Cisco 500-430 Cisco AppDynamics Professional Implementer(CAPI) Exam Practice Test

The Health Rule REST API allows you to create, configure, update, and delete health rules for multiple applications simultaneously. To use this API, you need to specify the application in the URL string. You can use either the application ID or the application name for this purpose. The application ID is a unique numeric identifier for each application in the Controller. The application name is the display name of the application in the AppDynamics UI. You cannot use the application alias, GUID, or REGEX for the Health Rule REST API. References: Health Rule API and Retrieve All Business Applications in the AppDynamics documentation.

The user under which the JVM runs must have write privileges to the conf and logs directories in the Java Agent home. This is because the conf directory contains the agent configuration files, such as controller-info.xml and agent-config.xml, which may need to be modified or updated by the user. The logs directory contains the agent log files, such as agent.log and agent-errors.log, which are generated by the agent and may need to be accessed or rotated by the user. The user can install the agent as the same user that owns the JVM or as an administrator on the host machine. The user can restrict the remaining contents of the agent directory, such as the lib and bin directories, to read-only access12. References: Install the Java Agent, Java Agent fails to start

According to the Cisco AppDynamics Professional Implementer (CAPI) documents, the two symptoms that occur if an AppDynamics Controller is not scaled correctly are:

• The Controller’s metric reporting is 7 to 10 minutes behind the current time. (D) This is a valid symptom because the AppDynamics Controller collects, processes, and stores metrics from the agents that monitor the applications, tiers, nodes, and other entities. If the Controller is not scaled correctly, it may not have enough resources, such as CPU, memory,disk space, or network bandwidth, to handle the incoming metrics data. This may result in a backlog of metrics data that causes the Controller to lag behind the current time. The Controller’s metric reporting delay can affect the accuracy and timeliness of the performance analysis and troubleshooting12.
• The Controller UI performs slowly. (E) This is a valid symptom because the AppDynamics Controller UI is a web-based application that allows users to access, visualize, and interact with the performance data and configuration settings of the AppDynamics platform. If the Controller is not scaled correctly, it may not have enough resources, such as CPU, memory, disk space, or network bandwidth, to serve the UI requests. This may result in a slow or unresponsive UI that affects the user experience and productivity12.

The incorrect options are:

• Snapshots are not available after 2 weeks. (A) This is not a valid symptom because the AppDynamics Controller does not store snapshots for more than 2 weeks by default. Snapshots are detailed records of the execution context and call graphs of the business transactions that are monitored by the AppDynamics platform. Snapshots are useful for diagnosing performance issues and errors, but they also consume a lot of disk space. The AppDynamics Controller automatically purges the snapshots that are older than 2 weeks, unless the retention policy is changed by the user. The availability of snapshots is not affected by the Controller scaling, unless the disk space is exhausted34.
• Health rule violations occur more frequently. (B) This is not a valid symptom because the AppDynamics Controller does not cause health rule violations to occur more frequently. Health rule violations are triggered when the performance or availability metrics of the monitored entities exceed the thresholds that are defined by the user. Health rule violations indicate the presence of performance issues or errors in the monitored applications, tiers, nodes, or other entities, not in the Controller itself. The frequency of health rule violations is not affected by the Controller scaling, unless the Controller fails to collect or process the metrics data5 .
• The average response times of tiers are higher than normal. © This is not a valid symptom because the AppDynamics Controller does not affect the average response times of tiers. The average response time of a tier is the average time that the tier takes to process the incoming requests from the business transactions that are monitored by the AppDynamics platform. The average response time of a tier is influenced by the performance and behavior of the application code, the infrastructure, the dependencies, and the workload of the tier, not by the Controller itself. The average response time of a tier is not affected by the Controller scaling, unless the Controller fails to collect or process the metrics data .

References:

• 1: Controller System Requirements - AppDynamics
• 2: Controller Sizing Guidelines - AppDynamics
• 3: Transaction Snapshots - AppDynamics
• 4: Configure Data Retention - AppDynamics
• 5: Health Rules - AppDynamics

AppDynamics can collect sensitive data such as credit card numbers from various sources, such as SQL queries, error messages, HTTP headers, cookies, and so on. To protect this data from unauthorized access or exposure, an administrator should configure the user permissions for the following features:

• SQL Bind Variables: This feature enables the agents to capture the values of the parameters that are passed to SQL queries. These values can contain sensitive data such as credit card numbers, passwords, or personal information. To prevent this data from being stored or displayed in the Controller UI, the administrator should disable the Capture SQL Bind Values permission for the users who do not need to see this data. Alternatively, the administrator can enable the Mask SQL Bind Values permission, which replaces the values with asterisks (*) in the UI. The administrator can also configure the agent properties to exclude or mask certain bind variables based on patterns or keywords1.
• Diagnostic Data Collectors: This feature enables the agents to collect additional data from the application code, such as method arguments, return values, HTTP headers, cookies, and so on. These data can also contain sensitive information that should not be exposed to unauthorized users. To control the access to this data, the administrator should disable the View Diagnostic Data Collectors permission for the users who do not need to see this data. The administrator can also configure the agent properties to exclude or mask certain data collectors based on patterns or keywords2.

Other features that can collect sensitive data and require user permissions are Error Detection, Memory Monitoring, and Policies. However, these features are less likely to capture credit card numbers than SQL Bind Variables and Diagnostic Data Collectors. Therefore, the best answer is option C and E. References: Sensitive Data Collection and Security, SQL Bind Variables, and Diagnostic Data Collectors in the AppDynamics documentation.

According to the Cisco AppDynamics Professional Implementer (CAPI) documents, the recommended way to add capacity to the Events Service cluster is to add nodes running on machines with identical hardware matching the existing nodes12. This will increase the data storage, replication, and redundancy of the cluster, as well as the processing power for queries. The Events Service cluster is horizontally scalable, so nodes can be added as your data storage requirements grow32. The Events Service must run on dedicated machines with identical directory structures, user account profiles, and hardware profiles1. For heap space allocation, AppDynamics recommends allocating half of the available RAM to the Events Service process, with a minimum of 7 GB up to 31 GB1. Solid-state drives (SSD) can significantly outperform hard disk drives (HDD), and are therefore recommended for production deployments1.

The incorrect options are:

• Add a new Events Service cluster to share the load. (A) This is not recommended because it will create additional complexity and overhead for managing multiple clusters and routing data and queries to the appropriate cluster. It will also require more license units to enable analytics on multiple clusters.
• Add more storage to the master nodes of the cluster. © This is not recommended because it will not increase the data replication and redundancy of the cluster, nor the processing power for queries. It will also create an imbalance in the cluster, as the master nodes will have more storage than the worker nodes, which may affect the performance and stability of the cluster.
• Add more storage to as many of the existing nodes as possible. (D) This is not recommended because it will not increase the data replication and redundancy of the cluster, nor the processing power for queries. It will also create an imbalance in the cluster, as some nodes will have more storage than others, which may affect the performance and stability of the cluster.

References:

• 1: Cisco AppDynamics Professional Implementer (500-430)
• 2: Events Service Requirements - AppDynamics
• 3: Events Service Deployment - AppDynamics
• 4: Events Service Deployment - AppDynamics

An Events Service cluster is a group of two or more Events Service nodes that work together to store and process unstructured data generated by AppDynamics components such as Application Analytics, Database Visibility, and End User Monitoring1. Using an Events Service cluster has two main advantages over a single-node instance12:

• Clusters allow data replication across multiple nodes. This means that the data is duplicated and distributed among the nodes in the cluster, providing data redundancy and protection against data loss in case of a node failure. Data replication also improves data availability and query performance, as the cluster can handle concurrent requests from multiple clients.
• Clusters are horizontally scalable by adding nodes. This means that the cluster can grow in size and capacity by adding more nodes to the cluster, without affecting the existing nodes or data. Horizontal scaling allows the cluster to handle increasing data volumes and performance demands, as well as balance the workload among the nodes. References: Events Service Deployment, What are the Benefits of Server Clustering?

To add a custom extension to a Machine Agent, you need at least three artifacts: a directory, a jar or script file, and a monitor.xml file12. The directory is where you place your extension files under the /monitors directory. The jar or script file is the executable file that collects and reports the custom metrics to the Machine Agent. The monitor.xml file is the configuration file that defines the name, frequency, and parameters of your extension. You can also optionally include other files such as libraries, configuration files, or templates for yourextension12. References: Build a Monitoring Extension Using Scripts, Extensions and Custom Metrics

The EUM agent is a special agent that runs in web, mobile, or IoT applications and collects metrics on the end user experience. The EUM agent communicates with the EUM Collector, which is a component that verifies, aggregates, and packages the raw metrics sent by the EUM agent12. The EUM Collector can be either a SaaS service provided by AppDynamics or an on-premises server installed by the customer12. The EUM Collector then sends the processed metrics to the AppDynamics Controller and the Events Service for storage, analysis, and visualization12. References: Overview of End User Monitoring, EUM Data

The AppDynamics REST API for retrieving metrics allows you to get values generated for metrics by specifying the path of the metric and the time frame for the data1. The following statements are true regarding this API12:

• Metrics can be retrieved for a fixed time range. You can use the time-range-type parameter to specify a fixed time range such as BEFORE_NOW, AFTER_TIME, or BETWEEN_TIMES. You can also use the duration-in-mins parameter to specify the length of the time range in minutes.
• Wildcards can be used in the REST API metric path. You can use the asterisk () character as a wildcard to match any metric name or part of a metric name. For example, you can use the metric path Business Transaction Performance|Business Transactions||*|Average Response Time (ms) to retrieve the average response time for all business transactions in all tiers. References: Retrieve Metric Data, Retrieve Metric Hierarchy

The default configuration of the Mobile SDK enables crash reports and network requests12. Crash reports capture and report any unhandled exceptions or signals that cause the app to terminate abnormally1. Network requests monitor the performance and errors of HTTP and HTTPS requests made by the app2. These features are enabled by default and do not require any additional code or configuration to work12. References: Crash Reports, Network Requests

The AppDynamics Controller is instrumented by an internal, out-of-the-box, AppDynamics Java agent that monitors the performance and health of the Controller itself1. To access the information provided by the internal agent, you need to log in to the Controller UI with the following credentials2:

• Account = system
• Username = root
• Password =

The system account is a special account that is used only for internal monitoring and troubleshooting purposes. It is not visible in the normal Controller UI and requires a special URL to access it2. The root user is the default administrator user for the system account and has the same password as the admin user for the customer1 account3. References: Controller Self-Monitoring, Monitoring a Controller Using the Internal Monitoring Agent, Controller Accounts

According to the Cisco AppDynamics Professional Implementer (CAPI) documents, the two recommendations for servers in an Events Service Cluster are:

• Should be on the same local network ©: This is a valid recommendation because the Events Service Cluster is based on Apache Cassandra, which is a distributed database that relies on network communication between the nodes. Having the servers on the same local network reduces the network latency and improves the performance and reliability of the cluster. The network bandwidth should be at least 1 Gbps, and the network firewall should allow the required ports for the Events Service Cluster12.
• Should have identical hardware specifications (D): This is a valid recommendation because the Events Service Cluster is horizontally scalable, which means that the nodes share the data storage and processing load equally. Having identical hardware specifications for the servers ensures that the cluster is balanced and efficient, and avoids performance bottlenecks or failures due to hardware differences. The hardware specifications should meet the minimum requirements for the Events Service Cluster, such as CPU cores, RAM, disk space, and disk type12.

The incorrect options are:

• Should be installed using the same user account (A): This is not a valid recommendation because the Events Service Cluster does not require the same user account for installation. The user account that is used to install the Events Service Cluster should have sudo privileges on the target hosts, but it does not have to be the same for all the hosts. The user account that is used to run the Events Service Cluster should have read and write permissions on the installation directory, but it does not have to be the same for all the hosts either12.
• Should have eight or more CPU cores (B): This is not a valid recommendation because the Events Service Cluster does not require eight or more CPU cores for the servers. The minimum requirement for the CPU cores is four, and the recommended requirement is six. Having more CPU cores may improve the performance of the cluster, but it is not a mandatory recommendation12.
• Should be running the same operating system version (E): This is not a valid recommendation because the Events Service Cluster does not require the same operating system version for the servers. The Events Service Cluster supports various Linux operating systems, such as CentOS, Red Hat, Ubuntu, and SUSE. The operating system version should be compatible with the Events Service version, but it does not have to be the same for all the hosts12.

References:

• 1: Events Service Requirements - AppDynamics
• 2: Events Service Deployment - AppDynamics

A load balancer is a network device that distributes incoming traffic among a group of servers or nodes. A load balancer can improve the performance, availability, and scalability of a service bybalancing the load and providing failover mechanisms. In the context of AppDynamics, a load balancer can be used to route the traffic from the Controller and other Events Service clients to the Events Service nodes. The Events Service is the on-premises data storage facility for unstructured data generated by Application Analytics, Database Visibility, and End User Monitoring deployments.

One of the reasons why a load balancer would be deployed in production for a single-node Events Service cluster is to allow for deployment growth in the future. A single-node Events Service cluster is suitable for test environments or small-scale deployments, but it does not offer data replication or scalability. If the data volume or availability requirements increase, the Events Service cluster needs to be expanded to a multi-node cluster, which consists of three or more nodes. Deploying a load balancer in front of a single-node Events Service cluster makes it easier to add more nodes later, without having to modify the configuration of the Controller and other Events Service clients. The load balancer can also provide a single endpoint for the clients and enable load balancing and failover among the nodes1.

The other options are not valid reasons for deploying a load balancer for a single-node Events Service cluster. Option A is incorrect, because the embedded Events Service is not meant to be used along with the single-node cluster, as it runs on the same machine as the Controller and does not offer data replication or scalability. The embedded Events Service is only used by the Database Visibility product by default, and it is not recommended for production Application Analytics or EUM installations1. Option B is incorrect, because hiding the Events Service server’s real name is not a security or performance benefit, and it can be achieved by other means, such as DNS or firewall rules. Option D is incorrect, because a load balancer cannot provide redundancy for a single-node, as there is no other node to fail over to in case of a node failure. A load balancer can only provide redundancy for a multi-node cluster, which has data replication and fault tolerance1. References: Events Service Deployment in the AppDynamics documentation.

The AppDynamics Rest API to retrieve business transactions allows you to get a list of all business transactions in a business application, along with their key metrics and properties1. The correct URL format for this API is1:

• http(s) ://:/controller/rest/applications//business-transactions

The other options are incorrect because12:

• Option A uses an invalid endpoint /allbts, which does not exist in the API.
• Option C uses an incorrect base URL /controller/applications, which is used for the Controller UI, not the Rest API.
• Option D uses a misspelled endpoint /allbis, which does not exist in the API. References: Retrieve All Business Transactions in a Business Application, AppDynamics APIs

The AppDynamics Controller properties that govern how long metric data is retained in the database are1:

• metrics.ten.min.retention.period: This property specifies the number of days to retain metric data at 10-minute granularity. The default value is 32 days.
• metrics.retention.period: This property specifies the number of days to retain metric data at 1-hour granularity. The default value is 365 days.
• metrics.min.retention.period: This property specifies the number of hours to retain metric data at 1-minute granularity. The default value is 4 hours.

The other options are incorrect because1:

• metrics.ten.sec.retention.period: This property does not exist in the AppDynamics Controller. The finest granularity for metric data is 1 minute.
• metrics.day.retention.period: This property does not exist in the AppDynamics Controller. The coarsest granularity for metric data is 1 hour.
• metrics.week.retention.period: This property does not exist in the AppDynamics Controller. The metric data retention is based on days, not weeks. References: Database Size and Data Retention