Development & technology · DevOps & Cloud

AI training for DevOps and Cloud Teams

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.

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

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.

All 10 courses for DevOps and Cloud Teams

Vibe & agentic coding (10)

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.

Prerequisites

Practical experience with Linux, Git and at least one cloud platform, plus a working knowledge of Terraform, containers and CI/CD.

Frequently asked questions

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.

Request without obligation

We will get back to you within one working day with a confirmation or an alternative suggestion.

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Total €949 plus VAT