Sentry VS Incoming

First, sign up for a free account at https://sentry.io. Create a new project and make note of your DSN (Data Source Name).

Using APM tools like NewRelic, Sentry, Datadog, etc to monitor the performance of your application and while you're on it, they can help you identify N+1 queries.

However, ensuring the reliability and performance of your Next.js app is equally crucial. That’s where Sentry comes into play. Combined with Sentry, an industry-leading error monitoring platform, Next.js empowers developers to proactively identify and resolve issues that may arise in their applications. In this article, we’ll explore how to integrate Sentry into your Next.js project for effective error monitoring and performance optimization.

Sentry: Error monitoring for applications, including APIs. Also offers application performance monitoring (APM).

Indeed, webapps are not immune to distribution problems. Wayward and invasive browser extensions are a clear threat, as are 3rd-party dependencies (and their dependencies) loaded at runtime. Which is why companies like https://sentry.io exist. I think the difference is that webapps are "distributable by default" and it takes real work to break this. Versus having local desktop apps which require work to distribute. A potent example of the power of defaults.

Sentry produces nothing of value? You don't value an open source error tracking and performance monitoring platform? https://github.com/getsentry/sentry

> You invent something, and then immediately turn it into a cheap commodity by releasing it for free.

Exactly. A 71-line python script https://github.com/getsentry/sentry/commit/3c2e87573d3bd16f6... was groundbreaking when it came out and the fact that it springboarded into a startup is commendable.

sentry.io: 5

Sentry - Open Source Alternative For Error Tracking

11. Sentry

This article from HoneyBadger explains most relevant topics about Rails DB transactions.

Honeybadger is a powerful error-monitoring tool for Python applications. Integrating an error monitoring service like Honeybadger into your development workflow provides numerous benefits for effectively managing exceptions. From real-time notifications and error grouping to rich diagnostics and trend analysis, Honeybadger equips you with the tools you need to quickly identify, investigate, and resolve errors and ultimately enhance the overall quality and reliability of your applications. To demo this, let's now explore some features and examples of integrating Honeybadger into your Python code.

honeybadger.io - Exception, uptime, and cron monitoring. Free for small teams and open-source projects (12,000 errors/month).

It sounds like you want to implement an exception monitoring tool like Honeybadger (my company), Sentry, or similar. They will tell you when someone encounters an error with your app, where the error occurred, and what the state of the app was (parameters, etc.) at the time of the error.

You may wonder why this is a problem. In the case of this code, we're sending the user's username to a third-party service. While username isn't inherently sensitive data, it certainly has to potential to be and should be treated as such. It's better to use IDs that can't identify the user if the third party—in this case, honeybadger—is breached. You can see the full list of supported data types, sorted by category, on the docs.

Sign up on the Honeybadger website and click on ‘start free trial’, as shown in the following image.