Pass the Splunk Enterprise Certified Architect SPLK-2002 Questions and answers with ExamsMirror

The following statements about integrating with third-party systems are true: You can use Splunk alerts to provision actions on a third-party system, and you can forward data from Splunk forwarder to a third-party system without indexing it first. Splunk alerts are triggered events that can execute custom actions, such as sending an email, running a script, or calling a webhook. Splunk alerts can be used to integrate with third-party systems, such as ticketing systems, notification services, or automation platforms. For example, you can use Splunk alerts to create a ticket in ServiceNow, send a message to Slack, or trigger a workflow in Ansible. Splunk forwarders are Splunk instances that collect and forward data to other Splunk instances, such as indexers or heavy forwarders. Splunk forwarders can also forward data to third-party systems, such as Hadoop, Kafka, or AWS Kinesis, without indexing it first. This can be useful for sending data to other data processing or storage systems, or for integrating with other analytics or monitoring tools. A Hadoop application cannot search data in Splunk, because Splunk does not provide a native interface for Hadoop applications to access Splunk data. Splunk can search data in the Hadoop File System (HDFS), but only by using the Hadoop Connect app, which is a Splunk app that enables Splunk to index and search data stored in HDFS

In the deployment planning process, a person should identify who gets to see network data in the data policy definition step. This step involves defining the data access policies and permissions for different users and roles in Splunk. The deployment schedule step involves defining the timeline and milestones for the deployment project. The topology diagramming step involves creating a visual representation of the Splunk architecture and components. The data source inventory step involves identifying and documenting the data sources and types that will be ingested by Splunk

Splunk Enterprise licensing is based on the amount of data that is ingested and indexed by the Splunk platform per day1. The data that counts against the license is the data that is stored in the indexes that are visible to the users and searchable by the Splunk software2. The indexes that are visible and searchable by default are the main index and any custom indexes that are created by the users or the apps3. The main index is the default index where Splunk Enterprise stores all data, unless otherwise specified4.

Option B is the correct answer because the data for the main index will count against the ingest-based license, as it is a visible and searchable index by default. Option A is incorrect because the summary index is a special type of index that stores the results of scheduled reports or accelerated data models, which do not count against the license. Option C is incorrect because the _metrics index is an internal index that stores metrics data about the Splunk platform performance, which does not count against the license. Option D is incorrect because the _introspection index is another internal index that stores data about the impact of the Splunk software on the host system, such as CPU, memory, disk, and network usage, which does not count against the license.

References:

1: How Splunk Enterprise licensing works - Splunk Documentation 2: What data counts against my license? - Splunk Documentation 3: [About indexes and indexers - Splunk Documentation] 4: [The main index - Splunk Documentation] : [Summary indexing - Splunk Documentation] : [About metrics indexes - Splunk Documentation] : [About the Monitoring Console - Splunk Documentation]

Increasing the number of parallel ingestion pipelines in server.conf is most likely to improve indexing performance when indexing is slow and real-time search results are delayed in a Splunk environment with two indexers and one search head. The parallel ingestion pipelines allow Splunk to process multiple data streams simultaneously, which increases the indexing throughput and reduces the indexing latency. Increasing the maximum number of hot buckets in indexes.conf will not improve indexing performance, but rather increase the disk space consumption and the bucket rolling time. Decreasing the maximum size of the search pipelines in limits.conf will not improve indexing performance, but rather reduce the search performance and the search concurrency. Decreasing the maximum concurrent scheduled searches in limits.conf will not improve indexing performance, but rather reduce the search capacity and the search availability. For more information, see Configure parallel ingestion pipelines in the Splunk documentation.

The correct topology to ensure a scalable and performant deployment for the customer’s use case is two search head clusters, one for ITSI and one for ES. This configuration provides high availability, load balancing, and isolation for each Splunk app. According to the Splunk documentation1, ITSI and ES should not be installed on the same search head or search head cluster, as they have different requirements and may interfere with each other. Having two separate search head clusters allows each app to have its own dedicated resources and configuration, and avoids potential conflicts and performance issues1. The other options are not recommended, as they either have only one search head or search head cluster, which reduces the availability and scalability of the deployment, or they have both ITSI and ES installed on the same search head or search head cluster, which violates the best practices and may cause problems. Therefore, option B is the correct answer, and options A, C, and D are incorrect.

1: Splunk IT Service Intelligence and Splunk Enterprise Security compatibility

When converting from a single-site to a multi-site cluster, existing single-site clustered buckets will maintain replication as required according to the single-site policies, but never age out. Single-site clustered buckets are buckets that were created before the conversion to a multi-site cluster. These buckets will continue to follow the single-site replication and search factors, meaning that they will have the same number of copies and searchable copies across the cluster, regardless of the site. These buckets will never age out, meaning that they will never be frozen or deleted, unless they are manually converted to multi-site buckets. Single-site clustered buckets will not continue to replicate within the origin site, because they will be distributed across the cluster according to the single-site policies. Single-site clustered buckets will not be replicated across all peers in the multi-site cluster, because they will follow the single-site replication factor, which may be lower than the multi-site total replication factor. Single-site clustered buckets will not stop replicating within the single-site and remain on the indexer they reside on, because they will still be subject to the replication and availability rules of the cluster

According to the Splunk documentation1, the Splunk Deployer deploys app content to the etc/slave-apps/ directory on the search head cluster members by default. This directory contains the apps that the deployer distributes to the members as part of the configuration bundle. The other options are false because:

The etc/apps/ directory contains the apps that are installed locally on each member, not the apps that are distributed by the deployer2.

The etc/shcluster/ directory contains the configuration files for the search head cluster, not the apps that are distributed by the deployer3.

The etc/deploy-apps/ directory is not a valid Splunk directory, as it does not exist in the Splunk file system structure4.

The additional information that is needed to calculate the daily disk consumption, per indexer, if indexer clustering is implemented, is the total daily indexing volume, the number of peer nodes, the replication factor, and the search factor. These information are required to estimate how much data is ingested, how many copies of raw data and searchable data are maintained, and how many indexers are involved in the cluster. The number of accelerated searches, the number of search heads, and the total disk size across the cluster are not relevant for calculating the daily disk consumption, per indexer. For more information, see [Estimate your storage requirements] in the Splunk documentation.

Per the Splunk Enterprise Licensing Documentation, a license peer (such as an indexer or search head) must regularly communicate with its license manager to report data usage and verify license validity. Splunk allows a 72-hour grace period during which the peer continues operating normally even if communication with the license manager fails.

If this communication is not re-established within 72 hours, the peer enters a “license violation” state. In this state, the system blocks all search activities, including ad-hoc and scheduled searches, but continues to ingest and index data. Administrative and licensing-related searches may still run for diagnostic purposes, but user searches are restricted.

The intent of this design is to prevent prolonged unlicensed data ingestion while ensuring the environment remains compliant. The 72-hour rule is hard-coded in Splunk Enterprise and applies uniformly across license types (Enterprise or Distributed). This ensures consistent licensing enforcement across distributed deployments.

Warnings are generated during the grace period, but after 72 hours, searches are automatically blocked until the peer successfully reconnects to its license manager.

References (Splunk Enterprise Documentation):

• Managing Licenses in a Distributed Environment

• License Manager and Peer Communication Workflow

• Splunk License Enforcement and Violation Behavior

• Splunk Enterprise Admin Manual – License Usage and Reporting Policies

Number of concurrent users: This is an important factor because it affects the search performance and resource utilization of the Splunk environment. More users mean more concurrent searches, which require more CPU, memory, and disk I/O. The number of concurrent users also determines the search head capacity and the search head clustering configuration12

Volume of incoming data: This is another crucial factor because it affects the indexing performance and storage requirements of the Splunk environment. More data means more indexing throughput, which requires more CPU, memory, and disk I/O. The volume of incoming data also determines the indexer capacity and the indexer clustering configuration13

Existence of premium apps: This is a relevant factor because some premium apps, such as Splunk Enterprise Security and Splunk IT Service Intelligence, have additional requirements and recommendations for the Splunk environment. For example, Splunk Enterprise Security requires a dedicated search head cluster and a minimum of 12 CPU cores per search head. Splunk IT Service Intelligence requires a minimum of 16 CPU cores and 64 GB of RAM per search head45