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🚀 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.

📂 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

🛠️ 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.

🎯 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