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Cisco 500-420 exam covers topics such as the basic concepts of application performance management, the use of Cisco AppDynamics for monitoring and analysis, performance testing, and troubleshooting. 500-420 exam is also designed to test the candidate's knowledge of the AppDynamics Controller, which is the main component of the AppDynamics solution. 500-420 exam consists of multiple-choice questions and simulations, which are designed to test the candidate's ability to troubleshoot real-world performance issues.
Cisco 500-420 exam is designed for individuals who are looking to begin their career in performance analytics. 500-420 Exam is also known as the Cisco AppDynamics Associate Performance Analyst certification exam. Cisco AppDynamics Associate Performance Analyst certification is ideal for those who want to learn about monitoring, testing, and analytics. 500-420 exam is intended for professionals who are involved in performance analysis and monitoring, including application developers, support engineers, technical consultants, and IT managers.
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Cisco 500-420 exam consists of multiple-choice questions and simulations, and covers a range of topics related to Cisco AppDynamics, including installation and configuration, application monitoring, troubleshooting, and analytics. 500-420 Exam is designed to validate your knowledge and skills in these areas, and can help you demonstrate your expertise to potential employers or clients.
NEW QUESTION # 14
Refer to the exhibit.
Using this heap-utilization graph, which method is used to confirm whether a memory leak is occurring during a specific timeframe?
Answer: A
Explanation:
The Tiers and Nodes > Memory tab provides the appropriate JVM-level view for confirming suspected heap growth over a selected timeframe. The analyst should compare Heap Utilization (%) with Heap Current Usage (MB) versus Max (MB) and observe the effect of major garbage-collection events.
A potential memory leak is indicated when heap usage rises progressively and fails to return to a stable lower level after garbage collection. The important pattern is not simply high memory utilization, but an increasing post-garbage-collection baseline over time. The exhibit shows current heap usage gradually increasing relative to the maximum heap allocation, which warrants further memory diagnostics.
Hardware-resource memory metrics represent operating-system memory and do not isolate JVM heap behavior. Swap usage can indicate host memory pressure but cannot confirm an application heap leak. JMX metrics may expose heap values, but the dedicated Memory tab provides the quickest correlated visualization for heap utilization, maximum heap, current usage, and garbage collection.
Relevant CAAPA topics include JVM Memory Monitoring, Heap Utilization, Garbage Collection, Tiers and Nodes Memory View, Memory Leak Detection, and Object Instance Tracking.
NEW QUESTION # 15
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: C
Explanation:
If a Business Transaction stops being displayed on the Business Transaction Dashboard after continuous load, it could be due to the deletion of the Business Transaction Custom Match Rule. Custom Match Rules in AppDynamics are used to define custom business transactions based on specific criteria. If such a rule is deleted, transactions that were previously identified and displayed based on that rule may no longer be recognized as distinct business transactions, leading to their disappearance from the dashboard.
References:
AppDynamics documentation on Business Transactions: Provides insights on configuring and managing business transactions, including the use of custom match rules.
NEW QUESTION # 16
The performance impact on the_______would lead a Performance Analyst to limit the duration and frequency of automatic diagnostic sessions.
Answer: C
Explanation:
The primary concern for a Performance Analyst when considering the impact of automatic diagnostic sessions is the application itself. Intensive diagnostic sessions can be resource-heavy, potentially affecting the application's performance. Therefore, it is often necessary to limit the duration and frequency of these sessions to ensure they do not negatively impact the application's end-user experience.
References:
AppDynamics documentation on Diagnostic Sessions:
https://docs.appdynamics.com/latest/en/troubleshoot/diagnostic-sessions
NEW QUESTION # 17
Which two Key Performance Indicators (KPIs) accurately provide insight into server-level resource consumption? (Choose two.)
Answer: B,C
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 # 18
Which three Key Performance Indicators (KPIs) are automatically collected when you create an Information Point without adding custom data? (Choose three.)
Answer: A,C,F
Explanation:
When an Information Point is created, AppDynamics automatically collects three core method-level KPIs:
Response Time, Errors per Minute, and Calls per Minute.
Response Time measures how long the configured class and method take to execute. This enables the Performance Analyst to identify degradation in a critical internal operation and compare current behavior with historical trends or baselines.
Errors per Minute records the rate at which executions of the Information Point encounter errors. This provides direct visibility into failures associated with the monitored method, even when that method is not itself a Business Transaction entry point.
Calls per Minute measures invocation frequency. It is useful for tracking operational activity such as cache access, pricing calculations, order processing, or calls to a business-critical internal service.
Minimum Response Time, Maximum Response Time, and CPU Time are not the three standard KPIs automatically generated for an Information Point in this context. Additional business values can be collected separately by configuring custom data or custom metrics.
Relevant CAAPA Study Guide topics include Information Points, Method-Level Monitoring, Calls per Minute, Response Time, Errors per Minute, Custom Data, Custom Metrics, and Baseline Comparison.
NEW QUESTION # 19
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P.S. Free 2026 Cisco 500-420 dumps are available on Google Drive shared by TestPDF: https://drive.google.com/open?id=10ztrhK39S4yVYGBt7wHj4OBu69buTRWE