Deploying and debugging RAD Studio applications has never been easier. With our new Docker image and our revamped run.sh
script, this process is now streamlined and more user-friendly. This post introduces our optimized PAServer Docker solution, highlighting significant improvements, including a whopping 64% reduction in image size.
Table of Contents
What is PAServer?
PAServer (Platform Assistant Server) is a tool that facilitates cross-platform development and deployment for RAD Studio, Delphi, and C++Builder. It enables remote compilation and debugging, allowing developers to build and debug applications on different platforms, such as Windows, Linux, macOS, iOS, and Android, from a single development environment. This integration streamlines the development process, enhancing efficiency and productivity by managing file transfers and remote sessions easily.
Why use Docker for Linux development?
Using Docker for development offers several key benefits that streamline the development process and enhance productivity. The key factors for using Docker are:
- Consistency and Reproducibility: Docker makes sure your app and environment work the same everywhere, from your computer to production, so no more “it works on my machine” problems.
- Isolation and Independence: Thanks to Docker’s container isolation, multiple instances of the same app with different setups can be run on the same machine without interfering with each other.
- Rapid Setup and Deployment: Setting up a new environment is a breeze with Docker. A few commands and you’re good to go.
- Scalability and Resource Efficiency: Docker containers are lightweight, using fewer resources than virtual machines. This means better performance and you can run more stuff on the same hardware.
- CI/CD Integration: Docker works great with CI/CD pipelines, automating testing, building, and deployment in a consistent environment, making your life easier.
What’s New?
- Optimized Image Size: The base Docker image has been reduced by 64%, resulting in faster downloads and less storage usage.
- Enhanced
run.sh
Script: Simplifies setup and deployment with flexible configuration options.
Key Features
Our Docker image and run.sh
script offer a range of features to make developing and deploying RAD Studio applications easier:
- Customizable Container Names: Easily assign unique names to your PAServer containers.
- Flexible Volume Mapping: Designate custom paths for data storage and access the compiled binaries directly from your computer.
- Background Running: Option to run containers in detach mode.
- Configurable Ports: Customize the port where PAServer runs.
- Production Mode: Toggle production mode on.
- Version: Specify which specific PAServer version to deploy.
- Password Protection: Secure your PAServer with a custom password.
All these options have been integrated into the new run.sh
script and you can easily access all the info through the handy --help
arg.
Accessing the new image and repo code
The new image is available on DockerHub, and the run.sh
script and the rest of the code to build your own images can be downloaded from GitHub.
Using run.sh
Script
Pull the repo from GitHub and navigate to the directory containing run.sh
in your terminal. Execute the script with your preferred options:
./run.sh [OPTIONS]
Options
--name
or-n
: Container’s name (e.g.,--name=myPAServer
).--path
or-pa
: Bind path for volume mapping (e.g.,--path=/my/custom/path
).--detach
or-d
: Run the container in detach mode (background).--port
or-p
: Port for PAServer (e.g.,--port=64211
).--production
or-pr
: Enable production mode (true
).--version
or-v
: PAServer version (e.g.,--version=latest
).--password
or-pw
: Set a password for PAServer (e.g.,--password=securepass
).--help
or-h
: Access the help of the script.
Example 1: Production Mode
Example 2: Detach Mode with Specific Version
[crayon-673f55da0d857504377223/]Other functionalities
The updated GitHub repo contains a brand new, in-depth readme that explains more advanced solutions in detail. Using docker run
instead of the new script, docker compose
or create your own image version customizing the Dockerfile
are just some examples.