2 Minute Demo: Troubleshooting Agent

Today we're going to take a close look at the troubleshooting agent, one of my call's new AI features that can save you up to 18 hours of time resolving incidents. Here we have a table that's lost 9 million records. We can see it's impacted 35 tables. These 35 tables to be exact. What we're going to do is use our troubleshooting agent to determine why we lost that data. We see here that we have a pull request that was issued with a filter condition that resulted in us losing that data. The agent here knows that this is actually a planned operation rather than a technical error. What the agent is doing in the background is looking at the tables upstream determining the difference in uh queries that have been issued as well as the ETL jobs surrounding that data and it's consolidated all this information and provided it to us. Now we can interact with our uh agent and through this information we might want to ask well how did you know that this was intentional and the agent is going to respond and it's going to tell us that it knows it was intentional for a few different reasons. One of the reasons that it knows that this was intentional was because of the name uh subscription prune gives a dead giveaway. Uh it knows that there was specific filter condition that was added and that it went through this uh manage pull request process and was documented appropriately. Another question we might have is who issued this pull request so that we can go ahead and talk to them. So let's go ahead and ask that question to our troubleshooting agent. And we have our answer that looks like the user was E8 Post. Now, if this is something you're interested in and you would like to ask whatever questions you like of the troubleshooting agent, get a personalized demo, go to our website, navigate to that request demo button, and book a time. It's really that easy, that simple. Hope to see you soon.