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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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