
Modern Web
Fluid Compute: Vercel’s Next Step in the Evolution of Serverless?
Feb 13, 2025
Mariano Cocirio, Staff Product Manager at Vercel, dives into Fluid Compute, an innovative cloud computing model that revolutionizes serverless applications. He discusses how this model tackles AI workload challenges by optimizing resource management and reducing costs related to idle time. Mariano highlights that developers can adopt Fluid Compute without major changes, while still benefiting from improved performance and scalability. The conversation also sheds light on the role of observability tools in maximizing efficiency and managing costs.
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Quick takeaways
- Fluid Compute combines serverless scalability with traditional server efficiency, optimizing resource management to reduce costs for AI workloads.
- The model simplifies development by minimizing changes to existing codebases, allowing developers to leverage multiple concurrent executions without major restructuring.
Deep dives
Challenges of Traditional Serverless Computing
Traditional serverless computing struggles to meet the demands of AI workloads, which often require longer processing times. As AI-generated content, such as music and videos, becomes more complex, the latency associated with these requests grows significantly, leading to potential cost inefficiencies. When serverless architectures process these requests serially, idle time accumulates during lengthy computations, resulting in users paying for periods when the CPU is underutilized. By addressing these challenges, Fluid Compute aims to enhance efficiency and reduce costs for developers working with AI applications.
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