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| Section | Weight | Objectives |
|---|---|---|
| Health Rules, Alerts, and Dashboards | 20% | - Alert configuration and actions - Creating and managing health rules - Custom dashboards and reporting |
| Troubleshooting and Performance Analysis | 15% | - Identifying bottlenecks and root causes - Remediation and optimization steps - Analyzing call graphs and snapshots |
| Information Points, Collectors, and Service Endpoints | 20% | - Configuring information points - Service endpoint monitoring - Database and custom collectors |
| Flow Maps and Application Architecture | 20% | - Component dependency visualization - Environment and topology overview - Interpreting flow maps |
| Business Transactions | 25% | - Metrics analysis and baselining - Slow, error, and stalled transaction identification - Transaction detection and configuration |
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NEW QUESTION # 36
How does a Performance Analyst identify if automatic remediation has been taken for a health rule violation?
Answer: C
Explanation:
To identify if automatic remediation actions have been taken for a health rule violation in AppDynamics, a Performance Analyst should expand the " Description " field of the health rule violation event. This section will provide details on the actions executed as part of the automatic remediation process. These details help analysts understand the steps taken by the system to mitigate the issue without manual intervention.
References: AppDynamics documentation on Health Rule Violations and Automated Actions.
NEW QUESTION # 37
Which statement is correct regarding controller-level and tier/node-level dashboards?
Answer: A
Explanation:
Controller-level and tier/node-level dashboards in AppDynamics are treated as separate entities. They are scoped differently, with controller-level dashboards providing a global view across the entire AppDynamics domain, and tier/node-level dashboards being specific to particular tiers or nodes within an application.
Performance Analysts do not have the ability to cross-reference directly between these two sets of dashboards within the AppDynamics UI.
References:
AppDynamics documentation on Dashboards:
https://docs.appdynamics.com/latest/en/application-monitoring/custom-dashboards
NEW QUESTION # 38
Within the Application Dashboard, which two methods could a Performance Analyst use to quickly demonstrate that a slow backend is contributing to an application slowdown? (Choose two.)
Answer: A,D
Explanation:
The Application Flow - Grid View and Application Flow Map provide the fastest dashboard-level methods for demonstrating that a backend dependency is contributing to degraded application performance.
In Grid View, the analyst can locate the backend and review dependency-specific indicators such as average response time, calls per minute, errors, and calls made by upstream tiers. Comparing these values across relevant time ranges makes it straightforward to show that backend latency rose at the same time as application response time.
The Application Flow Map provides the same dependency context visually. Selecting the backend exposes its performance metrics and relationship to the calling tier, allowing the analyst to compare current behavior with an earlier timeframe or baseline and demonstrate the backend's contribution to end-to-end latency.
Top Business Transactions focuses primarily on transaction-level performance rather than direct backend comparison. Transaction Snapshots provide detailed evidence for individual executions, but they are less suitable for a rapid dashboard-level comparison across timeframes.
Relevant CAAPA topics include Application Dashboard, Flow Map Analysis, Grid View, Backend Performance, Dependency Response Time, and Time-Range Comparison.
NEW QUESTION # 39
A Business Transaction was registered and displayed on the Business Transaction Dashboard. It has continuous load on it. After an hour, the Business Transaction stopped being displayed in the Business Transaction Dashboard. Which action stopped the display of the Business Transaction?
Answer: B
Explanation:
Excluding the Business Transaction from the Business Transaction Dashboard removes it from the displayed transaction list even while traffic continues to execute. Exclusion is specifically intended to suppress unwanted or low-value transactions from normal Business Transaction visibility and prevent them from consuming monitored transaction capacity.
Deleting the Business Transaction alone would not reliably keep it absent. Because the transaction has continuous load, the Application Agent could rediscover and register it again, causing it to reappear. Enabling Business Transaction Lock Down prevents newly discovered transactions from being registered, but it does not automatically remove Business Transactions that were already registered before lockdown was enabled.
Deleting a Custom Match Rule also does not directly remove the existing registered Business Transaction.
The transaction might remain registered, or automatic transaction discovery could continue detecting the same entry point.
Therefore, the action that directly explains why the continuously active transaction stopped appearing is that it was excluded from the Business Transaction Dashboard.
Relevant CAAPA topics include Business Transaction Exclusion, Transaction Registration, Automatic Rediscovery, Business Transaction Lock Down, Custom Match Rules, and Dashboard Visibility.
NEW QUESTION # 40
When a manual diagnostic session is triggered, what snapshots are captured?
Answer: B
Explanation:
A manual diagnostic session causes AppDynamics to collect detailed transaction snapshots for the selected Business Transaction during the active diagnostic period. When an instance of that Business Transaction crosses multiple instrumented tiers or nodes, the snapshot collection context is propagated with the transaction. Consequently, AppDynamics captures the participating transaction segments from all nodes through which the Business Transaction passes, producing an end-to-end distributed snapshot.
The capture is not restricted to transactions classified as slow, very slow, or errors. Those classifications are commonly used by automatic diagnostic-session and snapshot-triggering mechanisms, whereas a manual session is deliberately initiated to gather deeper diagnostic evidence, including transactions that might otherwise be considered normal.
Option D is incomplete because the triggering node initiates snapshot collection, but the resulting distributed snapshot can include downstream nodes that participate in the transaction. Options A and C incorrectly limit collection to performance-policy violations and error conditions.
Relevant CAAPA Study Guide topics include Transaction Snapshots, Manual Diagnostic Sessions, Distributed Transaction Correlation, Call Graph Collection, Business Transaction Health, and Cross-Tier Transaction Tracing.
NEW QUESTION # 41
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