Writing tests is essential for ensuring the quality of your code. Discover the difference between code coverage and test coverage and how to use them to make your testing process more efficient and effective.
AI code assistants are changing how developers debug production errors, but they need context to be useful. Learn how to build a custom GitHub Copilot agent that connects directly to your error tracking tool.
The Ruby 4.0 release marks the 30th birthday of the language! Read on to understand everything that's changed in Ruby 4, and how to upgrade with the least friction.
Learn how to use Rails Action Cable without Redis! Follow along and build a Solid Cable application with real-time features.
Did you miss it? This year we shipped new APM dashboards, real-time alerts for metrics and logs, EU data residency, an MCP server for your AI assistants, and so much more.
Choosing between Heroku's simplicity and Kubernetes flexibility impacts your team's developer productivity and operational costs. This Kubernetes comparison examines architecture differences, scaling capabilities, security concerns, and real-world use cases to help DevOps teams select the right platform for deployment.
Python integration testing is an essential step in preparing your application for deployment, but are you getting the most from your testing? Learn how Honeybadger can help you detect and fix problems before they impact your users.
Errors happen in every application. Devs have to decide: do you write code to handle the error? Suppress it? Notify the user? Report it to the team? In this article, Ayo Isaiah walks us through every aspect of the JavaScript error system. He'll show us how to work with errors and discuss appropriate choices for real-world scenarios.
Django’s built-in test framework makes it easy to validate complete workflows like signup, login, and image uploads. This guide walks through real integration tests for authentication and external services, plus best practices for managing data and mocks.
Legacy APMs somehow manage to be both too much and too little—overwhelming you with dashboards and data while failing to answer the questions that matter when production breaks. There's a better way.