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| Certification Vendor: | Dynatrace |
|---|---|
| Exam Name: | Dynatrace Associate Certification Exam |
| Exam Number: | Dynatrace-Associate |
| Exam Format: | Multiple response, Multiple choice |
| Passing Score: | 72% |
| Real Exam Qty: | 70 |
| Available Languages: | English, Multiple languages |
| Exam Price: | $200 USD |
| Exam Duration: | 105 minutes |
| Related Certifications: | Dynatrace Associate |
| Sample Questions: | Dynatrace Dynatrace-Associate Sample Questions |
| Exam Way: | Online proctored exam |
| Pre Condition: | Approximately six months of hands-on experience with Dynatrace is recommended. No formal prerequisites. |
| Official Syllabus URL: | https://www.dynatrace.com/certification/ |
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NEW QUESTION # 52
Select the topology levels that support the viewing of Problems. (Select all that apply)
Answer: A,B,D,F
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 # 53
I need fine-grained control of the Business Events data ingested. Adding which attribute allows me to achieve this?
Answer: C
Explanation:
The dt.security.context attribute enables fine-grained access control over ingested data, including Business Events.
It allows:
* Segmentation of data
* Restricting access to specific users or groups
* Applying security boundaries to sensitive datasets
Other attributes are related to tracing:
* dt.traceid and dt.spanid are for distributed tracing
* dt.entity.process_group_instance links data to entities
Only dt.security.context provides control over data access and segmentation.
Reference: Based on official Dynatrace University training materials covering Grail and data security.
NEW QUESTION # 54
Which steps outline the Business Event Dataflow? (Select all that apply)
Answer: B,C,D
Explanation:
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.
Reference: Based on official Dynatrace University training materials covering Business Analytics and Grail data flow.
NEW QUESTION # 55
Which language is required to be used to query Business Event data?
Answer: D
Explanation:
Dynatrace uses DQL (Dynatrace Query Language) to query Business Event data stored in Grail.
DQL enables:
* Querying across logs, metrics, traces, and business events
* Advanced filtering, aggregation, and correlation
* Unified analysis across all observability and business data
Grail is the data platform, not a query language.
SQL is not used in Dynatrace for this purpose.
USQL is legacy and not used for Grail-based querying.
Reference: Based on official Dynatrace University training materials covering Grail and DQL.
NEW QUESTION # 56
For supported technologies, do Kubernetes workloads and pods get monitored differently than traditionally monitored OneAgent processes?
Answer: A
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 # 57
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