Skylar Analytics contains a set of tools that lets you view, analyze, and use the data that SL1 gathers and sends to the Skylar AI engine. Skylar Analytics insights are presented in the SL1 user interface, in a ScienceLogic-hosted instance of Apache Superset, and in the Skylar AI API.
Skylar Analytics includes the following components:
- Data Visualization. Enables SQL-based dashboards and charts based on data gathered by Skylar AI and SL1. Data Visualization is achieved using a ScienceLogic-hosted instance of Apache Superset.
- Data Exploration. Enables third-party tools that use the Open Database Connectivity (ODBC) interface to access the metric data from Skylar AI. This component lets you use ODBC to connect Skylar AI data with applications like Tableau, Microsoft Power BI, or other business intelligence tools.
- Anomaly Detection. Uses always-on anomaly detection to find metric outliers in Dynamic Application time series data. It also computes an anomaly score that characterizes the significance of each anomaly. You can view anomalies for all Dynamic Application metrics by visiting the tab on the Device Investigator page for a device.
- Predictive Alerting. Helps to avoid problems such as file systems running out of space, hosts running out of memory, or issues with network reliability due to oversubscription. The alerts appear as enriched events within SL1.
This video provides an overview of the different features of Skylar Analytics: https://player.vimeo.com/video/990317575?h=74e1aca2bf