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NEW QUESTION # 50
What features should be used to get FULL visibility into a database's performance, including code-level analysis, and metric data? (Select all that apply)
Answer: A,B,E
Explanation:
To achieve full visibility into database performance , Dynatrace requires a combination of deep monitoring, code-level tracing, and database-specific metrics:
* OneAgent in Full-Stack mode on the database host enables deep process-level monitoring and visibility into database internals where supported
* OneAgent on application servers provides code-level tracing , capturing database calls within distributed traces and linking them to application performance
* Database Extensions provide detailed technology-specific metrics , such as query performance, buffer usage, and connections Real User Monitoring focuses on end-user experience and does not directly provide database-level visibility.
Infrastructure-only mode limits visibility to host-level metrics and does not provide deep code-level or database insights.
Reference: Based on official Dynatrace University training materials covering database monitoring and OneAgent deployment strategies.
NEW QUESTION # 51
How can Business Event data be ingested into Dynatrace?
Answer: B,E
Explanation:
Business Event data can be ingested into Dynatrace using:
* Dynatrace API - allows sending structured business events directly into the platform
* OpenTelemetry - supports ingestion of custom event data through open standards Other options are incorrect:
* OneAgent focuses on observability data, not business events
* Logs are separate data types, not primary business event ingestion
* RUM captures user interactions, not structured business events
These ingestion methods enable flexible integration of business data into Dynatrace for analysis.
Reference: Based on official Dynatrace University training materials on Business Events and Grail ingestion.
NEW QUESTION # 52
Which Dynatrace app would be best suited to retain the results of a DQL query for later analysis?
Answer: C
Explanation:
Notebooks are the best tool in Dynatrace for retaining and reusing DQL query results .
They allow users to:
* Store DQL queries
* Keep query results for later analysis
* Combine queries with text, documentation, and visualizations
* Share insights across teams
Other options:
* Dashboards are for visualization, not query retention
* Data Explorer is for ad-hoc analysis
* Reports are more static and not designed for iterative DQL workflows
Reference: Based on official Dynatrace University training materials on Notebooks and DQL usage.
NEW QUESTION # 53
Which capability allows me to integrate Synthetic monitors into my CI/CD pipeline to automate the execution?
Answer: A
Explanation:
On-demand execution allows Synthetic monitors to be triggered programmatically, making it ideal for integration into CI/CD pipelines .
This enables:
* Automated execution of Synthetic tests during deployments
* Validation of application availability and performance
* Integration with DevOps workflows
Other options:
* HTTP monitor is a test type
* Private locations define execution location
* Credential vault stores secrets
Only On-demand execution supports automation in CI/CD pipelines.
Reference: Based on official Dynatrace University training materials on Synthetic Monitoring automation.
NEW QUESTION # 54
Which of these data sources can I utilize when a Kubernetes cluster is being monitored?
Answer: A,C,D
Explanation:
When monitoring Kubernetes, Dynatrace provides multiple relevant data sources:
* Prometheus metrics - ingested and analyzed alongside other metrics
* Infrastructure-level metrics - CPU, memory, disk usage from nodes
* Kubernetes-specific events and metrics - pods, deployments, namespaces, cluster events Other options:
* Code-level insights relate to application tracing, not Kubernetes data sources directly
* OpenKit is used for custom user session tracking, not Kubernetes monitoring Reference: Based on official Dynatrace University training materials on Kubernetes monitoring.
NEW QUESTION # 55
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