🚀 DevOps, AI for Ops, and Cloud Security Labs

This repository is a collection of labs, presentations, and scripts covering modern DevOps practices, AI for operations (AIOps), cloud security, and monitoring. It is designed to help engineers, students, and professionals explore hands-on CI/CD, cloud-native security, observability, and AI-driven cost optimization.

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📂 Repository Contents

🔹 AI & AIOps

• AI for cost optimization.pptx → Using AI to optimize cloud costs.
• aI for devops.pptx → Leveraging AI in DevOps workflows.
• AIOPS.pptx → Introduction to AIOps (AI for IT operations).

🔹 CI/CD (Jenkins, GitHub, Azure DevOps, AWS CodeBuild)

• Jenkins CICD and scanning with sonar.pptx
• Jenkins sonarsetup.docx
• Jenkinsfile, jenkinsfilesonarnodejs, jenkinsnodejs
• Azure devops pipeline.pptx
• AWS Code Build.docx

🔹 Cloud Security & Scanning

• Aws inspector.pptx, Lab-aws-inspector.docx, Lab2 Inspector Scan.docx
• AWS CodeGuru Security Integration with GitHub.docx, Aws codeguru.pptx
• Checkpoint using DAST.pptx, Lab-ZAP.docx
• Lab SBOM.docx, Lab SCA-Trivy.docx
• SCA and Scan CVE.pptx, Scanning tool.pptx
• Protect secrets.pptx

🔹 Monitoring & Observability (Datadog, Prometheus, RUM)

• Prometheus Installation.docx
• Kubernetes-datadog.txt, Log streaming datadog.docx, RUM-datadog.docx
• Syntectic testing.docx

🔹 Git & Collaboration

• Scm and branching.pptx
• Slack.docx

🔹 Capstone & Workshops

• Capstone project.pptx, capstone proj.txt
• Azure workshop.pdf, Azure.pptx
• blue-green.docx

🔹 Supporting Files

• dockerfile, app.py, requirements.txt, index.html
• kubecost → setup for Kubernetes cost management

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🛠️ How to Use

1. Clone the repository:

   git clone https://github.com/<your-org>/<your-repo>.git
   cd <your-repo>

2. Explore labs by reading the .docx, .pptx, and .txt files.

3. Run sample code:

   python app.py

4. Use provided Jenkinsfiles and Dockerfile for CI/CD experiments.

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🎯 Learning Outcomes

By working through this repository, you will learn:

• Setting up CI/CD pipelines with Jenkins, GitHub, Azure DevOps, and AWS CodeBuild
• Integrating static and dynamic security scanning (SonarQube, Trivy, ZAP, AWS Inspector)
• Implementing AIOps for monitoring, anomaly detection, and cost optimization
• Observability with Datadog, Prometheus, RUM, synthetic testing
• Secrets management and DevSecOps best practices
• Cost optimization with Kubecost + AI-driven insights

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