About Cisco AI Network Analytics
Cisco AI Network Analytics is an application within Cisco DNA Center that leverages the power of machine learning and machine reasoning to provide accurate insights that are specific to your network deployment, which allows you to quickly troubleshoot issues. The following figure and the information that follows describes the Cisco AI Network Analytics architecture:
![Figure 2: Diagram of AI Network NAnalytics Architecture](/c/dam/en/us/td/i/400001-500000/430001-440000/438001-439000/438909.jpg)
Cisco AI Network Analytics consists of the following:
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A worldwide cloud-based data platform where machine learning models are built and analyzed for your specific network environment.
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A machine reasoning inference engine that automates human expertise and captures the workflows in a knowledge base repository.
Machine Learning
Cisco AI Network Analytics leverages advanced machine learning techniques and an advanced cloud learning platform with deidentified network event data to identify critical issues in your network. Cisco AI Network Analytics provides a rich set of information so that you can quickly troubleshoot issues, know their root causes, identify trends and insights, and obtain relevant comparative perspectives. Cisco AI Network Analytics provides this value using a simple, intuitive, and powerful user interface within Cisco DNA Center that is fully integrated with Cisco DNA Assurance.
![Figure 3: Cisco AI Network Analytics Features diagram.](/c/dam/en/us/td/i/300001-400000/350001-360000/356001-357000/356239.jpg)
Cisco AI Network Analytics provides the following:
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Cloud-Based Infrastructure: Network events information is deidentified in Cisco DNA Center and sent through a secure encrypted channel to the Cisco AI Network Analytics cloud-based infrastructure. The Cisco AI Network Analytics cloud runs the machine learning model with such deidentified network event data and brings the issues and overall insights back to Cisco DNA Center.
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Intelligent Issue Detection and Analysis, which includes:
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AI-Driven Baselining: Baselining is a method used to analyze network dynamics to extract behavioral patterns that help define what is the normal (baseline) behavior for that specific network. The actual network performance is then compared with that baseline.
Cisco AI Network Analytics uses the most advanced machine learning techniques to define the baseline that is relevant to your specific network and sites with the current conditions. With this information, Cisco AI Network Analytics is able to define what is normal for each network and site at a specific moment, and identify the most important issues.
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AI-Driven Anomaly Detection: Detect anomalies to determine their root causes and ease troubleshooting.
Cisco AI Network Analytics can detect the following types of AI-driven issues:
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Connection Issues (onboarding issues): Excessive Time, Excessive Failures, Excessive DHCP Time, Excessive DHCP Failures, Excessive AAA Time, Excessive AAA Failures, Excessive Association Time, and Excessive Association Failures.
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Application Experience Issues: Total Radio Throughput, Media Application Throughput, Cloud Application Throughput, Collab Application Throughput, and Social Application Throughput.
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Trends and Insights, which includes:
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Trend Deviations: Determine global patterns (trends) and deviations to provide system-generated insights.
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AP Performance Advisories: Detect APs that have a consistently poor client experience, and provide a root cause and suggested actions.
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Comparative Benchmarking, which includes:
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AI-Driven AP Comparisons in Network Heatmaps: Compare all of the APs in your network for a given month in a heatmap to spot trends and gain insights.
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AI-Driven Peer Comparisons: Determine how your network is performing in comparison to your peer networks for a selected Key Performance Indicator (KPI).
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AI-Driven Network Comparisons: Determine how a network (such as sites, buildings, AP models, client types) is performing compared to another network for a selected KPI.
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Machine Reasoning
The Machine Reasoning Engine (MRE) is a network automation engine that uses artificial intelligence (AI) to automate complex network operation workflows. It encapsulates human knowledge and expertise into a fully automated inference engine to help you perform complex root cause analysis, detect issues and vulnerabilities, and either manually or automatically perform corrective actions. MRE is powered by a cloud-hosted knowledge base, built by Cisco networking experts.