Welcome to last day of SigNoz Launch Week! We will start with a chat with Ankit (CTO, SigNoz) about the evolution of SigNoz, our focus on OpenTelemetry and belief in open-source. Post that we will deep dive into recently released Access Token management feature which will help users programmatically access data stored in SigNoz and unlock powerful use cases. Then we will showcase our new SaaS onboarding flow which makes getting started with SigNoz much easier. We will also discuss the process we follow for improving our documentation & onboarding flow.

For day 4, we will showcase the recent work we have done in Logs Pipeline. With Log Pipelines, you can transform logs to suit your querying and aggregation needs before they get stored in the database. Pipelines provide a way to modify the structure and content of log data without needing to change application code or redeploy components. By extracting relevant attributes from logs, pipelines enable more efficient analysis.

Welcome to SigNoz Launch week! In day 3 we will focus on monitoring frontend with SigNoz. We will take examples on how to monitor web vitals of your application and monitoring errors in client applications. This will be followed by a discussion with our maintainers on nuances of building performant frontend application for data dense products like SigNoz. Do tune in!

For day 2, the features in spotlight are the major improvements we have made in the Metrics module & Query Builder.

Welcome to SigNoz Launch Week 1.0! This is our first launch week, and we’re excited to introduce you to some cool new features in SigNoz. We ship fast but often miss sharing the story behind these features with our community. Launch week for us is an opportunity to share the behind-the-scenes of new features that we have built in the recent past. Our open-source maintainers will share the story on the whats, whys, and hows of new upgrades to SigNoz!

In this video, you will see a demo of how to monitor Kafka with OpenTelemetry. We will instrument a NodeJS application using Kafka and get client side metrics like delay between producer emitting a message to consumer receiving it via distributed tracing. We will also get Kafka server metrics like consumer lag and plot it dashboards.