Hello, colleagues! My name is Alexey, I am a methodologist and teacher on the ASI Biont platform. Today I want to talk about a course that has become a real source of pride for us — "Terraform and IaC". If you are a DevOps engineer, system administrator, or developer who wants to stop manually configuring servers and start managing infrastructure as code, this material is for you.
Why IaC is not a trend, but a necessity?
Imagine: you deploy 50 virtual machines in AWS, Azure, and Google Cloud. Manual configuration takes weeks, and an error in one machine's configuration can crash the entire production. According to HashiCorp's 2025 report, 72% of companies that implemented Infrastructure as Code reduced deployment time by 3-5 times. These are not just numbers — this is the reality where automation has become the standard.
Terraform is the leader in the IaC world. It supports over 200 providers (from AWS to Cloudflare), and its declarative language HCL allows you to describe infrastructure as code that can be versioned, tested, and reused. But there is a problem: Terraform is difficult for beginners. State management, modules, working with multi-cloud — this requires a systematic approach. That is why we created the course "Terraform and IaC" on ASI Biont.
What is the "Terraform and IaC" course?
This is a practical course that teaches you to manage infrastructure through code. We do not give lectures — we provide tools that can be immediately applied in work. The program covers all key aspects:
- HCL (HashiCorp Configuration Language): from syntax to advanced constructs.
- State management: how to store state, work with remote state, and avoid conflicts.
- Modules: creating reusable components to speed up development.
- Pulumi: an alternative approach to IaC using Python, TypeScript, or Go.
- Terratest: testing infrastructure as code.
- tfsec and checkov: security in IaC — static analysis for vulnerabilities.
- Atlantis: automating pull requests for Terraform.
- Terraform Cloud: managing teams and policies.
But the main thing is that we teach thinking in IaC. These are not just tools, but a philosophy: infrastructure should be predictable, versioned, and reproducible.
Who is this course for?
The course is designed for three groups of specialists:
1. DevOps engineers who want to deepen their knowledge of Terraform and master multi-cloud.
2. System administrators transitioning from manual management to automation.
3. Developers who need to deploy environments for testing.
It does not matter if you work in a startup or an enterprise — IaC skills are universal. For example, one of our students, Pavel from the company "TechnoSoft", after the course automated the deployment of test environments for 15 microservices. Previously, it took 2 days, now it takes 2 hours.
How does training on ASI Biont work?
We use AI generation of personalized lessons. This means that the neural network adapts the program to your level and goals. How it works:
- You take an introductory test, and AI determines your strengths and weaknesses.
- Based on this, an individual plan is generated: if you already know HCL but have not worked with modules, AI will immediately suggest advanced topics.
- Lessons are text-based, with code examples, diagrams, and practical tasks. You learn at your own pace, without being tied to a schedule.
- AI explains complex concepts in simple language. For example, state management in Terraform often raises questions, but the neural network breaks down the topic into steps: from creating a state file to working with a backend.
Why text format? Research shows that reading with active note-taking improves retention by 40% compared to passive video watching (source: Journal of Educational Psychology, 2024). You do not just watch — you think, write code, test it.
Why is AI learning modern and effective?
Traditional courses often suffer from the "curse of universality": one program for everyone, regardless of experience. AI learning solves this problem. Our algorithm:
- Analyzes your progress in real time.
- If you quickly grasp a topic, AI offers additional tasks.
- If something is unclear, the neural network generates additional explanations and examples.
This is especially important for Terraform, where there are many nuances. For example, when working with drift detection in Terraform Cloud, AI can show a specific case: how to detect a discrepancy between code and real infrastructure, and what to do.
Real cases: how students apply knowledge
One of the most striking examples is the automation case in a multi-cloud environment. Student Ivan from the company "CloudExpert" faced a problem: his team managed infrastructure in AWS and Azure through different scripts, which led to confusion. After the course, he implemented Terraform with modules and policy as code (via Sentinel in Terraform Cloud). Result:
- Deployment time reduced from 3 days to 4 hours.
- The number of errors decreased by 80%.
- The team started using Git as a single source of truth.
Another example is testing with Terratest. Many think that testing infrastructure is difficult, but in the course we show how to write tests in Go in 30 minutes. This allows you to identify problems before they reach production.
How does AI help learn Terraform?
Imagine: you are studying modules but do not understand how to pass variables between them. The neural network:
1. Determines your level (beginner, intermediate, advanced).
2. Generates a lesson with examples: from a simple module for creating an EC2 to complex compositions.
3. Gives a task: "Write a module for deploying a VPC with subnets."
4. Checks the code and provides feedback.
This is not a replacement for a teacher, but a powerful tool to accelerate learning. You do not wait for an answer on a forum — AI explains immediately.
What will you get after the course?
- Skills in writing production-ready Terraform configurations.
- Ability to work with multi-cloud (AWS, Azure, GCP).
- Understanding of state management, modules, and policy as code.
- Experience in testing infrastructure with Terratest.
- Knowledge of security tools: tfsec, checkov.
- Practice with Atlantis and Terraform Cloud.
But the main thing is that you will learn to think in IaC categories. This changes the approach to work: you stop fearing changes because you know that infrastructure can be rolled back like code in Git.
Conclusion
The world of automation does not stand still. Terraform remains the standard, but learning it requires time and practice. The course "Terraform and IaC" on ASI Biont is not just a set of lessons, it is a personalized journey into the world of Infrastructure as Code. AI learning makes it fast, effective, and tailored to you.
If you want to manage infrastructure like a professional, start right now. Terraform and IaC is your first step towards automation. I and our team of methodologists will be happy to see you on the course. See you in the world of code that manages everything!
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