How to Implement Sentry in a NestJS Project

Sentry is an essential tool for monitoring errors and performance in applications. It automatically captures and reports exceptions, in addition to allowing performance tracking and code profiling. In this article, we'll explore how to configure and use Sentry in a NestJS project.

1. Installing Sentry

First, you need to add the necessary dependencies to your NestJS project. Run the following command:

npm install @sentry/nestjs @sentry/profiling-node

2. Configuring Sentry

After installing the dependencies, configure Sentry in your project. Create a file for Sentry settings, for example, sentry.config.ts, and add the following code:

import * as Sentry from '@sentry/nestjs';
import { nodeProfilingIntegration } from '@sentry/profiling-node';

Sentry.init({
  dsn: process.env.SENTRY_DSN,  // Adicione sua DSN do Sentry aqui
  integrations: [nodeProfilingIntegration()],
  tracesSampleRate: 1.0,  // Captura 100% das transações para monitoramento de performance
  profilesSampleRate: 1.0,  // Define a taxa de amostragem para profiling de código
});

*3. Integrating Sentry into Application Launch
*
Now, you need to integrate Sentry into your application startup. In the main startup file (main.ts), configure Sentry to catch and report exceptions as shown below:

import '../src/config/sentry';  // Importa a configuração do Sentry
import {
  BaseExceptionFilter,
  HttpAdapterHost,
  NestFactory,
} from '@nestjs/core';
import { AppModule } from './app.module';
import * as Sentry from '@sentry/nestjs';

async function bootstrap() {
  const app = await NestFactory.create(AppModule, { rawBody: true });

  // Configurando o Sentry para capturar e relatar exceções
  const { httpAdapter } = app.get(HttpAdapterHost);
  Sentry.setupNestErrorHandler(app, new BaseExceptionFilter(httpAdapter));

  await app.listen(3000);
}
bootstrap();

Conclusion

With these settings, Sentry is now integrated into your NestJS project, monitoring errors, exceptions and application performance. This can be crucial for identifying and resolving issues quickly, ensuring a more stable and predictable user experience.

Remember to adjust sampling rates according to the environment and application criticality to avoid unnecessary overhead.

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