---
id: aws-lambda
title: Deploy on AWS Lambda
description: Prepare your crawler to run on AWS Lambda.
---

import ApiLink from '@site/src/components/ApiLink';

import CodeBlock from '@theme/CodeBlock';

import BeautifulSoupCrawlerLambda from '!!raw-loader!./code_examples/aws/beautifulsoup_crawler_lambda.py';
import PlaywrightCrawlerLambda from '!!raw-loader!./code_examples/aws/playwright_crawler_lambda.py';
import PlaywrightCrawlerDockerfile from '!!raw-loader!./code_examples/aws/playwright_dockerfile';

[AWS Lambda](https://docs.aws.amazon.com/lambda/latest/dg/welcome.html) is a serverless compute service that lets you run code without provisioning or managing servers. This guide covers deploying <ApiLink to="class/BeautifulSoupCrawler">`BeautifulSoupCrawler`</ApiLink> and <ApiLink to="class/PlaywrightCrawler">`PlaywrightCrawler`</ApiLink>.

The code examples are based on the [BeautifulSoupCrawler example](../examples/beautifulsoup-crawler).

## BeautifulSoupCrawler on AWS Lambda

For simple crawlers that don't require browser rendering, you can deploy using a ZIP archive.

### Updating the code

When instantiating a crawler, use <ApiLink to="class/MemoryStorageClient">`MemoryStorageClient`</ApiLink>. By default, Crawlee uses file-based storage, but the Lambda filesystem is read-only (except for `/tmp`). Using `MemoryStorageClient` tells Crawlee to use in-memory storage instead.

Wrap the crawler logic in a `lambda_handler` function. This is the entry point that AWS will execute.

:::important

Make sure to always instantiate a new crawler for every Lambda invocation. AWS keeps the environment running for some time after the first execution (to reduce cold-start times), so subsequent calls may access an already-used crawler instance.

**TL;DR: Keep your Lambda stateless.**

:::

Finally, return the scraped data from the Lambda when the crawler run ends.

<CodeBlock language="python" title="lambda_function.py">
    {BeautifulSoupCrawlerLambda}
</CodeBlock>

### Preparing the environment

Lambda requires all dependencies to be included in the deployment package. Create a virtual environment and install dependencies:

```bash
python3.14 -m venv .venv
source .venv/bin/activate
pip install 'crawlee[beautifulsoup]' 'boto3' 'aws-lambda-powertools'
```

[`boto3`](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html) is the AWS SDK for Python. Including it in your dependencies is recommended to avoid version misalignment issues with the Lambda runtime.

### Creating the ZIP archive

Create a ZIP archive from your project, including dependencies from the virtual environment:

```bash
cd .venv/lib/python3.14/site-packages
zip -r ../../../../package.zip .
cd ../../../../
zip package.zip lambda_function.py
```

:::note Large dependencies?

AWS has a limit of 50 MB for direct upload and 250 MB for unzipped deployment package size.

A better way to manage dependencies is by using Lambda Layers. With Layers, you can share files between multiple Lambda functions and keep the actual code as slim as possible.

To create a Lambda Layer:

1. Create a `python/` folder and copy dependencies from `site-packages` into it
2. Create a zip archive: `zip -r layer.zip python/`
3. Create a new Lambda Layer from the archive (you may need to upload it to S3 first)
4. Attach the Layer to your Lambda function

:::

### Creating the Lambda function

Create the Lambda function in the AWS Lambda Console:

1. Navigate to `Lambda` in [AWS Management Console](https://aws.amazon.com/console/).
2. Click **Create function**.
3. Select **Author from scratch**.
4. Enter a **Function name**, for example `BeautifulSoupTest`.
5. Choose a **Python runtime** that matches the version used in your virtual environment (for example, Python 3.14).
6. Click **Create function** to finish.

Once created, upload `package.zip` as the code source in the AWS Lambda Console using the "Upload from" button.

In Lambda Runtime Settings, set the handler. Since the file is named `lambda_function.py` and the function is `lambda_handler`, you can use the default value `lambda_function.lambda_handler`.

:::tip Configuration

In the Configuration tab, you can adjust:

- **Memory**: Memory size can greatly affect execution speed. A minimum of 256-512 MB is recommended.
- **Timeout**: Set according to the size of the website you are scraping (1 minute for the example code).
- **Ephemeral storage**: Size of the `/tmp` directory.

See the [official documentation](https://docs.aws.amazon.com/lambda/latest/dg/gettingstarted-limits.html) to learn how performance and cost scale with memory.

:::

After the Lambda deploys, you can test it by clicking the "Test" button. The event contents don't matter for a basic test, but you can parameterize your crawler by parsing the event object that AWS passes as the first argument to the handler.

## PlaywrightCrawler on AWS Lambda

For crawlers that require browser rendering, you need to deploy using Docker container images because Playwright and browser binaries exceed Lambda's ZIP deployment size limits.

### Updating the code

As with <ApiLink to="class/BeautifulSoupCrawler">`BeautifulSoupCrawler`</ApiLink>, use <ApiLink to="class/MemoryStorageClient">`MemoryStorageClient`</ApiLink> and wrap the logic in a `lambda_handler` function. Additionally, configure `browser_launch_options` with flags optimized for serverless environments. These flags disable sandboxing and GPU features that aren't available in Lambda's containerized runtime.

<CodeBlock language="python" title="main.py">
    {PlaywrightCrawlerLambda}
</CodeBlock>

### Installing and configuring AWS CLI

Install AWS CLI following the [official documentation](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) according to your operating system.

Authenticate by running:

```bash
aws login
```

### Preparing the project

Initialize the project by running `uvx 'crawlee[cli]' create`.

Or use a single command if you don't need interactive mode:

```bash
uvx 'crawlee[cli]' create aws_playwright --crawler-type playwright --http-client impit --package-manager uv --no-apify --start-url 'https://crawlee.dev' --install
```

Add the following dependencies:

```bash
uv add awslambdaric aws-lambda-powertools boto3
```

[`boto3`](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html) is the AWS SDK for Python. Use it if your function integrates with any other AWS services.

The project is created with a Dockerfile that needs to be modified for AWS Lambda by adding `ENTRYPOINT` and updating `CMD`:

<CodeBlock language="dockerfile" title="Dockerfile">
    {PlaywrightCrawlerDockerfile}
</CodeBlock>

### Building and pushing the Docker image

Create a repository `lambda/aws-playwright` in [Amazon Elastic Container Registry](https://docs.aws.amazon.com/AmazonECR/latest/userguide/what-is-ecr.html) in the same region where your Lambda functions will run. To learn more, refer to the [official documentation](https://docs.aws.amazon.com/AmazonECR/latest/userguide/getting-started-cli.html).

Navigate to the created repository and click the "View push commands" button. This will open a window with console commands for uploading the Docker image to your repository. Execute them.

Example:
```bash
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin {user-specific-data}
docker build --platform linux/amd64 --provenance=false -t lambda/aws-playwright .
docker tag lambda/aws-playwright:latest {user-specific-data}/lambda/aws-playwright:latest
docker push {user-specific-data}/lambda/aws-playwright:latest
```

### Creating the Lambda function

1. Navigate to `Lambda` in [AWS Management Console](https://aws.amazon.com/console/).
2. Click **Create function**.
3. Select **Container image**.
4. Browse and select your ECR image.
5. Click **Create function** to finish.

:::tip Configuration

In the Configuration tab, you can adjust resources. Playwright crawlers require more resources than BeautifulSoup crawlers:

- **Memory**: Minimum 1024 MB recommended. Browser operations are memory-intensive, so 2048 MB or more may be needed for complex pages.
- **Timeout**: Set according to crawl size. Browser startup adds overhead, so allow at least 5 minutes even for simple crawls.
- **Ephemeral storage**: Default 512 MB is usually sufficient unless downloading large files.

See the [official documentation](https://docs.aws.amazon.com/lambda/latest/dg/gettingstarted-limits.html) to learn how performance and cost scale with memory.

:::

After the Lambda deploys, click the "Test" button to invoke it. The event contents don't matter for a basic test, but you can parameterize your crawler by parsing the event object that AWS passes as the first argument to the handler.