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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.

If Temporal powers your business-critical workflows, you know how tough it is to get real visibility into what’s happening under the hood. Most tools only show basic Prometheus metrics-leaving you guessing about bottlenecks, failures, and performance issues. Join us for a live demo of SigNoz’s industry-first Temporal integration. We’ll show you how to: Whether you’re running Temporal in production or just exploring workflow orchestration, this session will show you how to move from “just metrics” to true, unified observability.

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.

We built deep Temporal observability in SigNoz.

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.