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Leandro Marcos
Leandro Marcos

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Creating a Credit Analysis API with Azure Functions in Java

#java #azure #serverless #cloud

🏦 Creating a Credit Analysis API with Azure Functions in Java

In this second article of our Azure Functions + Java series, you'll build a real and functional API that simulates a credit analysis, receiving client data and returning whether the credit is approved based on a randomly generated score.

📌 Didn’t read the introduction yet? Start here:

👉 Azure Functions with Java: When to Use, Pros, Limitations, and Triggers

🚀 What Are We Building?

We’re going to create an HTTP-based Azure Function that:

  • Receives a JSON payload with client name and desired amount
  • Generates a random credit score (from 0 to 1000)
  • Applies a rule: score ≥ 600 AND value ≤ 5000 = approved
  • Returns a JSON response with the result

💼 This use case is useful for:

  • Simulating a real-world credit scoring process
  • Testing microservices and APIs
  • Prototyping financial systems and flows

⚙️ Prerequisites

  • Java 17+
  • Maven
  • Azure CLI
  • Azure Function Core Tools 
 npm install -g azure-functions-core-tools@4 --unsafe-perm true
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📁 Creating the Project
Open your terminal and navigate to a folder that is not empty (e.g., C:\dev) and run:

mvn archetype:generate -DarchetypeGroupId=com.microsoft.azure -DarchetypeArtifactId=azure-functions-archetype -DgroupId=com.exemplo.fn -DartifactId=fn-analise-credito -Dversion=1.0-SNAPSHOT -Dpackage=com.exemplo.fn -DinteractiveMode=false -Darchetype.test=false
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Tip: Do not run this command inside the destination folder (e.g., fn-analise-credito), or Maven will throw an error because it expects to create the folder from scratch.

🧹 Optional: Remove Unit Test Folder

By default, the generated project includes a src/test folder with a sample unit test. If you're not using unit tests at this stage, you can delete it with the following command:

🪟 For Windows (CMD or PowerShell):

Remove-Item -Recurse -Force .\src\test
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🐧 For Linux or macOS:

rm -rf fn-analise-credito/src/test
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💡 You can run this right after generating the project. It helps to keep the structure clean for simple proof-of-concept scenarios.

✍️ Coding the Credit Analysis Function

🔧 File: Function.java

package com.exemplo.fn; import com.microsoft.azure.functions.annotation.*; import com.microsoft.azure.functions.*; import java.util.Optional; import java.util.Random; /** * Azure Function that simulates a credit analysis. */ public class Function { @FunctionName("analiseCredito") public HttpResponseMessage run( @HttpTrigger(name = "req", methods = {HttpMethod.POST}, authLevel = AuthorizationLevel.ANONYMOUS) HttpRequestMessage<Optional<String>> request, final ExecutionContext context) { String body = request.getBody().orElse(""); if (!body.contains("nome") || !body.contains("valor")) { return request.createResponseBuilder(HttpStatus.BAD_REQUEST) .body("Missing required fields: 'nome' and 'valor'") .build(); } String nome = extractValue(body, "nome"); double valor = Double.parseDouble(extractValue(body, "valor").replace(",", ".")); int score = new Random().nextInt(1001); // 0 to 1000 boolean aprovado = score >= 600 && valor <= 5000; String responseJson = String.format( "{ \"cliente\": \"%s\", \"valor\": %.2f, \"score\": %d, \"aprovado\": %s }", nome, valor, score, aprovado ); return request.createResponseBuilder(HttpStatus.OK) .header("Content-Type", "application/json") .body(responseJson) .build(); } private String extractValue(String json, String key) { String[] parts = json.replace("\"", "").replace("{", "").replace("}", "").split(","); for (String part : parts) { if (part.trim().startsWith(key)) { return part.split(":")[1].trim(); } } return ""; } }
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📥 Example Request & Response

✅ Sample Input

{ "nome": "Leandro", "valor": 3000 }
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✅ Sample Response

{ "cliente": "Leandro", "valor": 3000.00, "score": 712, "aprovado": true }
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▶️ Testing Locally

Compile and run the function:

mvn clean package mvn azure-functions:run
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Send a test request using Postman or curl:

curl -X POST "http://localhost:7071/api/analiseCredito" -H "Content-Type: application/json" -d "{ \"nome\": \"Leandro\", \"valor\": 3000 }"
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You should receive a response with score and approval decision.

✅ Final Thoughts

In this article, you created a real-world Azure Function that:

  • Parses and validates JSON input
  • Applies business logic (credit score simulation)
  • Returns a formatted and dynamic JSON response

This is a solid foundation for building:

  • APIs
  • Cloud-native services
  • Event-driven systems

The full code and instructions are available on GitHub:
👉 leandrofmarcos/fn-credit-analysis-java

📚 Next in the Series

We’ll continue exploring Azure Functions with more real use cases using Java:

  • ✅ Simulating Credit Analysis with Azure Functions in Java
  • 🔜 Queue Trigger: Processing Tasks Asynchronously with Java
  • 🔜 Blob Trigger: File Handling in Azure Storage
  • 🔜 Durable Functions with Java: Orchestrating Workflows Serverlessly
  • 🔜 Logging and Monitoring with Application Insights
  • 🔜 Best Practices for Scalable and Maintainable Functions

❤️ Enjoyed This?

Leave a ❤️, drop a comment, or share this with your team or community.
Let’s show the world that Java and Azure Functions are a powerful combo in modern serverless architectures! 💻☁️

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