After running my project on a local server for some time, I realized that scaling, maintaining, and securing everything was becoming a challenge. It was time to migrate to the cloud. In this post, I’ll share how I transitioned from hosting locally to using AWS and Azure cloud services, leveraging Terraform, Docker, and GitHub Actions to streamline the entire process.
Step 1: Setting Up Cloud Infrastructure with Terraform I started by using Terraform, an infrastructure-as-code tool, to provision the necessary cloud resources in both AWS and Azure. Terraform allowed me to automate the setup and management of my infrastructure, ensuring consistency and minimizing manual intervention.
For AWS, I spun up an Elastic Container Service (ECS) to host the Dockerized application, while for Azure, I created the necessary resources to handle my database needs. The flexibility of Terraform made it easy to version-control infrastructure changes and apply them across different environments.
Step 2: Migrating PostgreSQL to Azure My application relied on a local PostgreSQL database, and moving it to the cloud was one of the more critical parts of the migration. I decided to use Azure Database for PostgreSQL, which provided a managed solution with built-in security, scalability, and backups.
Using Azure’s pg_dump and pg_restore tools, I migrated the database schema and data from my local server to Azure. With Terraform, I ensured that all the necessary firewall rules and database configurations were applied automatically, reducing the risk of human error during the migration.
Step 3: Hosting the Application with Docker in AWS Once the database was set up, I focused on containerizing my application with Docker. Docker allowed me to package the application and all its dependencies into a single, portable image, ensuring it would run consistently across different environments.
I hosted the application using AWS Elastic Container Service (ECS). By deploying the application in Docker containers, I could easily scale my services, monitor performance, and minimize downtime. AWS ECS also integrates well with other AWS services like Elastic Load Balancing and Auto Scaling, making it an ideal solution for hosting the application.
Step 4: Automating Deployment with GitHub Actions To streamline the deployment process, I created a GitHub Actions pipeline. The pipeline automates the entire build and deployment cycle: every time I push changes to the repository, GitHub Actions builds a new Docker image and pushes it to the AWS Elastic Container Registry (ECR). From there, the new image is automatically deployed to the ECS service.
This pipeline has greatly improved my development workflow, allowing for continuous integration and continuous deployment (CI/CD). With GitHub Actions handling the heavy lifting, I can focus on writing code, knowing that any changes will be tested and deployed without manual intervention.
Migrating my project from a local server to the cloud using AWS and Azure was a major step forward. By leveraging Terraform to automate infrastructure provisioning, Docker to containerize my application, and GitHub Actions to automate deployments, I now have a more scalable, reliable, and maintainable system. The shift to the cloud has opened the door for future growth, giving me the flexibility to handle increasing traffic and the agility to add new features more efficiently.
Want to try out the Control Bot? Sign up for Beta access today and be one of the first to experience the future of interactive gaming.