Training course · Claude Code · DevOps & Cloud

Claude Code for DevOps and Cloud Teams

Agentic coding with Claude Code in the terminal and IDE: CLAUDE.md, subagents, hooks, MCP, CI pipelines and secure permissions.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Claude Code with the everyday processes of DevOps & Cloud. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Claude Code is Anthropic’s agentic coding assistant, working directly in your terminal and in popular IDEs. Rather than completing individual lines, it reads your repository, plans changes across multiple files, runs commands, executes tests and prepares commits. Over two days you will learn to use it with deliberate control: clear project instructions in CLAUDE.md, careful context management, and a workflow in which you set the direction as a developer and can trace every change the agent makes back to a clear intention.

The course is built around real engineering work: diagnosing bugs, delivering features, refactoring legacy code and filling gaps in test coverage. You will configure subagents for specialised tasks, enforce quality checks with hooks, connect external systems through the Model Context Protocol (MCP) and capture team knowledge as reusable skills. Finally, you will run Claude Code headless in CI pipelines and define permissions, sandboxing and approval rules so that its use remains defensible even in security-sensitive environments.

DevOps and cloud teams own infrastructure as code, CI/CD pipelines, monitoring, cost control and security – often across several cloud providers and on-premises environments. Much of the work is configuration in HCL, YAML and shell, troubleshooting through logs and cross-checking documentation. AI coding assistants and agents speed up exactly that: they write reusable Terraform modules, fix failing pipelines, create Ansible roles, analyse incident logs and propose cost optimisations. At the same time the stakes are high, because a single wrong command can hit production. This course teaches you to use agents productively with clear permission boundaries, plan-and-review workflows and safeguarded environments.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • DevOps engineers and platform teams
  • Cloud architects working with AWS, Azure or Google Cloud
  • Site reliability engineers responsible for operations and incidents
  • System administrators moving towards infrastructure as code
  • Developers who maintain their own CI/CD pipelines

Typical challenges we address

  • Growing volumes of Terraform, YAML and pipeline configuration with drift and duplication
  • Time-consuming troubleshooting of failing pipelines and distributed logs
  • Rising cloud costs without clear visibility
  • High demands on security, compliance and traceability of changes

What you will be able to do

  • You use Claude Code for multi-step development tasks while keeping full control over every change.
  • You maintain a CLAUDE.md that effectively conveys project conventions, commands and architectural guidance to the agent.
  • You extend Claude Code with subagents, hooks, MCP servers and skills tailored to your team.
  • You integrate Claude Code into Git workflows and CI pipelines with traceable, test-backed results.
  • Use AI agents safely for infrastructure as code, pipelines and configuration management.
  • Analyse incidents, pipeline failures and cloud costs faster with AI support.
  • Define permission boundaries and approval processes so agents cannot make uncontrolled changes to production.

Course outline

Day 1

Module 1 How Claude Code works
  • Installation, sign-in and use in the terminal, VS Code and JetBrains IDEs
  • Understanding the agentic loop: read, plan, act, verify
  • Using plan mode to agree on an approach before any code changes
  • Writing effective task briefs with goal, context and acceptance criteria
Module 2 Project context with CLAUDE.md and context management
  • Structuring CLAUDE.md at project, directory and user level
  • Documenting build, test and style conventions so the agent follows them reliably
  • Managing the context window with targeted file references, compaction and fresh sessions
  • Resuming sessions and breaking long tasks into manageable stages
Module 3 Extending Claude Code with subagents, hooks, MCP and skills
  • Defining subagents for code review, research or test generation
  • Using hooks to enforce formatting, linting or checks before and after tool calls
  • Connecting MCP servers for issue trackers, databases or internal documentation
  • Creating custom slash commands and skills for recurring team workflows
Module 4 Git workflows, testing and quality assurance
  • Creating branches, meaningful commits and pull requests with Claude Code
  • Test-first work: have tests written before the implementation
  • Reviewing diffs systematically and rejecting or refining changes
  • Organising parallel work with Git worktrees and multiple sessions

Day 2

Module 5 Headless operation, CI and security
  • Running Claude Code non-interactively in scripts and CI pipelines
  • Automated reviews and issue handling in GitHub or GitLab workflows
  • Configuring permission modes, allow and deny rules, and sandboxing
  • Handling secrets, prompt injection risks and organisation-wide policies
Module 6 Practice lab: DevOps & Cloud
  • Developing Terraform modules
  • Fixing CI/CD pipelines
  • Ansible and configuration management
  • Incident analysis
  • Optimising cloud costs
  • Policy as code and hardening
Module 7 Data protection, quality & transfer to daily work
  • Agents with access to cloud accounts and pipelines are a security matter: work with least privilege, separate environments and human approval, and keep cloud credentials, state files and secrets out of prompts. Operators of essential and important services must also meet NIS2 requirements on risk management, supply-chain security and traceability of changes.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Developing Terraform modules

The agent creates reusable Terraform or OpenTofu modules with variables, validations and outputs, runs fmt, validate and plan, and explains every planned change before a human approves the apply.

Fixing CI/CD pipelines

Failed GitHub Actions, GitLab CI or Azure DevOps runs are analysed from their logs, root causes such as caching issues or missing permissions identified and corrected pipeline definitions proposed.

Ansible and configuration management

The AI writes idempotent Ansible roles, templates and inventories, replaces fragile shell scripts and adds Molecule tests so configuration stays reproducible. Existing roles are gradually standardised along the way.

Incident analysis

Logs, metrics and alerts from monitoring are brought together, a timeline reconstructed, likely causes narrowed down and a draft postmortem with actions produced. The team keeps the final judgement.

Optimising cloud costs

The assistant reviews cost reports and resource definitions, finds oversized instances, orphaned volumes or missing lifecycle rules and drafts the matching IaC changes. Each recommendation includes estimated savings.

Policy as code and hardening

IaC code is scanned with tools such as Checkov or tfsec, findings are fixed and rules for encryption, tagging or network access are expressed as policy as code.

Possible hands-on projects

Drift detector

A script that regularly runs terraform plan across several environments, detects drift and posts a summary to a chat channel.

Pipeline template library

Reusable CI/CD templates for build, test, security scanning and deployment, documented and accompanied by sample projects. Teams adopt them with just a few lines of configuration.

Cost report tool

A CLI that pulls cost data from a cloud account, breaks it down by tags and teams and clearly highlights optimisation candidates.

Prerequisites

You have hands-on programming experience in at least one language and are comfortable with Git and the command line. Practical experience with Linux, Git and at least one cloud platform, plus a working knowledge of Terraform, containers and CI/CD.

Technical requirements

Your own laptop with admin rights, Git, a Node.js runtime and an up-to-date editor; a Claude subscription or Anthropic API access is required for the exercises.

Data protection & compliance

Agents with access to cloud accounts and pipelines are a security matter: work with least privilege, separate environments and human approval, and keep cloud credentials, state files and secrets out of prompts. Operators of essential and important services must also meet NIS2 requirements on risk management, supply-chain security and traceability of changes.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Thu, 3 December 2026 – Fri, 4 December 2026 Munich Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Online Request
  • Mon, 14 December 2026 – Tue, 15 December 2026 Stuttgart Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Hanover Request
  • Mon, 25 January 2027 – Tue, 26 January 2027 Online Request

Frequently asked questions

How is Claude Code different from traditional code completion?

Code completion suggests the next few lines, whereas Claude Code acts as an agent that handles whole tasks: it searches the repository, plans changes across several files, runs tests and commands, and corrects itself based on the results. You define the goal and review the outcome instead of steering every single line yourself.

Is Claude Code secure enough for enterprise use?

By default, Claude Code asks for approval before editing files or running commands. Permission rules, sandboxing, managed settings and hooks let you define precisely what the agent may do. During the course you learn to configure these mechanisms to match your security and data protection requirements and to assess risks such as prompt injection.

Does Claude Code work with my language and tech stack?

Yes. Claude Code is language-agnostic because it works with files, terminal commands and your existing build and test tooling. Whether you use Python, Java, TypeScript, Go, SAP-related code or infrastructure as code, what matters most is a well-written CLAUDE.md describing your commands and conventions. Each course variant adds the relevant domain focus.

Should an AI agent be allowed to apply infrastructure changes itself?

That is something to limit deliberately. A proven workflow has the agent write code and run plan, a human review the result and the apply run through the regular pipeline. On the course you learn to design permissions, sandbox environments and approvals so that production systems stay protected.

Which cloud platform does the course use?

The methods are vendor-neutral and transfer to AWS, Azure and Google Cloud. Exercises use examples you can reproduce with local tooling or test accounts. You are welcome to bring scenarios from your own platform, provided no production credentials are used.

How much does “Claude Code for DevOps and Cloud Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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