Fluid compute

Fluid compute offers a blend of serverless flexibility and server-like capabilities. Unlike traditional serverless architectures, which can face issues such as cold starts and limited functionalities, fluid compute provides a hybrid solution. It overcomes the limitations of both serverless and server-based approaches, delivering the advantages of both worlds, including:

• Zero configuration out of the box: Fluid compute comes with preset defaults that automatically optimize your functions for both performance and cost efficiency.
• Optimized concurrency: Optimize resource usage by handling multiple invocations within a single function instance. Can be used with the Node.js and Python runtimes.
• Dynamic scaling: Fluid compute automatically optimizes existing resources before scaling up to meet traffic demands. This ensures low latency during high-traffic events and cost efficiency during quieter periods.
• Background processing: After fulfilling user requests, you can continue executing background tasks using . This allows for a responsive user experience while performing time-consuming operations like logging and analytics in the background.
• Automatic cold start optimizations: Reduces the effects of cold starts through automatic bytecode optimization, and function pre-warming on production deployments.
• Cross-region and availability zone failover: Ensure high availability by first failing over to another availability zone (AZ) within the same region if one goes down. If all zones in that region are unavailable, Vercel automatically redirects traffic to the next closest region. Zone-level failover also applies to non-fluid deployments.
• Error isolation: Unhandled errors won't crash other concurrent requests running on the same instance, maintaining reliability without sacrificing performance.

See What is compute? to learn more about fluid compute and how it compares to traditional serverless models.

You can enable fluid compute through the Vercel dashboard or by configuring your file for specific environments or deployments.

To enable fluid compute through the dashboard:

1. Navigate to your project's Functions Settings in the dashboard
2. Locate the Fluid Compute section
3. Toggle the switch to enable fluid compute for your project
4. Click Save to apply the changes
5. Deploy your project for the changes to take effect

When you enable it through the dashboard, fluid compute applies to all deployments for that project by default.

You can programmatically enable fluid compute using the property in your file. This approach is particularly useful for:

• Testing on specific environments: Enable fluid compute only for custom environments environments when using branch tracking
• Per-deployment configuration: Test fluid compute on individual deployments before enabling it project-wide

Fluid compute is available for the following runtimes:

• Node.js
• Python
• Edge
• Bun
• Rust

Fluid compute allows multiple invocations to share a single function instance, this is especially valuable for AI applications, where tasks like fetching embeddings, querying vector databases, or calling external APIs can be I/O-bound. By allowing concurrent execution within the same instance, you can reduce cold starts, minimize latency, and lower compute costs.