Today, we are very happy to come up with a dynamic dashboard with active anomaly detection on the most used metrics. This is the first update of many that we will deliver in the following days.

Our dashboard aims to make the macro metrics clear while making the tiny details accessible. Using that; you can switch between projects and see the high level metrics at top-left. Just next to it, you can see the alerts and insights (this is also new coming with this update). Insights can show you discrepancies in your serverless architecture even if you didn't set up an alert for that.

At the second row of the dashboard, there's the "Function List" that can show most unhealthy or most costly functions sorted. We want you to check if there's something unexpected in your system. When you click on one of the function there, the charts just right of the functions' list will be updated.

Oh.. yes charts! These charts are first successful result of our work for weeks. You can catch if there's any anomaly in your invocation count, error count and average duration metrics for all functions in a project and for a particular function.

In serverless, it’s normal to see ups and downs because it’s mostly used for unexpected load, right? But even the most unusual graphs have a trendline if you look close/far enough. We are providing a trendline analysis for the metrics of your functions to detect the points that will go outside of the general trendline.  We are basically making a trend analysis in the data by using several parameters. We are using two variables in our calculations of the trend that are namely “period” and “rollup”. “Period” is basically the recurring pattern of your data. For example; the invocation count of your function can go very low on weekdays but can go crazy high for weekends in a normal recurring condition. In this case, it’s advised that you use the period as “week”. “Roll-up” is the period of data to make our aggregations. When you select 5 minutes as a roll-up interval, we’ll aggregate the metrics in 5 minutes into a single metric and consider (or not consider) it as an anomaly.

You can try this new feature from here and provide your feedback from the chat buble at bottom-right of the screen.