This video demonstrates deploying an 8-microservice e-commerce app (using MySQL, MongoDB, and Redis) onto an AKS cluster. It covers architecture, containerization, Kubernetes manifests, Helm charts, and ingress configuration for external access. The app, a forked IBM project, showcases various programming languages and database technologies. This segment provides a concise walkthrough of the e-commerce application's functionality, including user registration, product browsing, adding items to the cart, and the checkout process. The description highlights the application's features and its purpose as a learning tool for understanding e-commerce application development. This segment details the first three microservices of the e-commerce application: the user microservice (handling registration and login), the catalog microservice (managing product information), and the cart microservice (managing shopping carts). The explanation clearly outlines the function of each service and its interaction with other parts of the system. This segment continues the explanation of the e-commerce application's microservices, covering the shipping, payment, dispatch, and web microservices. It clarifies the role of each service in the overall workflow and justifies the choice of a microservice architecture. The presenter then verifies the identified microservices by referencing the application's source code. This segment explains the rationale behind using both MySQL and MongoDB databases in the application. The presenter justifies the use of MySQL for storing images and MongoDB for user data, highlighting the advantages of using different database types for different data structures. The discussion also addresses the potential alternative of using a single database with multiple tables. This segment focuses on the ratings microservice and explains the use of Redis, an in-memory data store, for managing product ratings. The presenter justifies the choice of Redis over a traditional database due to the dynamic nature of ratings and the need for fast retrieval of information. The explanation highlights the performance benefits of using an in-memory data store for frequently accessed and updated data. This segment explains why Redis, an in-memory datastore, is implemented as a StatefulSet with a persistent volume in a Kubernetes environment. It highlights the ephemeral nature of Kubernetes pods and the importance of data persistence to prevent data loss when pods are recreated. The explanation covers how persistent volumes ensure data is preserved across pod restarts, maintaining the application's state. This segment provides a practical, step-by-step approach to containerizing microservices using Dockerfiles. It focuses on the process of creating Dockerfiles for different programming languages (Node.js, Python), emphasizing the importance of understanding the application's entry point and commands. The explanation also addresses handling dependencies and working directories within the Dockerfile context. This segment delves into best practices for writing Dockerfiles, particularly focusing on managing dependencies across different programming languages (Node.js, Python). It draws parallels between dependency management tools like `package.json`, `requirements.txt`, and `pom.xml`, illustrating how similar steps are followed regardless of the programming language. The discussion also touches upon potential anti-patterns to avoid. This segment showcases the use of multi-stage Docker builds to optimize image sizes. It uses the example of a Java application, explaining how to separate the build process (with its dependencies) from the runtime environment, resulting in a smaller, more efficient container image. The presenter also references a related video for further learning. This segment introduces Helm charts as a superior alternative to managing multiple Kubernetes YAML manifests across different environments. It explains the advantages of using Helm charts for managing configuration parameters dynamically across various environments (dev, staging, prod), simplifying the deployment process and reducing complexity.This segment provides a detailed explanation of the structure of a Helm chart, focusing on the `templates` and `values.yaml` files. It demonstrates how to use the templating engine to manage dynamic parameters within the YAML manifests, allowing for environment-specific configurations without modifying the core templates. The explanation includes a practical example of how dynamic values are substituted into the deployment files. This segment details the process of cloning a GitHub repository containing a three-tier architecture project, navigating to the project directory, and preparing the local environment for Kubernetes cluster connection. The speaker provides clear instructions, including commands and folder names, making it easy for viewers to replicate the steps. This segment focuses on the intricacies of StatefulSets and Persistent Volume Claims (PVCs) within Kubernetes. The speaker explains the importance of parameters like access mode, storage class, and file mode in PVCs, particularly within the context of stateful applications. The explanation of how PVCs interact with storage classes and CSI drivers is particularly valuable. This segment demonstrates how to connect a local terminal to a Kubernetes cluster using the `aks get-credentials` command. The speaker explains the command's parameters, including resource group and cluster names, and verifies the connection using `kubectl get pods`. This provides a practical guide for establishing a connection to a remote Kubernetes cluster. This segment delves into the selection of appropriate storage classes (Azure Disks and Azure Files) within an AKS environment. The speaker clarifies the distinctions between these storage types and provides guidance on choosing the optimal storage class based on application requirements (single-pod access vs. shared storage across multiple pods/nodes). This segment explains the importance of ingress controllers for enabling external access to microservices running within a Kubernetes cluster. The speaker contrasts the use of load balancers with ingress controllers, highlighting the additional capabilities offered by ingress controllers (e.g., web application firewall, path-based routing). The instructions for enabling the ingress controller in AKS are straightforward. This segment demonstrates the creation and application of an Ingress YAML file to route external traffic to the deployed microservices. The speaker explains key parameters within the YAML file, including namespace, service name, port, and ingress class name. The discussion of ingress class names and their importance in multi-team environments is particularly insightful.