Keith: I’m assuming green is good? David: Yes—green is good, yellow is caution, and red means something needs attention. We have a “group by” feature that allows dynamic grouping—by provider, resource type, and more. It updates the display in real time.
When we click on a resource, we see its current state, alert history, and relevant metadata. Sometimes, understanding all the underlying infrastructure isn’t necessary. In service-based architectures, you may just need to know whether a key component is down. We help surface that at the right level.
Let’s look at the application view. This breaks down all our apps—HA Proxy, time-series databases, etc. If I’m paged about an issue with Zookeeper, I can drill down to see which nodes are healthy and which ones are in an error state.
We also show trend projections—what we expect to happen based on historical data. You can compare 24-hour and 7-day views to assess whether it’s a one-off issue or part of a larger pattern. You can then analyze whether the problem is localized or if other resources are impacted.
Our forensic session feature simplifies log analysis. It highlights important log keywords—so you don’t need to manually search or build complex queries. If Zookeeper has no leader, we’ll highlight that in red so it’s immediately visible. From there, you can build dashboards for whatever matters—like AI workloads.
We show GPU utilization, LLM input/output token metrics, vector database requests—all in one place. So you don’t need separate tools for each domain. Finally, let’s talk about Edwin AI. Edwin AI focuses on event intelligence and generative AI assistance. Remember all those alerts from earlier?
Edwin correlates them into a single, actionable insight. We might take three seemingly separate alerts and merge them into one incident, say, on a virtual machine in Azure.
We’ll show you the insight, when it was triggered, the underlying alert types (SNMP, uptime, web check, ping loss), and how they’re connected. We even offer GenAI-generated summaries—human-readable descriptions of the issue, potential root causes, and recommended remediation.
We’re also working on AI agent functionality—like a chat assistant that lets you ask follow-up questions. You can say, “Tell me more about this log,” or “Explain this metric,” and the assistant will help you troubleshoot faster.
