# VercelDeployer
[EN] Source: https://mastra.ai/reference/deployer/vercel

The `VercelDeployer` class handles deployment of standalone Mastra applications to Vercel. It manages configuration, deployment, and extends the base [Deployer](/reference/deployer/) class with Vercel specific functionality.

## Usage example

```typescript title="src/mastra/index.ts" showLineNumbers copy
import { Mastra } from "@mastra/core/mastra";
import { VercelDeployer } from "@mastra/deployer-vercel";

export const mastra = new Mastra({
  // ...
  deployer: new VercelDeployer(),
});
```

## Constructor options

The deployer supports a small set of high‑value overrides that are written to the Vercel Output API function config (`.vc-config.json`):

- `maxDuration?: number` — Function execution timeout (in seconds)
- `memory?: number` — Function memory (in MB)
- `regions?: string[]` — Regions to deploy the function (e.g. `['sfo1','iad1']`)

These options are merged into `.vercel/output/functions/index.func/.vc-config.json` while preserving default fields (`handler`, `launcherType`, `runtime`, `shouldAddHelpers`).

### Example with overrides

```typescript title="src/mastra/index.ts" showLineNumbers copy
import { Mastra } from "@mastra/core/mastra";
import { VercelDeployer } from "@mastra/deployer-vercel";

export const mastra = new Mastra({
  // ...
  deployer: new VercelDeployer({
    maxDuration: 600,
    memory: 1536,
    regions: ["sfo1", "iad1"],
  }),
});
```


---
title: "Reference: AnswerRelevancyMetric | Evals"
description: Documentation for the Answer Relevancy Metric in Mastra, which evaluates how well LLM outputs address the input query.
---