This edition
Your users are leaving before you know they had problems. A slow signup flow, a failing payment endpoint, or a broken onboarding step. By the time you hear about it from support tickets, you've already lost trust and revenue.
Most Go applications start with great intentions: fast iteration, clean code, and rapid shipping. But without the right observability foundations from day one, teams end up flying blind. Metrics live in one place, logs in another, and there's no way to connect a spike in error rates to actual user impact.
In this talk, I'll share hard-won lessons from building production systems at scale and show you how to instrument Go applications with user journeys at the center. You'll learn how to build a minimal, effective observability stack using OpenTelemetry, connect technical signals to business outcomes, and establish SLOs that Product and Engineering can co-own.
This is not a talk about adding more dashboards. This is about shipping fast with confidence.
LEVEL: Intermediate
Past editions
Event-driven systems are everywhere, but choosing the right approach can be tricky. Should you use simple webhooks, a message queue like Kafka, or something Go-native like Watermill? This talk explores the trade-offs between webhooks and pub/sub systems, focusing on scalability, reliability, and maintainability in Go applications. We'll walk through real-world scenarios—such as SaaS integrations, real-time notifications, and high-throughput data pipelines—and provide clear decision-making guidelines. Whether you're building a small Go service or architecting a large event-driven system, you'll leave with a solid framework for making the right choice.
LEVEL: Intermediate
