Monitoring Network Performance and Events
Interfaces Sending or Receiving Traffic
- DMF Top Filter interfaces
- Production interfaces
This information derives from the LLDP/CDP exchange between the production switches and the DANZ Monitoring Fabric switches.
Anomalies
- Comparing dashboards and visualization over time
- sFlow > Count sFlow vs Last Wk
- New Flows & New Hosts
- Utilization alerts
- Machine Learning
Identify any unusual activity by comparing the same dashboard over the past 1 hour to the same time last week. For example, the bar visualization of traffic over time shows changing ratios of internal to external traffic, which can highlight an abnormality.
In a well-inventoried environment, use the New Flows & New Hosts report.
Configure utilization alerts associated with the following DMF port types:
- Filter
- Delivery
- Core
- Services
- Percentage of outbound traffic exceeds usual thresholds.
- New Hosts appearing on the network every 24 hours.
Application Data Management
Application Data Management (ADM) helps users govern and manage data in business applications like SAP ERP. To use Arista Analytics for ADM, perform the following steps:
- Pick a service IP address or block of IP addresses.
- Identify the main body of expected communication with adjacent application servers.
- Filter down to ports that need to be communicating.
- Expand the time horizon to characterize necessary communication completely.
- Save as CSV.
- Convert the CSV to ACL rules to enforce in the network.
WAN Link Optimization
To identify a WAN link or device that is approaching full utilization, complete the following steps:
Machine Learning
- Single-metric anomaly detection
- Multimetric anomaly detection
- Population
- Advanced
- Categorization
- Select the time range
- Select the appropriate metric
- Enter details: job ID, description, custom URLs, and calendars to exclude planned outages from the job
Single-metric anomaly detection uses machine learning on only one metric or field.