| Overview |
Scalable AI compute platform built on Ray for deploying and fine-tuning large language models in production. |
Datadog Real User Monitoring captures end-user performance data and errors from browser and mobile applications. It integrates with Datadog's infrastructure monitoring for full-stack observability. |
| Pricing |
Pay-per-use ($$-$$$$) |
Paid ($15/1000 sessions/mo) |
| Key Features |
- Ray-based
- Auto-scaling
- Fine-tuning
- Managed endpoints
- Multi-model
- GPU clusters
|
- Real user monitoring
- error tracking
- session replay
- core web vitals
- resource tracking
- long task detection
- frustration signals
- full-stack correlation
|
| Pros |
- Built on Ray
- Excellent scaling
- Production-grade
- Fine-tuning support
|
- Excellent infrastructure integration
- Full-stack visibility
- Strong error tracking
- Good performance metrics
|
| Cons |
- Complex setup
- Higher learning curve
- Enterprise-focused pricing
|
- Expensive at scale
- Requires Datadog ecosystem
- Complex pricing model
- Steep learning curve
|
