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| Section | Weight | Objectives |
|---|---|---|
| Health Rules, Dashboards, and Snapshots | 20% | - Create and interpret dashboards - Create and configure health rules - Locate and analyze snapshots |
| Troubleshooting | 15% | - Identify slow performance and errors from backend systems - Utilize dashboards to identify performance issues - Capture snapshots and troubleshoot health rule violations |
| Agents and Application Performance | 20% | - Troubleshoot performance problems - Verify agent functionality, performance, and connectivity - Monitor performance trends - Determine application performance impact and scheduled reports - Configure alerts and identify system performance metrics |
| Business Transactions | 20% | - Manage discovery and analyze transaction metrics - Create and configure business transaction settings - Determine transaction scope and rule assignment |
| Collectors, Information Points, and Service Endpoints | 25% | - Configure information points and service endpoints - Define and configure data collectors - Analyze service endpoint metrics |
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NEW QUESTION # 32
Which two roll-up types can be configured for an Information Point? (Choose two.)
Answer: C,D
Explanation:
An Information Point custom metric can be configured with the roll-up types Average and Sum. The selected roll-up determines how values reported by repeated executions of the monitored class and method are aggregated during each metric reporting interval.
Average calculates the mean of all collected values within the interval. This is appropriate for measurements such as average item-processing time, average order value, or another numeric value where typical behavior is the primary concern.
Sum adds all collected values reported during the interval. It is appropriate for cumulative business or operational measurements, such as the total number of items processed, total transaction value, or total quantity handled by the instrumented method.
Max is not one of the configurable Information Point roll-up choices in this context. Although maximum values can appear in other AppDynamics metric-analysis scenarios, they are not selected as an Information Point custom-metric roll-up type. Count is represented separately through invocation-frequency metrics such as Calls per Minute rather than as the configured roll-up method for the collected numeric value.
Relevant CAAPA Study Guide topics include Information Points, Custom Metrics, Metric Aggregation, Average Roll-Up, Sum Roll-Up, Method Invocation Monitoring, and Calls per Minute.
NEW QUESTION # 33
Developers and operations personnel complain that the Controller tracks many irrelevant Java classes and methods. How does a Performance Analyst exclude this unhelpful information?
Answer: C
Explanation:
The Performance Analyst should navigate to Configuration > Instrumentation > Call Graph Settings and configure package exclusions. Call Graph Settings control which Java packages, classes, and methods the Application Agent includes when constructing call graphs for transaction snapshots.
Excluding irrelevant package prefixes removes low-value framework, utility, generated-code, or third-party method detail from captured call graphs. This reduces diagnostic noise, makes transaction snapshots easier for developers to interpret, and can lower instrumentation and data-collection overhead. Exclusions should be applied carefully so that application-owned packages and methods required for root-cause analysis remain visible.
The controller-info.xml file contains Java Agent registration and Controller connectivity settings, such as the Controller address, account information, application, tier, and node identity. It is not the appropriate location for call-graph package exclusions. Baselines evaluate normal metric behavior and have no effect on instrumented classes or methods. The mbeans-server.xml file concerns JMX or MBean-related monitoring rather than Java call-graph filtering.
Relevant CAAPA Study Guide topics include Instrumentation Configuration, Call Graph Settings, Package Exclusions, Java Agent Overhead Management, Transaction Snapshots, and Code-Level Visibility.
NEW QUESTION # 34
Within the configuration setting for Slow Transactions, under the "Configure Diagnostic Session Duration and Collection Rate" option, what is the default value pair for the setting "Collect up to ____snapshots per minute for _____ minutes"?
Answer: B
Explanation:
The default value pair for the setting "Collect up to ____ snapshots per minute for _____ minutes" in the configuration for Slow Transactions is 10, 10. This means that by default, the system is set to collect up to 10 snapshots per minute for a duration of 10 minutes during a diagnostic session.
References:
AppDynamics documentation on Transaction Snapshots: Outlines the default settings for diagnostic session duration and collection rates, including the collection of snapshots.
NEW QUESTION # 35
A team of developers deploys new Java servlet code that should create new business transactions in AppDynamics. After applying load on the new code function, there are no new Business Transactions on the Business Transaction Dashboard. Which two options should the developers check in AppDynamics to make sure the Business Transactions can be discovered?
[Choose two.)
Answer: C,E
Explanation:
When new business transactions are not appearing on the Business Transaction Dashboard after deploying new code, developers should verify that there are no exclusion rules in place on the tier where the new code was deployed. Additionally, it is crucial to ensure that the Auto Discovery feature for servlets is enabled for Java agents, as this allows AppDynamics to automatically detect and name business transactions based on incoming requests to servlets. Both of these checks are necessary to ensure that new business transactions can be discovered and monitored.
References: AppDynamics documentation on Business Transaction detection and Java Agent configuration.
NEW QUESTION # 36
An online order portal for a restaurant has a "menu" transaction with different request types that must be monitored as separate transactions, such as "menu.salads" and "menu.entree." A Performance Analyst wants to create one rule that separates the transactions instead of creating an individual rule for each request type.
Which option should be enabled on a Custom Match rule?
Answer: C
Explanation:
The Performance Analyst should enable Split Transaction using request data. This capability allows a single Custom Match rule to dynamically divide one base transaction into multiple business transactions according to values contained in the incoming HTTP request. For example, the rule can identify the base transaction as menu and append a request-derived value such as salads or entree, producing distinct transactions named menu.salads and menu.entree.
This approach avoids maintaining separate match rules for every menu category and scales automatically as additional request values are introduced.
An HTTP Request Data Collector captures request attributes for visibility within transaction snapshots but does not itself split or rename business transactions. A Method Invocation Data Collector captures method parameters, return values, or invoked-object data and is also unrelated to transaction splitting. Split Transaction using JSON is appropriate only when the required discriminator must specifically be extracted from a JSON payload.
Relevant CAAPA topics include Business Transaction Detection, Custom Match Rules, Transaction Naming, Request-Based Splitting, and Data Collectors.
NEW QUESTION # 37
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