When working with customers transitioning their traditional management to Cisco DNA Center, I often receive the question: Where are the alarms?
With higher complexity of the network infrastructure and higher demands from users, there’s a need to step up the game when it comes to network automation. The approach to network management is evolving rapidly to fulfill this higher demand for automation. Cisco DNA Center is the Intent-Based platform that can bring the automation of the Campus and Branch to the next level.
With this in mind, Cisco DNA Center Assurance leverages the concept of issues to help identify problems rather than just monitoring data. Instead of showing traditional alarms that can overwhelm the network administrator and provide a big number of false positives, Cisco DNA Center receives a large amount of information from the network devices and it processes this data to try to identify problems in the network. I personally see the concept of “issue” as signatures for network or client problems.
In the snapshot below, we can see a list of issues that were detected in this particular network. The type of issues varies from device, connectivity, application, client, and others.
In essence, there are three types of issues: local, AI-driven, and user-defined issues. Local issues are those that are defined in Cisco DNA Center and typically use thresholds or parameters also defined in Cisco DNA Center. AI-Driven Issues are also defined in Cisco DNA Center but are identified by deviations from predicted baselines. These predicted baselines are calculated automatically using AI-driven technologies. Network administrators can create custom or user-defined issues that match Syslog messages.
Issues have a priority associated, they can have a local impact (for example, a client) or global impact and they can be resolved automatically or manually. Optionally, network administrators can associate issues with external notifications, for example, email, Webhooks, Pageduty, and others.
In the snapshot below, there’s a sample of the issue catalog. For each issue, we can see the different attributes such as priority, resolution type, Global/Local category, and Subscription:
Let’s summarize the attributes associated with issues:
- Priority (customizable)
- Enabled vs disabled (customizable)
- Global vs local
- Subscriptions Enablement (customizable)
- Resolution Type (Manual/Auto)
- Locally defined, AI-Driven or user-defined
Some of the attributes are customizable, the options for customization depend on each issue. In the snapshot below, we show an example of issue customization:
How to Troubleshoot Issues
To guarantee a good user experience, we need to be able to find problems. But that’s not enough, we also need to solve those problems as fast as possible. When Cisco DNA Center identifies issues, it provides a clear explanation of the problem coupled with suggested actions to help resolve it faster. Multiple Cisco DNA Center issues also use Machine Reasoning Engine (MRE) technologies to identify the root cause. What is MRE? 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, and detect issues and vulnerabilities. In this context, a machine reasoning engine provides a workflow that ingests telemetry data and applies reasoning rules to help accelerate the resolution of a problem.
Check the videos below for some examples of issue troubleshooting.
On top of system issues (local and AI-driven), network administrators can add their own customized issues matching Syslog messages originating from network devices. We can customize these issues with parameters like a priority and external notifications.
In the snapshot below, we show a newly creative issue that detects “Native VLAN Mismatch”:
Check the videos below that show how to create the user-defined issue “Native VLAN Mismatch” shown in the snapshot above:
Read more of my blogs for more similar content!
Nicely written and should help field teams hugely, Lila. Good one!
Happy to hear that you enjoyed the read and that it will be helpful. Thanks for your comment
Great blog Lila! Very concise and clearly articulated.
Thanks so much Bryony!
I like this!
Thanks for your comment. Glad you liked it