The easiest way to build Machine Learning APIs¶
Package models trained with any ML frameworks and reproduce them for model serving in production
Deploy anywhere for online API serving or offline batch serving
High-Performance API model server with adaptive micro-batching support
Central hub for managing models and deployment process via Web UI and APIs
Modular and flexible design making it adaptable to your infrastructure
BentoML is a framework for serving, managing, and deploying machine learning models. It is aiming to bridge the gap between Data Science and DevOps, and enable teams to deliver prediction services in a fast, repeatable, and scalable way.
👩💻 Star/Watch/Fork the BentoML Github Repository.
- Getting Started
- Core Concepts
- Advanced Guides
- Offline Batch Serving
- Monitoring with Prometheus
- Understanding BentoML adaptive micro batching
- 1. The overall architecture of BentoML’s micro-batching server
- 2. parameter tuning best practices & recommendations
- 3. How to implement batch mode for custom input adapters
- 4. Comparison
- Adding Custom Model Artifact
- Customizing InputAdapter
- Deploy yatai server behind NGINX
- Using Helm to install YataiService
- 1. Configuration
- 2. Deploying
- Deployment Guides
- Deploying to AWS Lambda
- Deploying to AWS SageMaker
- Deploying to Azure Functions
- Deploying to AWS EC2
- Deploying to Clipper Cluster
- Deploying to AWS ECS(Elastic Container Service)
- Deploying to Google Cloud Run
- Deploying to Azure Container Instance
- Deploying to Kubernetes Cluster
- Deploying to KNative
- Deploying to Kubeflow
- Deploying to KFServing
- Deploying to Heroku
- Deploying to SQL Server Machine Learning Services
- Example Projects
- API Reference
- CLI Reference
- Frequently Asked Questions
- Why BentoML?
- How does BentoML compare to Tensorflow-serving?
- How does BentoML compare to Clipper?
- How does BentoML compare to AWS SageMaker?
- How does BentoML compare to MLFlow?
- Does BentoML do horizontal scaling?
- How does BentoML compare with Cortex?
- How does BentoML compare to Seldon?
- Is there a plan for R support?