October 29 from 10am - 11am PT
As LLMs become increasingly central to enterprise AI applications, ensuring reliable, scalable, and cost-efficient deployment is crucial. For many teams, the choice between SaaS and VPC deployment models raises critical questions about performance, observability, and scalability. In this webinar, we’ll explore the key differences between SaaS and VPC, and how Predibase’s Inference Engine provides enterprise-grade solutions for both, with a focus on maximizing reliability and efficiency.
We’ll cover:
- Turbo LoRA and FP8 for 4x throughput: Learn how Turbo LoRA and FP8 significantly increase fine-tuned model throughput.
- Observability Tools: Leveraging logs, graphs, and event tracking for real-time monitoring and system health insights.
- Autoscaling & Cold Starts: How our autoscaling feature minimizes cold starts and ensures optimal burst capacity to handle spikes in traffic.
- Multi-Region High Availability: Ensuring consistent service with multi-region load balancing, automatic failover, and the ability to seamlessly move jobs between clusters.
- VPC Deployment: The benefits of deploying within your own private cloud, with complete control over data and infrastructure.
Join us to learn how we designed a highly resilient AI infrastructure that can dynamically scale, provide robust failover mechanisms, and meet enterprise performance demands across any deployment model.
Featured Speakers:
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Travis Addair Co-Founder & CTO, Predibase |
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Noah Yoshida Staff Software Engineer, Predibase |
