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| Section | Weight | Objectives |
|---|---|---|
| Business Transactions | 20% | - Determine transaction scope and rule assignment - Create and configure business transaction settings - Manage discovery and analyze transaction metrics |
| Agents and Application Performance | 20% | - Configure alerts and identify system performance metrics - Troubleshoot performance problems - Determine application performance impact and scheduled reports - Monitor performance trends - Verify agent functionality, performance, and connectivity |
| Health Rules, Dashboards, and Snapshots | 20% | - Create and configure health rules - Create and interpret dashboards - Locate and analyze snapshots |
| Collectors, Information Points, and Service Endpoints | 25% | - Configure information points and service endpoints - Define and configure data collectors - Analyze service endpoint metrics |
| Troubleshooting | 15% | - Identify slow performance and errors from backend systems - Utilize dashboards to identify performance issues - Capture snapshots and troubleshoot health rule violations |
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NEW QUESTION # 63
Which statement about Service End Points and Business Transactions is true?
Answer: D
Explanation:
Both Service Endpoints and Business Transactions in AppDynamics have the capability to configure data collectors. Data collectors are used to gather detailed information about transactions or endpoints, such as method parameters, return values, and SQL statements.
References:
AppDynamics documentation on Data Collectors:
https://docs.appdynamics.com/latest/en/application-monitoring/configure-data-collection
NEW QUESTION # 64
A Performance Analyst is reviewing Business Transactions with an application team. The application team wants to increase the Application Business Transaction limit because it needs visibility into all the different transactions. What should the Performance Analyst do?
Answer: D
Explanation:
The Performance Analyst should first investigate the Business Transactions exceeding the configured limit and determine why so many unique transactions are being registered. Business Transaction limits protect the Controller from excessive metric creation, unnecessary cardinality, and degraded monitoring performance.
A high transaction count is often caused by overly granular transaction naming, dynamic URL segments, request parameters, identifiers, or automatic discovery rules that create a separate Business Transaction for each variation. The analyst should review All Other Traffic, transaction detection rules, naming rules, and the entry points generating excessive registrations. Low-value traffic such as health checks, static resources, or framework-generated requests can be excluded, while related requests can be grouped or split more deliberately through Custom Match Rules.
Increasing the limit without correcting the underlying detection behavior may only postpone the problem and increase Controller resource consumption. The limit should be raised only after the transaction model has been validated and a genuine business requirement remains.
Relevant CAAPA Study Guide topics include Business Transaction Limits, All Other Traffic, Transaction Detection Rules, Custom Match Rules, Exclude Rules, Transaction Naming, and Metric Cardinality Management.
NEW QUESTION # 65
Which two Key Performance Indicators (KPIs) accurately provide insight into server-level resource consumption? (Choose two.)
Answer: A,E
Explanation:
Memory Used% and CPU %Busy are the two KPIs that directly measure server-level resource consumption.
Memory Used% represents the proportion of physical memory currently consumed on the monitored server.
A sustained high value can indicate memory pressure, excessive process allocation, insufficient capacity, or conditions that may lead to paging and degraded application performance.
CPU %Busy measures the percentage of processor capacity actively being used. It is a primary indicator of compute-resource utilization and helps identify CPU saturation, processing bottlenecks, or insufficient server capacity. Persistent high CPU utilization may correlate with increased response time, transaction queuing, and reduced throughput.
The remaining options describe availability, application behavior, or transaction performance rather than direct infrastructure-resource consumption. Calls per Minute measures workload volume, Average Response Time measures transaction latency, Availability indicates whether a system or service is reachable, and Application Restarts records lifecycle events.
Relevant CAAPA Study Guide topics include Server Visibility, Infrastructure Monitoring, Hardware Resource Metrics, CPU Utilization, Memory Utilization, and Correlating Server Health with Application Performance.
NEW QUESTION # 66
What are two differences between creating a Transaction Group using the 'Create Group' action and defining a Transaction Detection rule? (Choose two.)
Answer: C,D
Explanation:
Creating a Transaction Group using the 'Create Group' action in AppDynamics allows for the aggregation of data from multiple transactions under a single group, facilitating a consolidated view of similar transactions.
This differs from defining a Transaction Detection Rule, which typically focuses on identifying and categorizing individual transactions based on specific criteria. Transaction Groups do not change the names of incoming requests nor reduce the number of overall business transactions; instead, they provide a method for organizing and analyzing related transactions collectively, offering a streamlined approach compared to individually configuring Transaction Detection Rules for each transaction.
References:
AppDynamics documentation on Business Transactions: Covers the concept of Transaction Groups and their role in organizing and analyzing transaction data, as well as the process for creating and managing Transaction Detection Rules.
NEW QUESTION # 67
Which path is used to specify a metric that evaluates across multiple hardware entities or memory pools?
Answer: A
Explanation:
A relative metric path with a wildcard is used when a metric condition must be evaluated across multiple comparable entities, such as hardware resources, JVM memory pools, nodes, or other dynamically named metric branches.
A relative path is resolved in the context of each entity selected by the health rule or metric evaluation scope.
Adding a wildcard allows AppDynamics to match multiple child metric paths rather than requiring one fixed, fully qualified metric location. This is particularly useful when memory-pool names, hardware instances, or resource identifiers differ between nodes or runtime environments.
An absolute metric path points to one exact location in the metric hierarchy and is therefore better suited to a single, explicitly identified metric. Although wildcard matching can be supported in metric configurations, the correct approach for evaluating equivalent metrics across multiple scoped entities is the relative-path model.
The Metric Browser supports hierarchical metric navigation, and wildcard-capable paths are used where dynamic or repeated entity structures must be addressed. Relevant CAAPA Study Guide topics include Metric Browser, Relative and Absolute Metric Paths, Wildcard Metric Selection, Health Rule Conditions, Hardware Resource Metrics, and JVM Memory Pool Monitoring.
NEW QUESTION # 68
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