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Metrics anomaly detection configurations

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Metrics anomaly detection configurations

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These anomaly detection jobs can be created in the Metrics app in Kibana.

The jobs below detect anomalous memory and network behavior on hosts and Kubernetes pods. For more details, see the datafeed and job definitions in the metrics_ui_* folders in GitHub.

hosts_memory_usage

For memory usage data about hosts in the Metrics app.
Models system memory usage.
Detects unusual increases in memory usage across hosts.

hosts_network_in

For network traffic across hosts in the Metrics app.
Models inbound network traffic.
Detects unusually high inbound traffic across hosts.

hosts_network_out

For network traffic across hosts in the Metrics app.
Models outbound network traffic.
Detects unusually high outbound traffic across hosts.

k8s_memory_usage

For memory usage data about Kubernetes pods in the Metrics app.
Models system memory usage.
Detects unusual increases in memory usage across Kubernetes pods.

k8s_network_in

For network traffic accross Kubernetes pods in the Metrics app.
Models inbound network traffic.
Detects unusually high inbound traffic across Kubernetes pods.

k8s_network_out

For network traffic across Kubernetes pods in the Metrics app.
Models outbound network traffic.
Detects unusually high outbound traffic across Kubernetes pods.

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