Fluid compute: Evolving serverless for AI workloads
Serverless was built for the web. AI just broke it.
Why it matters
Traditional serverless infrastructure wasn't designed for LLM workloads' sustained compute and continuous execution demands. Vercel's 'fluid compute' signals a fundamental shift in how deployment platforms must architect for AI—a challenge every infrastructure vendor will face.
The key facts
8 to knowTraditional serverless designed for stateless, transactional web apps
LLM interactions require sustained compute and continuous execution patterns
Vercel introducing 'fluid compute' as evolution of serverless for AI
Infrastructure architecture shift driven by AI workload requirements
Serverless computing redesigned for AI workloads
LLM interactions require sustained compute vs. stateless transactions
Continuous execution patterns needed for production AI
Infrastructure gap between web app and AI app requirements
Go to the source
Vercel Blogvercel.com
Publisher excerpt: AI’s rapid evolution is reshaping the tech industry and app development. Traditional serverless computing was designed for quick, stateless web app transactions. LLM interactions require a different sustained compute and continuous execution patterns.