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Sentry Build Developer Workshops
On-Demand
We’re going hands-on with all things application development, and making sure that when your code breaks, you have a good way figure out how to fix it. Sentry Build workshops stay in the code, building software, and debugging real problems with the latest tools from Sentry.







Welcome to Sentry Build
We're going hands-on with all things application development, and making sure that when your code breaks, you have a good way figure out how to fix it. Sentry Build workshops stay in the code, building software, and debugging real problems with the latest tools from Sentry.
git clone https://github.com/sergical/nextjs-conf-scheduler.git cd nextjs-conf-scheduler pnpm install pnpm db:init pnpm db:push pnpm db:seed pnpm dev
Topics
Sentry’s Next.js SDK automatically captures unhandled errors in both server and client components. You’ll learn how to configure error boundaries, add custom context, and use Sentry’s issue grouping to triage and resolve errors faster — whether they originate on the server or in the browser.
Distributed tracing connects frontend requests to backend handlers, database queries, and third-party calls in a single waterfall view. You’ll instrument your Next.js app so Sentry can trace a request from the browser through server components and API routes, making it easy to pinpoint where time is spent.
Structured logs (Sentry.logger) let you search and correlate log output with specific errors and traces — great for debugging individual requests. Metrics (Sentry.metrics counters and distributions) give you aggregate counts and percentiles you can alert on. You’ll learn when to reach for each and how they complement error monitoring and tracing.
Sentry automatically instruments database calls so you can spot slow queries, N+1 patterns, and connection issues. You’ll set up Drizzle ORM with Turso and see how every query appears as a span in your traces, complete with timing and query details.
When you add AI-powered features using the Vercel AI SDK, Sentry can track token usage, model latency, and tool calls automatically. You’ll instrument an AI feature end-to-end so you can monitor costs, debug unexpected model behavior, and trace AI calls alongside the rest of your application.








