AWS ECR

Overview: Why Docker Runtimes Matter Laravel Vapor typically provides pre-packaged runtimes that cover 90% of use cases. However, these environments come with a hard limit of 250MB for application size. For media-heavy projects or those requiring niche dependencies, this ceiling is a deal-breaker. Switching to a Docker runtime obliterates these limits, allowing for application images up to 10GB and providing total control over the underlying OS and PHP environment. Prerequisites To follow this guide, you should be comfortable with the Laravel framework and basic CLI commands. Locally, you must have Docker Desktop installed and running. You also need an active Vapor account and the `vapor-cli` package installed in your project. Key Libraries & Tools * **Laravel Vapor**: A serverless deployment platform for Laravel. * **Docker**: The containerization engine used to build and package your environment. * **PHP Extensions**: Specifically GMP or ImageMagick, which often require manual installation in custom environments. Code Walkthrough: Customizing Your Environment First, create a environment-specific Dockerfile at your root. If you are deploying to staging, name it `staging.dockerfile`. ```dockerfile FROM laravelphp/vapor:php74 Install the GMP extension for mathematical operations RUN pecl install gmp && docker-php-ext-enable gmp ``` This file tells Vapor to use the official PHP 7.4 base image and executes a `RUN` command to install the missing extension. To verify the installation within your application, you can use a simple route check: ```php Route::get('/check-extension', function () { return extension_loaded('gmp') ? 'Installed' : 'Missing'; }); ``` Finally, trigger the build and deployment using the standard command. Vapor recognizes the Dockerfile and shifts from a zip-based upload to a container image build. ```bash vapor deploy staging ``` Syntax Notes Vapor uses a specific naming convention for Dockerfiles linked to environments. A file named `production.dockerfile` will only be used during a `vapor deploy production` run. This allows you to maintain different extension sets for local testing versus live environments. Practical Examples Custom runtimes are essential when your application needs to process complex images using ImageMagick or handle high-precision math with GMP. It is also the go-to solution for legacy projects where the vendor folder alone exceeds the standard 250MB serverless limit. Tips & Gotchas Always remember that container builds take longer than standard zip deployments because Vapor must build and push the image to AWS ECR. If your build fails, check that your local Docker daemon is running; Vapor uses your local machine's resources to build the image before pushing it to the cloud.