To enable automatic anomaly detection in Kubernetes:

Connect Dynatrace to the Kubernetes API to gather cluster data

Deploy OneAgent (via container/Docker/Operator) to monitor nodes and workloads

Enable Kubernetes anomaly detection settings in Dynatrace

This allows Dynatrace to automatically detect issues like CPU saturation.

RUM is unrelated to infrastructure anomaly detection.

A User Session in Dynatrace contains detailed information about user interactions and experience:

User Tags – custom identifiers assigned to users

Session and Action Properties – metadata describing session behavior

JavaScript and Request Errors – frontend and backend errors impacting the session

User Actions – all interactions such as clicks, page loads, and XHR calls

Server-side code-level insights are not directly part of the user session view; they belong to service-level and distributed tracing analysis.

Log Security Context in Dynatrace allows restricting access to specific logs based on user roles and permissions.

It enables:

Fine-grained access control over log data

Segmentation of logs based on teams or responsibilities

Secure handling of sensitive log information

Other options do not provide this capability:

Log Processing rules transform logs, not control access

SAML configuration handles authentication

OAuth tokens manage API access

Log Viewer is only for viewing logs

Dynatrace provides a comprehensive observability platform including:

Application Observability – full-stack monitoring of applications

Infrastructure Observability – monitoring hosts, cloud, and containers

Business Events Monitoring – capturing and analyzing business data

Application Security – runtime vulnerability detection and protection

OpenSource is not a Dynatrace platform capability.

The Business Event Dataflow in Dynatrace follows a structured pipeline that focuses on collecting, handling, and analyzing business events:

Capture – Business events are ingested into Dynatrace from various sources such as applications, APIs, or external systems

Process – The captured data is processed, enriched, and stored within the Dynatrace platform (Grail)

Analyze – Users query and analyze the processed data using tools like dashboards and DQL

Export is not considered a core step in the business event dataflow. While exporting data is possible, it is not part of the primary ingestion-to-analysis pipeline defined in Dynatrace.

Public Synthetics use Dynatrace’s global network of locations to test applications from various geographic regions.

Ideal for global availability testing

No infrastructure setup required

Private Synthetics are for internal environments.

A Global outage is detected when all configured Synthetic locations report failures at the same time within a defined number of consecutive failed executions. This indicates that the issue is not location-specific but instead affects the application or service globally.

Dynatrace Synthetic Monitoring differentiates between:

Local outages , where only a subset of locations fail (indicating regional or network-specific issues)

Global outages , where all locations fail simultaneously, indicating a widespread availability problem

Options such as Public Synthetics and Private Synthetics refer to types of Synthetic locations, not outage classifications.