In this module, we will explore the process of deploying container apps using YAML configuration files, similar to Kubernetes deployment. You'll get hands-on experience with creating, configuring, and exporting YAML files for your container apps, enabling easier management and scalability.

In this module, we will introduce the concept of jobs within Azure Container Apps, including manual, scheduled, and event-driven jobs. You will learn how to create and execute jobs to automate and manage containerized workloads efficiently.

In this module, we will dive into Kubernetes Event-Driven Autoscaling (KEDA) and how it optimizes container app scaling. You'll learn to configure KEDA scalers, create autoscaling jobs, and manage resources for a responsive, scalable container environment.

In this module, we will explore how to securely manage secrets in container apps using Azure Key Vault. You will learn how to create, store, and access sensitive information, ensuring that your app remains secure in the cloud.

In this module, we will explore how to use revisions to manage container app updates and split traffic between versions. You'll learn how to deploy new versions of your apps with minimal disruption, ensuring smooth transitions and optimal performance.

In this module, we will cover the tools and methods for logging and troubleshooting in Azure Container Apps. You'll learn how to set up logging, diagnose problems, and use Grafana dashboards for deep insights into your container application’s health.

In this module, we will guide you through a hands-on lab where you'll build and deploy both frontend and backend applications to Azure Container Apps. This practical experience will solidify your understanding of container app deployment and integration.

In this module, we will explore the use of Managed Identity (MI) for secure communication in Azure. You'll learn to configure MI, create a container registry, and build and deploy both frontend and backend applications with secure access.

In this module, we will explore various storage options for Azure Container Apps, from temporary ephemeral storage to long-term persistent storage using Azure File Share. You'll learn to manage and configure storage solutions based on your app’s data needs.

In this module, we will guide you through the steps of configuring custom domain names for your Azure Container Apps. You’ll learn how to personalize your web presence and improve brand recognition by following a hands-on demonstration.

In this module, we will introduce workload profiles and explain their role in optimizing the performance and resource management of Azure Container Apps. You will learn how to configure these profiles to ensure efficient performance of your containerized workloads.

In this module, we will focus on configuring custom domains with a free managed certificate, enabling secure connections for your Azure Container Apps. You'll learn how to ensure SSL/TLS encryption, providing safe and reliable access to your applications.

In this module, we will explore networking and infrastructure options for Azure Container Apps, focusing on secure communication. You will learn how to implement App Gateway and HTTPS for enhanced security, alongside the use of TLS certificates for encrypted traffic.

In this module, we will introduce private endpoints and demonstrate how they ensure secure communication between your Azure Container Apps and other Azure resources. You will learn how to configure these endpoints for maximum security and privacy in your application architecture.

In this module, we will delve into the networking stack for Azure Container Apps, including containers, services, and ingress IPs. You will gain insights into how these components work together to optimize communication and secure your applications.

In this module, we will explore the Service Connector, a powerful feature for enabling seamless communication between Azure services and container apps. You’ll learn to use the Service Connector to link your containerized applications with Azure Storage Blob and other services.

In this module, we will guide you through using Azure Container Registry (ACR) in conjunction with ABAC to manage image access for multiple container applications. You’ll gain the skills to automate and secure image management processes across your containerized apps.

In this module, we will cover the essentials of GitHub Actions for CI/CD pipelines. You will learn to automate the deployment of your containerized applications using YAML pipelines, with a live demo showcasing the process.

In this module, we will focus on using Azure DevOps pipelines for deploying containerized applications to Azure Container Apps. You’ll gain hands-on experience in setting up and configuring CI/CD pipelines for automation and deployment.

In this module, we will demonstrate how to use Azure CLI to create and deploy container applications to Azure. You will explore the process of managing both frontend and backend deployments using simple CLI commands.

In this module, we will cover the Bicep language for infrastructure as code (IaC) and demonstrate how to deploy container apps using Bicep. You will also learn how to deploy multiple container apps using Bicep’s easy-to-read syntax.

In this module, we will guide you through using Terraform to deploy containerized applications to Azure. You’ll learn how to automate the deployment of both backend and frontend apps using Terraform for efficient infrastructure management.

In this module, we will dive into the concept of landing zones and demonstrate how to deploy them using both Bicep and Terraform. You will learn how to create secure, scalable infrastructure for your container apps.

In this module, we will explore the limitations of private domain names in Azure Container Apps and show you how to work within these constraints to configure secure internal communication for your containerized applications.

In this module, we will demonstrate how to run the Deepseek R1 model in Azure Container Apps, showcasing the use of containerized large language models (LLMs) for AI workloads. You will learn how to deploy and optimize AI models within containerized environments.