Learn by Building

Hands-On Training: Build Azure Infrastructure with Terraform

Terraform for Beginners:: Automate and Manage Real Azure Environments Using Terraform

This course, titled Hands-On Training: Build and Automate Azure Infrastructure with Terraform, is designed for individuals ranging from Beginner to Intermediate who want to master Infrastructure-as-Code (IaC) principles on the Microsoft Azure platform. It provides a logical and structured path to take a new learner from "I've never used Terraform" to being able to confidently deploy and secure real Azure infrastructure using best practices. The training begins with Section 1: Getting Started with Terraform on Azure, where you will receive a complete introduction to Terraform, covering core concepts of IaC, its architecture, and the full lifecycle workflow of init, plan, apply, and destroy. You will set up your development environment by installing Terraform and configuring Visual Studio Code, defining the Azure provider, and securely authenticating to Azure using a Service Principal. In Section 2: Building a Complete Azure Infrastructure with Terraform, the course transitions into a comprehensive, project-based deployment. Students will build a fully working, full-stack Azure environment from the ground up, provisioning foundational elements like resource groups, storage accounts, virtual networks, and subnets. You will then move on to deploy and configure more complex resources, including public IPs, network interfaces, Network Security Groups (NSGs) for traffic control, and virtual machines (for Kafka and Flask applications), before automating the creation of an Azure Databricks workspace. This section transforms static cloud setup into repeatable, automated Terraform workflows and includes essential troubleshooting skills. Section 3: Automating Azure Infrastructure with Terraform Loops elevates your skills by showing you how to optimize and scale the infrastructure built in the previous section. You will learn to replace repetitive configurations with elegant, reusable patterns by mastering Terraform's looping constructs, specifically for_each and dynamic blocks. This section focuses on refactoring resource creation—like multiple Network Security Groups, Public IPs, and Virtual Machines—from separate blocks into concise, data-driven code, teaching you how to maintain clean and scalable infrastructure definitions. Finally, Section 4: Terraform Best Practices—Variables, State & Security prepares you for professional, real-world DevOps environments. You will learn how to set up and use Azure Cloud Shell, properly organize your projects, and remove sensitive credentials by utilizing environment variables. A major focus is on the security and collaboration aspects of state management: understanding Terraform's state file and moving it to Azure Storage for secure, shared access and reliability. The section concludes by implementing production-level security, replacing hard-coded passwords with SSH key-based authentication for your Azure Virtual Machines. The course emphasizes Hands-On Practice and uses industry-relevant tools, ensuring students are prepared for entry-level DevOps or Cloud Engineer roles focused on Azure and Terraform.

Hands-On Training: Streaming Data with Apache Kafka on Azure

Most Apache Kafka courses explain concepts but never show how to build a complete real-world streaming system. In this course, you will build a real-time data streaming pipeline from scratch using Apache Kafka on Microsoft Azure. Through practical, hands-on exercises, you will learn how to install, configure, and run Kafka in a cloud environment while implementing real data streaming scenarios. This course focuses on learning by doing. Instead of only studying theory, you will deploy Kafka on Azure virtual machines, produce and consume streaming data using Python, and integrate your pipeline with Azure services such as Azure Data Lake and Azure Databricks. By the end of the course, you will understand how real-time streaming architectures are built and how Apache Kafka is used in modern data engineering platforms. What You Will Learn Apache Kafka Fundamentals Understand the architecture of Kafka, including brokers, topics, partitions, producers, and consumers. Deploying Kafka on Azure Learn how to create and configure Azure infrastructure to run Kafka clusters on virtual machines. Hands-On Kafka Installation and Configuration Install and configure Kafka and Zookeeper step-by-step and understand how they work together. Building Real-Time Streaming Pipelines Create streaming data workflows using Python producers and consumers. Integration with Azure Data Platform Stream data to Azure Data Lake and process it using Azure Databricks and Delta Tables. End-to-End Streaming Project Implement and run multiple real-world scenarios demonstrating how Kafka supports scalable real-time data processing. Why Take This Course? This course is designed around practical implementation, not just theoretical explanations. You will: • Deploy Apache Kafka in a real cloud environment • Build a complete streaming pipeline from producer to analytics • Work with industry tools such as Python, Azure Databricks, Delta Tables, and Data Lakes • Understand how streaming architectures are implemented in real-world projects By the end of the course, you will have built and tested a full streaming data architecture using Apache Kafka on Azure. Who This Course Is For This course is ideal for: • Aspiring Data Engineers who want hands-on experience with streaming technologies • Developers interested in real-time data processing and event-driven architectures • Cloud engineers working with Azure and modern data platforms • Anyone who wants to understand how Apache Kafka works in real-world data engineering scenarios