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If you're building a Next.js application that has AI capabilities inside it, Agent Monitoring helps put all the AI context with the rest of the data inside Sentry. Correlating tool call duration with database performance and token consumption helps debug in full-stack context.

Adding additional information to issues captured in Sentry can help you identify and prioritize your most critical issues. Logs and Metrics help build context around the error and understand correlation and causation all in one place due to everything being trace connected.

Session Replay lets you see how your users experienced your Next.js application before a crash happened. Aside from how the user used your app, it also captures the console output of the browser, the network requests, and the memory snapshot, so you get all the information needed to debug the issue. In this video you’ll learn how to use Session Replay and implement it in your Next.js application.

Seer is Sentry's AI Debugging agent that has access to all the context that Sentry pulls together from your applications. Sometimes it shows up predicting bugs before they ship to prod. Sometimes it's catching issues in prod and bringing you the fix. Seer pulls from distributed traces, logs, profiles, stack traces, errors, and your codebase, and helps you find the broken parts of your application and fix them faster.

Setting up Sentry is literally one CLI command. This video walks you through how to create a new Next.js project on Sentry, how to install Sentry into that project, and how to trigger and monitor your first error.

Configuring source maps for your Next.js application with a Sentry project gives you detailed information about where performance issues and errors are triggered in your code, making it faster to debug and resolve issues.

Set up a Log Drain from Vercel and monitor all of your application data in Sentry. We'll take a quick look at how to set up a Log Drain, and show you two quick examples of how they can be used.

Stack traces tell you what broke. They rarely tell you why. In this video, Serge walks through a real Next.js production bug that only affected Firefox and Safari. The error showed up clearly in Sentry, but the stack trace alone wasn’t enough to explain what was going wrong. The missing piece turned out to be logs. You’ll see how adding logs to a Next.js API route exposed unexpected request data, how those logs connected back to traces, and how that context made the root cause obvious and easy to fix.

Aggregate and query logs on Sentry. Add logs to your errors, errors to not only make debugging easier, but also give valuable context to Seer AI. Logs help you and Seer better understand issues.

Get started with Sentry for Next.js in just one minute.