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DevOps and GenAI using .NET, Azure OpenAI and GitHub

Курс от Packt
Средний≈ 8.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course explores the integration of Generative AI into modern DevOps workflows. It covers AI-assisted automation, pipelines, and agentic systems. Learners gain practical skills using .NET, Azure OpenAI, and GitHub. This course begins by establishing a strong foundation in Generative AI within the DevOps ecosystem, explaining how AI enhances efficiency, decision-making, and automation across the software delivery lifecycle. Learners explore key concepts such as AI-assisted versus autonomous DevOps, along with critical risk considerations including hallucinations, model drift, and operational reliability. The course then transitions into practical implementation, where learners apply AI to real DevOps scenarios such as infrastructure as code, pipeline generation, testing strategies, release automation, and incident response. Through guided demonstrations, learners gain hands-on experience integrating AI into workflows using tools like .NET, Azure OpenAI, and GitHub, improving speed, consistency, and delivery outcomes. In the final phase, advanced topics such as enterprise governance, secure integration patterns, and agentic AI systems are explored in depth. Learners design intelligent pipelines, orchestrate AI-driven workflows, and implement autonomous agents with observability and control, enabling scalable, secure, and production-ready DevOps practices aligned with modern enterprise needs. This course is ideal for DevOps professionals, engineers, and IT managers looking to leverage AI to optimize their workflows. A basic understanding of DevOps concepts and tools such as GitHub and cloud services is recommended for participants. The course combines theory with hands-on demonstrations using real-world tools. You'll progress from basic AI concepts to advanced topics like AI agents in DevOps workflows. The practical approach ensures you can immediately apply your knowledge. This course is based on DevOps and GenAI using .NET, Azure OpenAI and GitHub, by Trevoir Williams. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Навыки, которые вы освоите

AI SecurityResponsible AIInfrastructure as Code (IaC)AI IntegrationsGenerative AIAgentic systemsDevOpsGenerative AI AgentsAI OrchestrationCI/CDGitHubRisking.NET FrameworkAzure DevOpsEnterprise ArchitectureAgentic WorkflowsIT AutomationAI WorkflowsDevops ToolsMLOps (Machine Learning Operations)

Программа курса

7 модулей · 71 учебных материалов

01Introduction3 материалов

Navigating Your DevOps and GenAI Learning Path

IntroductionВидеоCourse Scope and ToolingВидеоIntroducing DevOps and GenAI Tools in a Team MeetingDIALOGUE
02Generative AI Concepts for DevOps8 материалов

Harnessing Generative AI in the DevOps Pipeline

Учитесь у экспертов

Packt - Course Instructors

Преподаватель курса

DevOps and GenAI using .NET, Azure OpenAI and GitHub
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Обучение на Coursera

≈ 8.8 ч

7 модулей

Язык: Английский

Часть программы вашего университета
Section OverviewВидео
How Generative AI Helps DevOps EngineersВидео
Where Generative AI Adds Value in the DevOps LifecycleВидео
AI-Assisted vs AI-Autonomous DevOpsВидео
Risk Awareness: Hallucinations, Drift, and OverreachВидео
Section ReviewВидео
Understanding AI in DevOps WorkflowsDIALOGUE
Core Generative AI Concepts in DevOpsЗадание
03Practical AI-Assisted DevOps10 материалов

Leveraging AI to Transform DevOps Workflows

Section OverviewВидеоAI-Assisted Infrastructure as Code (IaC)ВидеоDemo: AI-Assisted Infrastructure as Code (Bicep + GitHub Copilot)ВидеоDemo: Pipeline Authoring and Optimization Using AIВидеоDemo: AI for Test Strategy and Release ConfidenceВидеоDemo: AI-Assisted Release Notes AutomationВидеоDemo: AI-Assisted Incident Response and Root Cause AnalysisВидеоSection ReviewВидеоOptimizing CI/CD Pipelines with AI AssistanceDIALOGUEPractical Generative AI in DevOpsЗадание
04DevOps AI Tools, Governance, and Enterprise Readiness10 материалов

Building Smart and Secure AI-Driven DevOps Workflows

Section OverviewВидеоEnterprise AI Tooling Landscape for DevOpsВидеоReview of AI Tooling Used in DevOpsВидеоEstablishing AI Guardrails for Enterprise DevOps TeamsВидеоAuditing, Accountability, and Operational OversightВидеоCreating an AI Adoption Playbook for Your OrganizationВидеоMeasuring ROI of AI in DevOpsВидеоSection ReviewВидеоUnderstanding AI Governance in DevOpsDIALOGUEEnterprise Readiness and AI Governance for DevOpsЗадание
05Integrating Generative AI into DevOps Pipelines12 материалов

Bringing AI into the DevOps Loop: Automation, Security, and Efficiency

Section OverviewВидеоProvisioning and Connecting to an AI EngineВидеоDesigning Deterministic AI Workflow StepsВидеоOrchestrating AI Jobs in GitHub ActionsВидеоContext Engineering for DevOps AIВидеоCost and Performance Management for AI PipelinesВидеоObservability and Feedback Loops for AI-Assisted PipelinesВидеоSecure Integration Patterns (Technical Security)ВидеоAI-Augmented ChatOpsВидеоSection ReviewВидеоIntegrating AI into a CI/CD PipelineDIALOGUEIntegrating Generative AI into DevOps PipelinesЗадание
06Agentic AI for Advanced DevOps Scenarios25 материалов

Building and Managing Intelligent Agents in Modern DevOps

Section OverviewВидеоAI Agents 101: Anatomy of an AgentВидеоAgentic AI in CI/CD Pipelines (Safe and Unsafe Use Cases)ВидеоDemo: Developing a Minimal DevOps AgentВидеоDemo: Adding Minimal Agent to a GitHub WorkflowВидеоAgent Failure Modes in ProductionВидеоProgressive Autonomy Design ModelВидеоAgentic Patterns in DevOps Workflows (PRs, Builds, Incidents)ВидеоDemo: Developing a PR Code Quality Suggesting AgentВидеоDemo: Integrating Agent into PR Code Quality Assessment WorkflowВидеоMemory in Agentic Systems: What to Store and What Not to StoreВидеоDemo: Adding Workflow-Level Memory to a DevOps AgentВидеоTools and MCP: Standardizing Context and Actions Across AgentsВидеоDemo: Build an MCP Server for GitHub ToolingВидеоDemo: Extend the Agent with MCP ToolsВидеоDemo: Test and Verify the GitHub Workflow Using the MCP AgentВидеоMulti-Agent Systems for Incident ResponseВидеоDemo: Creating a Multi-Agent ImplementationВидеоDemo: Testing a Multi-Agent WorkflowВидеоObservability and Evaluation of AI AgentsВидеоDemo: Adding Observability and Evaluation to an AgentВидеоDemo: Visualizing Agent OpenTelemetry with AspireВидеоSection ReviewВидеоUnderstanding Agentic AI in DevOps WorkflowsDIALOGUEAgentic AI in Advanced DevOps ScenariosЗадание
07Conclusion3 материалов

Mastering Practical Applications of DevOps and GenAI

Conclusion and RecommendationsВидеоSummarizing DevOps and GenAI Best PracticesDIALOGUEThe DevOps and GenAI using .NET, Azure OpenAI and GitHub Final AssessmentЗадание