Welcome to the next module on designing a compute solution. In traditional on-premises environments, deployments often depend on virtual machines or containers, which can limit your flexibility. In contrast, cloud platforms like Microsoft Azure provide a broader range of options through Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). The right compute solution for your project depends on your application requirements. Whether you’re migrating an existing application to the cloud or building a new one from scratch, you will need to weigh factors such as a need for serverless architecture, containerization, or full control over the operating system. In this module, we will review various compute service options and follow a decision-making flowchart to help you select the optimal solution for your application. Consider the following scenario: Vendata Corp intends to deploy a three-tier application on Azure with these specific requirements:Documentation Index
Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
Use this file to discover all available pages before exploring further.
- Two web applications, “API” and “API Customer,” each requiring custom domains and Azure AD authentication.
- Source code stored in GitHub, with automatic updates triggered by commits to the master branch.
- A focus on core development by Vendata Developers, with Microsoft managing the underlying infrastructure.
- A business logic tier that handles requests from both web applications, listening on a custom port (8080) and necessitating load balancing.
- Custom-built business logic that requires managing the operating system and server dependencies.
- A data tier operating on SQL containers for simplified management, supported by a managed container orchestrator to oversee these SQL containers.
Below is a quick recap emphasizing the placement of load balancers for the front-end and mid-tier components.
