic Arts, Mobius Labs, and Argilla praise dstack for accelerating research while lowering costs and reducing infrastructure overhead. Whether for rapid prototyping or production workloads, dstack provides a unified, cost-efficient solution for AI development and deployment.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
AWS Lambda
Amazon SageMaker
Azure Functions
Google Cloud Platform
Google Cloud Run
Google Compute Engine
Grafana
H2O.ai
Heroku
Keras
Knative
Kubernetes
Microsoft Azure
NVIDIA DRIVE
Prometheus
PyTorch
Python
Swagger
ZenML

Integrations

Amazon Web Services (AWS)
AWS Lambda
Amazon SageMaker
Azure Functions
Google Cloud Platform
Google Cloud Run
Google Compute Engine
Grafana
H2O.ai
Heroku
Keras
Knative
Kubernetes
Microsoft Azure
NVIDIA DRIVE
Prometheus
PyTorch
Python
Swagger
ZenML

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

BentoML

Country

United States

Website

www.bentoml.com

Vendor Details

Company Name

dstack

Founded

2022

Country

Germany

Website

dstack.ai/

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Alternatives

Alternatives