Introduction to Skylar Analytics

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This chapter explains what Skylar AI is and how to use it with Skylar Analytics.

Skylar Analytics includes the following components:

  • Data Visualization. Displays dashboards and charts based on data gathered by Skylar AI and SL1.
  • Data Exploration. Enables third-party tools that use the Microsoft Open Database Connectivity (ODBC) interface to access the metric data from Skylar AI.
  • Anomaly Detection. Uses always-on, unsupervised machine learning to identify unusual patterns that do not conform to expected behavior.
  • Predictive Alerting. Generates events in SL1 that forecast when a future event could happen, instead of reporting on an event that has already occurred.

Skylar Analytics requires SL1 12.3.0 or later.

To view the latest Skylar Analytics release notes, see the Skylar Analytics Release Notes.

What is Skylar AI?

Autonomic IT leverages artificial intelligence (AI), automation, and data to intelligently self-manage an entire IT stack. Autonomic IT drives autonomous businesses with rapid decision-making, cost-optimized scalability, and innovative experiences that empower organizations to focus on core innovation. The ScienceLogic AI Platform, which includes Skylar Automated RCA,Skylar Analytics, and soon Skylar Advisor, helps customers with their journey towards Autonomic IT.

Skylar AI is a software services suite powered by artificial intelligence (AI) that is designed to automatically manage and anticipate IT incidents. Skylar AI reasons over telemetry and the stored knowledge of an organization to deliver accurate insights, recommendations, and predictions. 

SL1 collects data and leverages Skylar AI to learn the patterns for a particular device metric over a period of time. Skylar uses the resulting data to build a device metric-specific model that is used to define a scope of expected behavior as well as anomalous data points.

Features of Skylar AI

Skylar AI is the engine that powers several different software components. The components in the Skylar family of services share the following characteristics:

  • Reactive. When something fails, Skylar AI tells you in plain language what happened and how to fix it with relevant context.
  • Predictive. Skylar AI alerts you in advance to an expected out-of-capacity condition.
  • Proactive. Skylar AI accurately answers any question asked of it with context drawn from company knowledge sources, such as bugs, support tickets, Knowledge Base articles, and Product Documentation, and recommends next steps.

Skylar AI integrates seamlessly with the SL1 platform and other IT management tools. You can interact with Skylar AI through these familiar environments, where it enhances existing workflows with AI-driven insights and automation capabilities. Skylar AI can send you alerts and notifications, which can be customized to suit individual preferences or organizational needs. These alerts help you stay informed about potential issues, ongoing incidents, or opportunities for optimization.

Components of Skylar AI

The Skylar AI family of services currently includes the three following components:

  • Skylar Automated Root Cause Analysis (RCA), a log-based, root cause identification and analysis service powered by unsupervised AI.
  • Skylar Analytics, an advanced reporting and custom analytics service that combines AI-powered analytics with deep data exploration and visualization.
  • Skylar Advisor, a proactive IT problem-solving advisory service powered by human-centered AI.

Data Analyzed by Skylar AI

The following image shows the flow of data into and out of SL1 and the Skylar AI Engine:

Image of the Skylar AI and SL1 exchange of data.

The following list contains some of the types of data that SL1 can send to the Skylar AI engine, where the data is analyzed and used by Skylar Automated RCA, Skylar Analytics, and Skylar Advisor:

  • Alert and event logs
  • Availability data collected by SL1
  • Business service health, availability, and risk metrics from SL1
  • Class-Based Quality-of-Service (CBQoS) metadata and CBQoS time series data
  • Data from Gen 1 SL1 agents, which use the SL1 Distributed Environment
  • Data from Gen 3 SL1 agents, which use the SL1 Extended Architecture
  • Dynamic Application performance data
  • Topology data for L2, L3, CDP, LLDP, and ad-hoc relationships between devices
  • DCM(+R) relationships
  • Metadata for web content, SOAP/XML transaction, and domain name monitors
  • Process and service data

What is Skylar Analytics?

The Skylar Analytics suite of services uses data gathered by SL1 to explore data, generate visualizations, and monitor IT infrastructure metrics. Skylar Analytics can also use Skylar AI to predict alerts before they happen, and detect anomalies that could become events that might disrupt your IT infrastructure and functionality.

Image of an Skylar Analytics components.

Skylar Analytics includes the following components:

  • Data Visualization contains dashboards and charts based on data gathered by Skylar AI and SL1. Currently, this data includes server-focused metrics and basic network interface metrics, with more metrics planned for future Skylar updates. Please note that the dashboards in Business Intelligence (BI) tools are independent of SL1 dashboards or reports. Data Visualization is achieved using a ScienceLogic-hosted instance of Apache Superset or with your own third party tool.
  • Data Exploration enables third-party tools that use the Microsoft 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. For Skylar Beta, this feature is not yet available.
  • Anomaly Detection uses Skylar AI to identify unusual patterns that do not conform to expected behavior. Anomaly Detection provides always-on, unsupervised, machine-learning-based monitoring that automatically identifies unusual patterns in the real-time performance metrics and resource data that it observes. Anomalies do not necessarily represent problems or events to be concerned about; rather, they represent unexpected behavior that might require further investigation.
  • Predictive Alerting generates events in SL1 that forecast when a future event could happen, instead of reporting on an event that has already occurred. SL1 will display capacity predictions and even automate run book automations based on anticipation of out-of-capacity events before they become a production issue. Predictive alerts are based on real-time data analyzed by Skylar AI against expected device metrics.

For more information about these components, see the following chapters.

Getting Started with Skylar Analytics

Before you can start using Skylar Analytics, you will need to perform the following configurations in SL1 to enable the export of data from SL1 to Skylar:

After you perform these configurations, you can access Skylar Analytics and other key Skylar AI components from the Skylar AI page () in SL1.

Running the Skylar SL1 Management Script

The Skylar SL1 Management Script lets you set up your SL1 connectors and SL1 services for exporting data to Skylar. The script is named sl-otelcol-mgmt.py, and it is included with Skylar Analytics in the sl-otelcol package.

To run the Skylar SL1 Management Script:

  1. Run the Skylar SL1 Management Script on the Database Server (an SL1 Central Database or an SL1 Data Engine):

    sudo sl-otelcol-mgmt.py -vv skylar --skylar-metrics --skylar-config --skylar-endpoint "https://skylar.com" --skylar-api-key "<Skylar-API-Key>" --ap2-feature-flags

    where <Skylar-API-Key> is the API key for Skylar AI. Ask your ScienceLogic contact for this value.

    After successfully running the script, on the System Log page (System > Monitor > System Logs), you will see "Info" messages for each configuration change. You will also see "Major" system log messages whenever connectivity fails for the Skylar endpoint or the OpenTelemetry Collector.

  2. Continue to the next step to specify the organizations you want to use for exporting data to Skylar.

Enabling Skylar Analytics for One or More SL1 Organizations

In SL1, if you want to use Anomaly Detection and Predictive Alerting, you will need to select one or more organizations that will share data with Skylar AI. This data will come from all of the devices in a selected organization. By default, the Skylar AI features are disabled.

You can see which organizations are currently sending data to Skylar AI by going to the Organizations page (Registry > Accounts > Organizations) and looking at the Skylar AI Status column for the organizations.

To enable Anomaly Detection and Predictive Alerting:

  1. In SL1, go to the Organizations page (Registry > Accounts > Organizations) and click the check box for one or more organizations.
  2. In the Select Action drop-down, select Send Data from Selected Orgs to Skylar AI and click Go to start sending data about the selected organizations to Skylar AI. The Skylar AI Status column for the selected organizations changes to Enabled.