I'm learning Azure and understand what many services do individually, but I still struggle to decide which ones belong in an actual solution. For example, a project might need data storage, data processing, an API, and application monitoring, yet several Azure services could satisfy each requirement. How do experienced developers and architects make these choices? Do you use a particular checklist, decision-making process, or architecture pattern? I'm especially interested in how you balance technical fit, scalability, complexity, and cost.
4 Answers
Treat it as a requirements-matching exercise. Write down what each part of the application needs to do, then compare candidate services against those needs, including pricing and how much maintenance they require. For learning or personal projects, cost can be the deciding factor, so services that scale down or have useful free tiers may be preferable. A small sandbox project is a good way to gain practical experience with different services.
A lot of this skill comes from studying architectures, experimenting, and seeing how different designs behave in production. Learn what problem each service solves, when it is a poor fit, and what its limits and pricing model look like. Then make the simplest choice that satisfies the current requirements. Avoid forcing an early decision forever—requirements change, and switching to a better-fitting service is usually easier earlier in development.
There isn’t one universal answer—it depends on the workload. Start by defining the requirements: data shape, read/write patterns, expected scale, availability, latency, security, operational effort, and budget. For example, simple key-value data might fit Table Storage, relational structured data could point to Azure SQL or PostgreSQL, and flexible JSON documents might suit Cosmos DB. Compare the trade-offs instead of choosing based only on the service’s popularity. Early in a project, it’s also fine to test a couple of options and change direction before the decision becomes expensive.
Think about the whole solution rather than selecting isolated services. A typical web application might combine a web app or container, an API layer, a database, object storage or a data lake, background processing, and Application Insights. The right combination depends on throughput, scaling requirements, reliability goals, and budget. Serverless options can be attractive when you want low idle costs, while managed platforms reduce the amount of infrastructure you have to operate.

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