Systems | Development | Analytics | API | Testing

Debugging Without a Net: The Pain of Reproducing Production Issues

Every engineer has been there — a late-night page, a broken feature in production, and no clear way to reproduce it. The logs are vague. The metrics look normal. Your local environment works fine. Yet something somewhere is failing for real users. So begins the detective work — debugging a live system with almost no tools, no perfect test data, and no clone of production.

Advanced Debugging in Elixir with IO.inspect

When writing Elixir, most developers quickly get familiar with IO.inspect as a quick way to see what's happening inside their code. But what many overlook is that IO.inspect is far more powerful than just a method that prints a variable to the console. In fact, with the right options and placement, IO.inspect can become a precise, highly targeted debugging tool, one that doesn't interrupt your program flow and works seamlessly with Elixir's functional pipelines.

Make Your Debugging Workflow Smarter, Faster with BugSnag and SmartBear MCP

Tired of wasting hours triaging errors and digging through logs? With BugSnag from SmartBear and GitHub Copilot, you can now debug faster : AI surfaces the root cause, explains the issue, and helps you fix it – all from your IDE. Powered by SmartBear’s integration with the Model Context Protocol (MCP), and bringing runtime context into your development tools, errors from BugSnag are automatically enriched with the technical metadata your LLM needs to deliver accurate, relevant suggestions.

Stop guessing! Speedscale's Notebook finds anything in your traffic.

Debugging complex microservices just got an upgrade. This video demonstrates Speedscale's innovative Notebook capability, allowing you to perform advanced substring searches and filter production traffic based on deeply nested JSON fields within request and response bodies. Unlike traditional observability tools that only record telemetry, Speedscale's always-on recorder captures full traffic payloads, empowering you to precisely pinpoint issues, identify specific user calls, or validate API versions. Streamline your troubleshooting, enhance your testing, and gain unprecedented visibility into your production environment.

Debugger in Kong Konnect

Are you spending too much time trying to track down failing requests or figure out performance issues within your Kong API Gateway? In this quick demo, we show you how to use Konnect's Debugger to save hours of debugging time by rapidly finding the root cause of latency and other issues. You'll learn how Debugger allows you to set up deep tracing sessions for your Kong data planes, collecting OpenTelemetry-compatible traces across the entire request and response lifecycle. We will walk you through a real-world scenario where we diagnose a spike in latency for a specific service.

Introducing Konnect Debugger: Get Unprecedented API Traffic Visibility

We're excited to announce the general availability of Konnect Debugger, formerly known as Active Tracing during its tech preview phase. This powerful debugging and observability solution in Kong Konnect has evolved from a focused tracing tool into a comprehensive debugging platform.

Beyond console.log: Smarter Debugging with Modern JavaScript Tooling

Ask any JavaScript developer their most used debugging tool and chances are the answer will be console.log. It’s immediate, low friction, and available in every browser. For development, it’s fantastic. But for production and complex applications, if you rely on console.log alone, cracks begin to show. It lacks context, doesn’t persist, and makes reproducing or analyzing user-reported issues a challenge. In this article, we’ll look at smarter, scalable debugging strategies.