| Overview |
Scalable AI compute platform built on Ray for deploying and fine-tuning large language models in production. |
An open-source container orchestration platform for automating deployment, scaling, and management of containerized applications. |
| Pricing |
Pay-per-use ($$-$$$$) |
Free (Free (managed services vary)) |
| Key Features |
- Ray-based
- Auto-scaling
- Fine-tuning
- Managed endpoints
- Multi-model
- GPU clusters
|
- Container orchestration
- Auto-scaling
- Service discovery
- Rolling updates
- Self-healing
- Storage orchestration
- Secret management
- Extensible
|
| Pros |
- Built on Ray
- Excellent scaling
- Production-grade
- Fine-tuning support
|
- Industry standard orchestration
- Highly scalable
- Active community
- Cloud-agnostic
|
| Cons |
- Complex setup
- Higher learning curve
- Enterprise-focused pricing
|
- Very complex
- Steep learning curve
- Resource overhead
- Operational burden
|
