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Dynatrace Dynatrace-Associate Exam Syllabus Topics:

TopicDetails
Topic 1
  • Automation: Covers workflows, event-driven automation, and integrations that enable teams to automate remediation and operational tasks.
Topic 2
  • Kubernetes Infrastructure: Covers monitoring and observability of Kubernetes clusters, workloads, and containerized environments within Dynatrace.
Topic 3
  • Dashboards: Covers building and customizing dashboards to visualize and communicate observability data across teams and stakeholders.
Topic 4
  • Infrastructure Observability: Covers monitoring and visibility into hosts, services, and infrastructure components to detect and analyze performance issues.
Topic 5
  • Foundational Platform Capabilities: Covers the core features and navigation of the Dynatrace platform, including entity relationships, tagging, and how data is collected.
Topic 6
  • Synthetics: Covers the creation and monitoring of synthetic tests to simulate user interactions and proactively detect availability or performance issues.
Topic 7
  • Security: Covers vulnerability detection, security alerting, and how Dynatrace identifies and prioritizes security risks across the environment.
Topic 8
  • Business Analytics: Covers capturing and correlating business metrics with technical data to measure the impact of application performance on business outcomes.

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Dynatrace Associate Certification Exam Sample Questions (Q25-Q30):

NEW QUESTION # 25
Name the 3 pillars of observability?

Answer: A,C,E

Explanation:
The three pillars of observability are:
* Metrics - numerical performance data
* Logs - event-based records
* Traces - end-to-end request tracking
These pillars provide the foundation for understanding system behavior.
Other options:
* Automation is not a pillar
* RUM is a capability built on top of these pillars
Reference: Based on standard observability principles covered in Dynatrace University.


NEW QUESTION # 26
For supported technologies, do Kubernetes workloads and pods get monitored differently than traditionally monitored OneAgent processes?

Answer: E

Explanation:
Yes, Kubernetes workloads and pods are monitored differently compared to traditional OneAgent-monitored processes. When Dynatrace is deployed into Kubernetes using the Dynatrace Operator, the OneAgent automatically injects itself into each pod at runtime. This means each container is monitored independently and is shown in Dynatrace as a container entity , not as a traditional process.
This container-based visibility is designed to suit the dynamic and short-lived nature of Kubernetes environments. Traditional OneAgent monitoring associates metrics and topology with processes and hosts, but in Kubernetes, the emphasis shifts toward containers, pods, and workloads. This shift allows Dynatrace to provide accurate and timely data on what's really happening inside containerized apps, aligned with Kubernetes-native objects and metrics.
Other answer options either misstate the behavior (e.g., no service data or requiring OpenTelemetry) or oversimplify the relationship between traditional and Kubernetes monitoring (e.g., "same general information"), making Option E the only correct and fully accurate one.
Reference: Based on official Dynatrace University training content and architecture documentation.


NEW QUESTION # 27
How many threshold values can you set in Data Explorer?

Answer: B

Explanation:
In Dynatrace Data Explorer , you can configure up to five threshold values for a metric. These thresholds allow users to define multiple levels of severity or ranges for visualization and alerting purposes.
This enables:
* Better visualization of metric boundaries
* Clear differentiation between normal, warning, and critical states
* Enhanced dashboard customization
Options with fewer or more thresholds do not align with the platform's supported configuration.
Reference: Based on official Dynatrace University training materials covering Data Explorer and metric analysis.


NEW QUESTION # 28
Select the topology levels that support the viewing of Problems. (Select all that apply)

Answer: B,C,D,E

Explanation:
Dynatrace Problems can be viewed across key monitored entities:
* Processes
* Hosts
* Applications
* Services
These are core topology layers where Davis AI correlates issues.
Other options:
* Synthetics and Data Center are not primary topology levels for problem views Reference: Based on official Dynatrace University training materials on Smartscape and problem analysis.


NEW QUESTION # 29
Which steps would I need to perform to automatically detect anomalies, such as cluster CPU-request saturation events on a node, in my Kubernetes environment?

Answer: A,B,C

Explanation:
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.
Reference: Based on official Dynatrace University training materials on Kubernetes monitoring and anomaly detection.


NEW QUESTION # 30
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