Udemy - Generative AI for DevOps

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Udemy - Generative AI for DevOps (Size: 2.7 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Introduction
  1. Introduction.mp4 15.7 MB
  2 - Generative AI Concepts for DevOps
  3 - Practical AI-Assisted DevOps
  10. Reference Source Code.html 5.6 KB
  11. AI-Assisted Infrastructure as Code (IaC).mp4 12.1 MB
  12. Demo AI-Assisted Infrastructure as Code (Bicep + GitHub Copilot).mp4 168.2 MB
  12. Prompts - GitHub Gists.url 102.4 B
  13. Demo Pipeline Authoring and Optimization Using AI.mp4 129.5 MB
  13. Prompts - GitHub Gist.url 102.4 B
  14. Demo AI for Test Strategy and Release Confidence (Description).html 819.2 B
  14. Demo AI for Test Strategy and Release Confidence.mp4 122.2 MB
  14. Prompts - GitHub Gists.url 102.4 B
  15. Demo AI-Assisted Release Notes Automation (Description).html 819.2 B
  15. Demo AI-Assisted Release Notes Automation.mp4 131.3 MB
  15. Prompts - GitHub Gists.url 102.4 B
  16. Demo AI-Assisted Incident Response & Root Cause Analysis.mp4 59.7 MB
  16. Prompts - GitHub Gists.url 102.4 B
  17. Section Review.mp4 7.2 MB
  4 - DevOps AI Tools, Governance, and Enterprise Readiness
  18. Section Overview.mp4 3.5 MB
  19. Enterprise AI Tooling Landscape for DevOps.mp4 25.4 MB
  20. Review of AI Tooling Used in DevOps.mp4 46.2 MB
  21. Establishing AI Guardrails for Enterprise DevOps Teams.mp4 27.3 MB
  22. Auditing, Accountability, and Operational Oversight.mp4 11.4 MB
  23. Creating an AI Adoption Playbook for Your Organization.mp4 20 MB
  24. Measuring ROI of AI in DevOps.mp4 27.2 MB
  25. Section Review.mp4 5.4 MB
  5 - Integrating Generative AI into DevOps Pipelines
  26. Section Overview.mp4 5.6 MB
  27. Reference Source Code.html 5.6 KB
  28. Provisioning and Connecting to an AI Engine.mp4 55.9 MB
  29. Designing Deterministic AI Workflow Steps (Description).html 819.2 B
  29. Designing Deterministic AI Workflow Steps.mp4 101.5 MB
  30. Orchestrating AI Jobs in GitHub Actions.mp4 80.2 MB
  31. Context Engineering for DevOps AI.mp4 101 MB
  32. Cost & Performance Management for AI Pipelines.mp4 144 MB
  33. Observability and Feedback Loops for AI-Assisted Pipelines.mp4 96.8 MB
  34. Secure Integration Patterns (Technical Security).mp4 33.8 MB
  35. AI-Augmented ChatOps.mp4 63 MB
  36. Section Review.mp4 8.2 MB
  6 - Agentic AI for Advanced DevOps Scenarios
  37. Section Overview.mp4 4.1 MB
  38. AI Agents 101 Anatomy of an Agent.mp4 21.3 MB
  39. Agentic AI in CI CD Pipelines (Safe and Unsafe Use Cases).mp4 13 MB
  40. Reference Source Code.html 5.6 KB
  41. Demo Developing a Minimal DevOps Agent.mp4 75.6 MB
  42. Demo Adding Minimal Agent to a GitHub Workflow.mp4 41.7 MB
  43. Agent Failure Modes in Production.mp4 21.7 MB
  44. Progressive Autonomy Design Model.mp4 26.9 MB
  45. Agentic Patterns in DevOps Workflows (map to PRs, builds, incidents).mp4 11.8 MB
  46. Demo Developing PR Code Quality Suggesting Agent.mp4 90.5 MB
  47. Demo Integrating Agent into PR Code Quality Assessment Workflow.mp4 69.6 MB
  48. Memory in Agentic Systems What to Store, What Not to Store.mp4 14.8 MB
  49. Demo Adding Workflow-Level Memory to a DevOps Agent.mp4 94.3 MB
  50. Tools and MCP Standardizing Context + Actions Across Agents.mp4 14.6 MB
  51. Demo Build an MCP Server For GitHub Tooling.mp4 139 MB
  52. Demo Extend The Agent with MCP Tools.mp4 85.9 MB
  53. Demo Test and Verify the GitHub Workflow using the MCP Agent.mp4 64.2 MB
  54. Multi-Agent Systems for Incident Response.mp4 30 MB
  55. Demo Creating Multi-Agent Implementation.mp4 93.9 MB
  56. Demo Testing a Multi-Agent Workflow.mp4 24.1 MB
  57. Observability and Evaluation of AI Agents.mp4 29.2 MB
  58. Demo Adding Observability and Evaluation to An Agent.mp4 118.5 MB
  59. Demo Visualize Agent Open Telemetry with Aspire.mp4 38.6 MB
  60. Section Review.mp4 5.9 MB
  7 - Conclusion
  61. Conclusion and Recommendations.mp4 31.3 MB
  9. Section Overview.mp4 3.4 MB
  3. Section Overview.mp4 7 MB
  4. How Can Generative AI Help DevOps Engineers (Description).html 819.2 B
  4. How Can Generative AI Help DevOps Engineers.mp4 28.4 MB
  5. Where Generative AI Adds Value in the DevOps Lifecycle (Description).html 819.2 B
  5. Where Generative AI Adds Value in the DevOps Lifecycle.mp4 43.2 MB
  6. AI-Assisted vs AI-Autonomous DevOps (Description).html 819.2 B
  6. AI-Assisted vs AI-Autonomous DevOps.mp4 26.8 MB
  7. Risk Awareness Hallucinations, Drift, and Overreach.mp4 26.5 MB
  8. Section Review.mp4 6.3 MB
  2. Course Scope and Tooling.mp4 4.6 MB

Description


Generative AI for DevOps

https://WebToolTip.com

Published 3/2026
Created by Trevoir Williams
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 61 Lectures ( 5h 8m ) | Size: 2.74 GB

Use Generative AI, GitHub Copilot, Azure OpenAI, GitHub Actions, and .NET 10 to modernize DevOps Workflows

What you'll learn
✓ Apply Generative AI across the DevOps lifecycle for coding, pipelines, infrastructure, testing, release management, and incident response.
✓ Utilize Copilot to streamline CI/CD workflows.
✓ Automate repetitive DevOps tasks with Copilot.
✓ Enhance infrastructure as code (IaC) practices.
✓ Troubleshoot and monitor with AI assistance.
✓ Develop DevOps tuned AI Agents
✓ Implemented Autonomous AI Agents
✓ Integreate LLM Reasoning into GitHub Workflows
✓ Understand the difference between AI-assisted and AI-autonomous DevOps, including safe and unsafe use cases.
✓ Use AI for ChatOps, release notes, test strategy, root cause analysis, and documentation workflows.
✓ Add observability, evaluation, and feedback loops to AI-assisted pipelines and agents.
✓ Improve DevOps outcomes with better prompt engineering and context engineering for operational tasks.
✓ Design deterministic and secure AI-assisted workflow steps for GitHub Actions and pipeline automation.
✓ Build and extend a minimal DevOps agent, add memory carefully, and integrate MCP-based tooling into workflows.
✓ Establish enterprise guardrails for security, compliance, accountability, and responsible AI use in DevOps teams.

Requirements
● Git and GitHub fundamentals
● Basic command-line usage
● A GitHub account (personal or enterprise).
● Basic cloud and infrastructure concepts
● Core DevOps concepts such as CI/CD, pull requests, source control, pipelines, and release workflows
● Intermediate development experience with C# and .NET is helpful because the course examples are standardized on .NET
● Familiarity with Azure and GitHub Actions will help you move faster through the s

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