Vercel Launches Daemons and Adds Python Support

The platform expands its infrastructure capabilities with background worker tools and persistent storage options.

Updated on Oct. 15, 2026 in Data Centers

Isometric editorial illustration of modular storage units and data conduits representing backend technical infrastructure. — Vercel has launched Daemons in public beta and added Python support, enabling developers to manage complex backend architectures and persistent storage. AI Illustration. Upload story photo >

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Vercel has introduced Daemons into public beta, allowing developers to deploy containers and manage specific process counts per region. Additionally, the company made both Python support and its Drives persistent storage solution generally available.

Why it matters

These updates provide developers with greater control over concurrency for asynchronous workloads while enabling necessary persistent storage options for AI agents. By integrating these features, Vercel aims to support more complex backend architectures directly on its platform.

Vercel plans include default storage capacities of 1 TiB, while the Hobby plan features a 1 GiB limit and enterprise configurations reach up to 16 TiB. Writes to Drives are handled via local NVMe disk before streaming to object storage.

The players

Vercel

Vercel is a cloud platform for serverless deployment and frontend hosting that supports various programming languages and modern development workflows.

The details

Developers can deploy Daemons through Git or the Vercel CLI to manage background workers. The new Python support extends to frameworks including FastAPI, Flask, and Django, while Drives allow agents to mount files in new sandboxes.

October 15, 2026: Vercel introduced the new features at its Ship conference.

The Tech Race

This release expands the platform's utility by adding stateful capabilities and background processing to an environment previously focused primarily on stateless frontend deployment. It signals a move by Vercel to compete more directly with traditional backend infrastructure providers.

Developers can now run background tasks and Python backends directly within their existing Vercel workflow without switching to secondary hosting services. This integration simplifies deployment pipelines and reduces the complexity of managing persistent storage for AI-driven applications.

The takeaway

The move toward persistent storage and containerized workers allows teams to centralize their backend logic rather than relying on disparate cloud services. Developers should evaluate their current storage needs to determine if their project fits within the new Tiered Drives capacity limits.