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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.

Learn about Sentry's Session Replay in 60 seconds.

You can use the Sentry MCP server to debug issues in applications that are built in v0. You can also use it to create projects, pull down configurations, or dig into performance issues in applications. Check it out.

We're looking at what building a standard set of tools to use in Claude Code looks like for Sentry - and Claude's plugin marketplace is a great way to distribute them. Take it for a spin - the plugin distributes the MCP server, a few skills for setting up core parts of Sentry, and a few commands to use.

​See how Agent Monitoring gives you a better look at all things model usage, call duration, prompting, and more ​Go under the hood with MCP Monitoring - and learn how to debug client connection issues, tool call performance, transports, and all things MCP ​When things start breaking, use Seer, Sentry's AI Debugging Agent to troubleshoot those vague issues that are crashing and get help from a team of robots using Sentry’s AI PR Review.

See how Sentry Logs can surface hidden state bugs that stack traces alone can’t explain. In this walkthrough, we debug a React Native app with an Express.js backend where a missing diet value causes a crash. We inspect the issue, pull in the connected logs, and confirm whether the problem comes from an initial render or from real backend data. By combining issues, traces, and logs from the same session, you get the full story—and a faster path to the fix.

Learn how to use Sentry Logs to measure how often a bug occurs and which users it impacts. In this example, a React Native app with an Express.js backend crashes when the diet value becomes undefined. After identifying the root cause, we use Explore Logs to count how many times users switch their diet to “none,” filter the related log messages, and group results by user type to understand the impact.