Operations | Monitoring | ITSM | DevOps | Cloud

In a time when budgets are tight but reliability still needs to be high, observability is under the spotlight. Monitoring and observability tools are some of the most expensive parts of a tech stack, often eating up the bulk of the budget. Luckily, there are strategies organizations can implement to reduce costs, such as utilizing open-source solutions like OpenTelemetry (OTEL), which provides a flexible, open standard for data collection without the price tag of proprietary tooling.

Traces tell you what happened and when. Logs tell you why. When something breaks, logs are often your first clue—and if they’re correlated with traces, they can cut debugging time down from hours to minutes. In this section, we’ll wire up end-to-end structured logging across both server and browser environments in your Next.js app, complete with trace correlation and SigNoz integration.

Everything comes at a cost — and observability is no exception. When we add metrics, logging, or distributed tracing to our applications, it helps us understand what’s going on with performance and key UX metrics like success rate and latency. But what’s the cost? I’m not talking about the price of observability tools here, I mean the instrumentation overhead.

Nextjs is a production-ready React framework for building single-page web applications. It enables you to build fast and user-friendly static websites, as well as web applications using Reactjs. Using OpenTelemetry Nextjs libraries, you can set up end-to-end tracing for your Nextjs applications. Nextjs has its own monitoring feature, but it is only limited to measuring the metrics like core web vitals and real-time analytics of the application.

Sentry’s auto-instrumentation, using BrowserTracing, is convenient. You can get interesting insights about your frontend application out-of-the-box, such as whether slow and failing API calls are hurting your user experience (summarized in Network Requests), or how your website stacks up against industry standards for performance (summarized in Web Vitals).

OpenTelemetry is emerging as the common framework for collecting observability data, and for good reason. It’s vendor-neutral, open source, and designed to collect traces, metrics, and logs in a consistent way. But while most of the buzz is around tracing and metrics, let’s not forget: logs are still the backbone of investigation and response. That’s why Graylog now supports native collection of OpenTelemetry data over gRPC.

In the fast-paced world of CI/CD, understanding the performance and behaviour of your pipelines is crucial. GitHub Actions has become a popular choice for automating builds and deployments, but anyone who's debugged a flaky workflow or long-running job knows how challenging it can be to get visibility into what's happening under the hood. We usually rely on build logs, timing data, or guesswork when something goes wrong.

In one of our previous blogs, we discussed distributed tracing in depth. We examined why distributed tracing is critical and its components - spans and trace context. You can check the complete guide here: What is Distributed Tracing and How to Implement it with Open Source? Here, we'll look at some of the best distributed tracing tools. We'll see what each of them offers so that you can choose the right tool for your monitoring and observability requirements.

Observability is essential for maintaining and scaling modern applications. With.NET 8, Microsoft has enhanced support for observability using OpenTelemetry. In this post, we explore how to monitor.NET 8 applications logs with SigNoz, an open-source observability platform, using the OpenTelemetry Protocol (OTLP) exporter.