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| Certification Vendor: | Dynatrace |
|---|---|
| Exam Name: | Dynatrace Associate Certification Exam |
| Exam Number: | Dynatrace-Associate |
| Exam Format: | Multiple Choice, Scenario-based questions, Multiple Response |
| Available Languages: | English |
| Exam Duration: | 60–105 |
| Real Exam Qty: | 50–70 |
| Related Certifications: | Dynatrace Professional Certification |
| Certificate Validity Period: | 2 years |
| Passing Score: | 80% |
| Exam Price: | USD 200 |
| Recommended Training: | Dynatrace University Learning Paths |
| Exam Registration: | Dynatrace University Dynatrace Training & Certification |
| Sample Questions: | Dynatrace Dynatrace-Associate Sample Questions |
| Exam Way: | Online proctored exam |
| Pre Condition: | No formal prerequisites; recommended ~6 months hands-on experience with Dynatrace platform |
| Official Syllabus URL: | https://www.dynatrace.com/support/training-and-certification/ |
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NEW QUESTION # 34
What kind of problems can appear in Dynatrace? (Select all that apply)
Answer: A,B,C,D
Explanation:
Dynatrace categorizes problems based on the type of issue detected:
* Availability - when a service or application becomes unavailable
* Errors - when there is an increase in failure rate
* Slowdown - when response times degrade
* Resource - when infrastructure resources (CPU, memory, disk) are saturated Critical is not a problem type; it is a severity level used to indicate importance, not classification.
Reference: Based on official Dynatrace University training materials covering problem detection categories.
NEW QUESTION # 35
What is the smallest aggregation time for recent metrics?
Answer: A
Explanation:
Dynatrace aggregates recent metrics at a minimum granularity of 1 minute .
This ensures:
* Efficient storage
* Consistent visualization
Smaller intervals like 10 or 30 seconds are not standard aggregation intervals.
Reference: Based on official Dynatrace University training materials on metrics.
NEW QUESTION # 36
A team approaches you about fetching code-level information in Dynatrace about an AWS Lambda/Azure function. Assuming it is instrumented with OneAgent, what's the best place to go to get information about the function?
Answer: B
Explanation:
In Dynatrace, serverless functions (AWS Lambda / Azure Functions) are represented as services when instrumented.
The Services page provides:
* Code-level insights
* Distributed traces
* Performance metrics
* Failure analysis
Other options:
* Hosts page is not applicable to serverless
* Logs page shows logs only
* Cloud provider pages show infrastructure-level data, not deep code insights Reference: Based on official Dynatrace University training materials on serverless monitoring.
NEW QUESTION # 37
Which of the following properties are added to your ingested log data when trace enrichment for logs is enabled? (Select all that apply)
Answer: B,D,E
Explanation:
When trace enrichment for logs is enabled in Dynatrace, additional metadata is automatically added to logs to correlate them with distributed traces.
The key properties added include:
* dt.trace_id - uniquely identifies the distributed trace
* dt.span_id - identifies the specific span within the trace
* dt.entity.process_group_instance - links the log to the specific monitored process instance These attributes enable:
* Seamless correlation between logs and traces
* End-to-end observability across services
* Faster root cause analysis by linking logs directly to transactions
The other options are not part of trace enrichment:
* dt.security_context is related to log access control, not trace enrichment
* DT_RELEASE_VERSION is used for versioning metadata, not tracing
Reference: Based on official Dynatrace University training materials covering log monitoring and trace-log correlation.
NEW QUESTION # 38
What steps would I need to perform to analyze logs?
Answer: A,E
Explanation:
To analyze logs in Dynatrace, two essential steps are required:
* Ingest logs into Dynatrace - logs must first be collected and stored in the platform (Grail)
* Use DQL (Dynatrace Query Language) - to query, filter, and analyze the ingested log data These steps allow users to extract insights, detect issues, and correlate logs with other observability data.
Other options are not part of log analysis:
* RUM is for user experience monitoring
* Distributed Traces are for request tracking
* Operator is for Kubernetes deployment
Reference: Based on official Dynatrace University training materials on log monitoring and DQL.
NEW QUESTION # 39
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