Update devops projects

src/data/projects/basic-github-actions.md

@@ -1,36 +0,0 @@
----
-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`
-
-<hr />
-
-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.

src/data/projects/basic-iac-with-terraform.md

@@ -1,42 +0,0 @@
----
-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).
-
-<hr />
-
-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.

src/data/projects/docker-webserver.md

@@ -1,39 +0,0 @@
----
-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/).
-
-<hr />
-
-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.

src/data/projects/local-monitoring-stack.md

@@ -1,57 +0,0 @@
----
-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/).
-
-<hr />
-
-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.