Operations | Monitoring | ITSM | DevOps | Cloud

Interactive Dashboards eliminate the current workflow of opening new tabs and manually recreating queries every time you need to investigate a spike or anomaly. Click directly on any data point to drill down and explore. ​What you can do: ​Built for developers who need to debug production issues efficiently, not juggle with multiple tabs.

In this video, we’ll walk you through how to monitor Claude code activity using OpenTelemetry and SigNoz. You’ll learn how to instrument your usage, capture telemetry data, and visualize it with SigNoz to get better insights into your system performance. Whether you’re exploring observability for AI workloads or looking for an open-source solution to monitor your llm activity, this guide will help you get started.

Making LLMs Observable : AI, OpenTelemetry and Rise of MCP.

Monitor apps using Vercel AI SDK with SigNoz and OpenTelemetry. This video talks about how to configure your AI apps to send data to SigNoz using OpenTelemetry.

What if setting up observability in your Next.js app was as easy as running a few commands? In this quick guide, we show you how to instrument your Next.js application using OpenTelemetry and visualize with SigNoz — without all the headaches.

2025 has truly been the year of Agentic AI, with MCP (Model Context Protocol) emerging as one of its flashy and most talked-about innovations. While many products have seamlessly integrated MCP servers into their systems, these servers are increasingly being labelled as black boxes, opaque components that handle critical tasks but offer little visibility into what’s happening under the hood. We prompt an agent, a tool gets invoked, and a response is generated. But what really happens in between? And when something breaks, how do we trace the failure and debug it effectively?

Build funnels directly on your traces and get instant answers to questions like: What fraction of spans made it from event A to event B? Between which spans are most requests failing? What is the latency between key spans? Traditional observability tools let you inspect traces and spans, but they can’t aggregate or analyze how requests flow across multiple services or stages in your system. In asynchronous, distributed architectures, the root span rarely tells the full story-and there’s no way to measure conversion, drop-off, or latency between arbitrary steps across all traces.

Tired of guessing why your releases stall, which PRs are stuck, or where flaky tests are wasting your team’s time? Most teams obsess over production monitoring, but what about the bottlenecks that often hide in the CI/CD pipeline slowing delivery, draining productivity, and introducing risk before code ever ships. With CI/CD Observability, you can: So, stop flying blind in your delivery process and make every release faster, more reliable, and fully transparent!

Is it the third-party API or my code? Your service suddenly slows down, or errors spike, and you’re stuck guessing if it’s your own logic or an external API you don’t control. We’ve seen this pain across teams: dashboards don’t tell you which vendor or endpoint is the culprit, and debugging turns into a maze of guesswork. Rate limiting, vendor errors, or integration issues often slip through until users complain.

Ever tried to build a metrics dashboard and thought, “Wait, what metrics am I actually sending?” We heard this from users again and again-so we built Metrics Explorer. For the first time, you get a real-time, interactive view of every metric coming into your system: Whether you’re onboarding a new integration, debugging an alert, or just exploring your data, Metrics Explorer makes it easy to understand and work with your metrics-no more guesswork, just clarity.