diff --git a/src/data/projects/basic-github-actions.md b/src/data/projects/basic-github-actions.md
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+---
+title: 'Github Actions Workflow'
+description: 'Write GitHub Actions workflow to deploy a simple GitHub Pages site.'
+isNew: true
+sort: 3
+difficulty: 'beginner'
+nature: 'CI/CD'
+skills:
+ - 'devops'
+ - 'github actions'
+ - 'ci/cd'
+seo:
+ title: 'Github Actions Workflow'
+ description: 'Write GitHub Actions workflow to deploy a simple GitHub Pages site.'
+ keywords:
+ - 'basic ci/cd'
+ - 'devops'
+ - 'devops projects'
+roadmapIds:
+ - 'git-github'
+ - 'devops'
+---
+
+In this project, you will write a basic HTML file and setup a GitHub Actions workflow to test, build & deploy it to GitHub Pages.
+
+## Requirements
+
+- Create a simple HTML file (the content is up to you)
+- Create a GitHub Actions workflow that will test, build & deploy the website to [GitHub Pages](https://pages.github.com/).
+- Failures in the workflow should be clearly indicated and failures will halt the workflow
+- The workflow should be in the `.github/workflows` directory
+- The workflow file should be named `main.yml`
+
+
+
+If you are looking to build a more advanced version of this project, you can either create a more advanced Astro website or you can build a more advanced GitHub Actions workflow.
diff --git a/src/data/projects/basic-iac-with-terraform.md b/src/data/projects/basic-iac-with-terraform.md
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+---
+title: 'Basic Infrastructure as Code with Terraform'
+description: 'Provision a simple cloud infrastructure using Terraform'
+isNew: false
+sort: 4
+difficulty: 'beginner'
+nature: 'CLI'
+skills:
+ - 'terraform'
+ - 'devops'
+ - 'iac'
+ - 'cloud'
+seo:
+ title: 'Basic Infrastructure as Code with Terraform'
+ description: 'Learn to provision cloud resources using Terraform'
+ keywords:
+ - 'terraform'
+ - 'infrastructure as code'
+ - 'cloud provisioning'
+ - 'devops'
+roadmapIds:
+ - 'devops'
+ - 'terraform'
+ - 'aws'
+---
+
+In this project, you will use Terraform to provision a virtual machine in AWS.
+
+## Requirements
+
+- Install Terraform on your local machine.
+- Set up an account with a AWS and obtain necessary credentials.
+- Create a `main.tf` file in the root directory of your project.
+- Write Terraform configuration to provision a basic resource (e.g., an EC2 instance on AWS or a VM on Azure).
+- Use Terraform commands to initialize, plan, apply, and destroy your infrastructure.
+- The provisioned resource should be accessible and verifiable in your cloud provider's console.
+
+You can learn more about Terraform basics [here](https://learn.hashicorp.com/terraform).
+
+
+
+For a more advanced version of this project, consider adding multiple resources, using variables and outputs, or implementing a modular structure for your Terraform configuration.
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diff --git a/src/data/projects/docker-webserver.md b/src/data/projects/docker-webserver.md
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+---
+title: 'Docker Web Server'
+description: 'Create a Web Server using Docker & NGINX'
+isNew: false
+sort: 3
+difficulty: 'beginner'
+nature: 'CLI'
+skills:
+ - 'docker'
+ - 'devops'
+ - 'nginx'
+ - 'web'
+seo:
+ title: 'Docker Web Server'
+ description: 'Create a Web Server using Docker & NGINX'
+ keywords:
+ - 'docker web server'
+ - 'docker'
+ - 'system administration'
+ - 'web server'
+roadmapIds:
+ - 'devops'
+ - 'docker'
+---
+
+In this project, you will create an NGINX web server that will serve a simple HTML page using Docker.
+
+## Requirements
+
+- The Dockerfile should be named `Dockerfile`.
+- The Dockerfile should be in the root directory of the project.
+- The build process will add a local HTML file to the container, which will be accessible to NGINX.
+- The simple HTML page will be accessible to you from `localhost:8080`
+
+You can learn more about writing a Dockerfile [here](https://docs.docker.com/engine/reference/builder/).
+
+
+
+If you are looking to build a more advanced version of this project, you can consider using the `alpine:latest` image and setting up NGINX yourself rather than using the official NGINX image.
diff --git a/src/data/projects/local-monitoring-stack.md b/src/data/projects/local-monitoring-stack.md
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+---
+title: 'Local Monitoring System with Docker'
+description: 'Set up a local monitoring system using Docker with Grafana and Prometheus'
+isNew: false
+sort: 1
+difficulty: 'intermediate'
+nature: 'CLI'
+skills:
+ - 'docker'
+ - 'devops'
+ - 'monitoring'
+ - 'grafana'
+ - 'prometheus'
+seo:
+ title: 'Local Monitoring System with Docker, Grafana, and Prometheus'
+ description: 'Learn to set up a local monitoring system using Docker with Grafana and Prometheus'
+ keywords:
+ - 'docker'
+ - 'monitoring'
+ - 'grafana'
+ - 'prometheus'
+ - 'devops'
+roadmapIds:
+ - 'devops'
+ - 'docker'
+---
+
+In this project, you will set up a local monitoring system using Docker, Grafana, and Prometheus. This setup will allow you to collect metrics and visualize them in a dashboard.
+
+## Requirements
+
+- Docker and Docker Compose installed on your local machine.
+- Create a `docker-compose.yml` file in the root directory of your project.
+- Set up Prometheus as the metrics collection system.
+- Configure Grafana as the visualization tool.
+- Create a simple dashboard in Grafana to display system metrics.
+- Add a sample application to monitor, such as a simple web server.
+
+Your `docker-compose.yml` file should define services for:
+1. Prometheus
+2. Grafana
+3. A sample application to monitor
+
+## Steps
+
+1. Create the `docker-compose.yml` file with services for Prometheus and Grafana.
+2. Configure Prometheus to scrape metrics (you'll need a `prometheus.yml` configuration file).
+3. Set up Grafana to use Prometheus as a data source.
+4. Create a simple dashboard in Grafana to display metrics.
+5. Use `docker-compose up` to start your monitoring stack.
+6. Access Grafana through your web browser and verify that metrics are being collected and displayed.
+
+You can learn more about Prometheus [here](https://prometheus.io/docs/introduction/overview/) and Grafana [here](https://grafana.com/docs/grafana/latest/).
+
+
+
+For a more advanced version of this project, consider adding alerting rules in Prometheus, setting up additional exporters to collect more diverse metrics, or monitoring a multi-container application.
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