Practice Free SPLK-2002 Exam Online Questions
Question #41
What does setting site=site0 on all Search Head Cluster members do in a multi-site indexer cluster?
- A . Disables search site affinity.
- B . Sets all members to dynamic captaincy.
- C . Enables multisite search artifact replication.
- D . Enables automatic search site affinity discovery.
Correct Answer: A
A
Explanation:
Setting site=site0 on all Search Head Cluster members disables search site affinity. Search site affinity is a feature that allows search heads to preferentially search the peer nodes that are in the same site as the search head, to reduce network latency and bandwidth consumption. By setting site=site0, which is a special value that indicates no site, the search heads will search all peer nodes regardless of their site. Setting site=site0 does not set all members to dynamic captaincy, enable multisite search artifact replication, or enable automatic search site affinity discovery. Dynamic captaincy is a feature that allows any member to become the captain, and it is enabled by default. Multisite search artifact replication is a feature that allows search artifacts to be replicated across sites, and it is enabled by setting site_replication_factor to a value greater than 1. Automatic search site affinity discovery is a feature that allows search heads to automatically determine their site based on the network latency to the peer nodes, and it is enabled by setting site=auto
A
Explanation:
Setting site=site0 on all Search Head Cluster members disables search site affinity. Search site affinity is a feature that allows search heads to preferentially search the peer nodes that are in the same site as the search head, to reduce network latency and bandwidth consumption. By setting site=site0, which is a special value that indicates no site, the search heads will search all peer nodes regardless of their site. Setting site=site0 does not set all members to dynamic captaincy, enable multisite search artifact replication, or enable automatic search site affinity discovery. Dynamic captaincy is a feature that allows any member to become the captain, and it is enabled by default. Multisite search artifact replication is a feature that allows search artifacts to be replicated across sites, and it is enabled by setting site_replication_factor to a value greater than 1. Automatic search site affinity discovery is a feature that allows search heads to automatically determine their site based on the network latency to the peer nodes, and it is enabled by setting site=auto
Question #42
Which of the following options in limits, conf may provide performance benefits at the forwarding tier?
- A . Enable the indexed_realtime_use_by_default attribute.
- B . Increase the maxKBps attribute.
- C . Increase the parallellngestionPipelines attribute.
- D . Increase the max_searches per_cpu attribute.
Correct Answer: C
C
Explanation:
The correct answer is
C. Increase the parallellngestionPipelines attribute. This is an option in limits.conf that may provide performance benefits at the forwarding tier, as it allows the forwarder to process multiple data inputs in parallel1. The parallellngestionPipelines attribute specifies the number of pipelines that the forwarder can use to ingest data from different sources1. By increasing this value, the forwarder can improve its throughput and reduce the latency of data delivery1. The other options are not effective options to provide performance benefits at the forwarding
tier.
Option A, enabling the indexed_realtime_use_by_default attribute, is not recommended, as it enables the forwarder to send data to the indexer as soon as it is received, which may increase the network and CPU load and degrade the performance2.
Option B, increasing the maxKBps attribute, is not a good option, as it increases the maximum bandwidth, in kilobytes per second, that the forwarder can use to send data to the indexer3. This may improve the data transfer speed, but it may also saturate the network and cause congestion and packet loss3.
Option D, increasing the max_searches_per_cpu attribute, is not relevant, as it only affects the search performance on the indexer or search head, not the forwarding performance on the forwarder4. Therefore, option C is the correct answer, and options A, B, and D are incorrect.
1: Configure parallel ingestion pipelines 2: Configure real-time forwarding 3: Configure forwarder output 4: Configure search performance
C
Explanation:
The correct answer is
C. Increase the parallellngestionPipelines attribute. This is an option in limits.conf that may provide performance benefits at the forwarding tier, as it allows the forwarder to process multiple data inputs in parallel1. The parallellngestionPipelines attribute specifies the number of pipelines that the forwarder can use to ingest data from different sources1. By increasing this value, the forwarder can improve its throughput and reduce the latency of data delivery1. The other options are not effective options to provide performance benefits at the forwarding
tier.
Option A, enabling the indexed_realtime_use_by_default attribute, is not recommended, as it enables the forwarder to send data to the indexer as soon as it is received, which may increase the network and CPU load and degrade the performance2.
Option B, increasing the maxKBps attribute, is not a good option, as it increases the maximum bandwidth, in kilobytes per second, that the forwarder can use to send data to the indexer3. This may improve the data transfer speed, but it may also saturate the network and cause congestion and packet loss3.
Option D, increasing the max_searches_per_cpu attribute, is not relevant, as it only affects the search performance on the indexer or search head, not the forwarding performance on the forwarder4. Therefore, option C is the correct answer, and options A, B, and D are incorrect.
1: Configure parallel ingestion pipelines 2: Configure real-time forwarding 3: Configure forwarder output 4: Configure search performance
Question #43
If .delta replication fails during knowledge bundle replication, what is the fall-back method for Splunk?
- A . .Restart splunkd.
- B . .delta replication.
- C . .bundle replication.
- D . Restart mongod.
Correct Answer: C
C
Explanation:
This is the fall-back method for Splunk if .delta replication fails during knowledge bundle replication. Knowledge bundle replication is the process of distributing the knowledge objects, such as lookups, macros, and field extractions, from the search head cluster to the indexer cluster1. Splunk uses two methods of knowledge bundle replication: .delta replication and .bundle replication1. .Delta replication is the default and preferred method, as it only replicates the changes or updates to the knowledge objects, which reduces the network traffic and disk space usage1. However, if .delta replication fails for some reason, such as corrupted files or network errors, Splunk automatically switches to .bundle replication, which replicates the entire knowledge bundle, regardless of the changes or updates1. This ensures that the knowledge objects are always synchronized between the search head cluster and the indexer cluster, but it also consumes more network bandwidth and disk space1. The other options are not valid fall-back methods for Splunk.
Option A, restarting splunkd, is not a method of knowledge bundle replication, but a way to restart the Splunk daemon on a node2. This may or may not fix the .delta replication failure, but it does not guarantee the synchronization of the knowledge objects.
Option B, .delta replication, is not a fall-back method, but the primary method of knowledge bundle replication, which is assumed to have failed in the question1.
Option D, restarting mongod, is not a method of knowledge bundle replication, but a way to restart the MongoDB daemon on a node3. This is not related to the knowledge bundle replication, but to the KV store replication, which is a different process3. Therefore, option C is the correct answer, and options A, B, and D are incorrect.
1: How knowledge bundle replication works 2: Start and stop Splunk Enterprise 3: Restart the KV store
C
Explanation:
This is the fall-back method for Splunk if .delta replication fails during knowledge bundle replication. Knowledge bundle replication is the process of distributing the knowledge objects, such as lookups, macros, and field extractions, from the search head cluster to the indexer cluster1. Splunk uses two methods of knowledge bundle replication: .delta replication and .bundle replication1. .Delta replication is the default and preferred method, as it only replicates the changes or updates to the knowledge objects, which reduces the network traffic and disk space usage1. However, if .delta replication fails for some reason, such as corrupted files or network errors, Splunk automatically switches to .bundle replication, which replicates the entire knowledge bundle, regardless of the changes or updates1. This ensures that the knowledge objects are always synchronized between the search head cluster and the indexer cluster, but it also consumes more network bandwidth and disk space1. The other options are not valid fall-back methods for Splunk.
Option A, restarting splunkd, is not a method of knowledge bundle replication, but a way to restart the Splunk daemon on a node2. This may or may not fix the .delta replication failure, but it does not guarantee the synchronization of the knowledge objects.
Option B, .delta replication, is not a fall-back method, but the primary method of knowledge bundle replication, which is assumed to have failed in the question1.
Option D, restarting mongod, is not a method of knowledge bundle replication, but a way to restart the MongoDB daemon on a node3. This is not related to the knowledge bundle replication, but to the KV store replication, which is a different process3. Therefore, option C is the correct answer, and options A, B, and D are incorrect.
1: How knowledge bundle replication works 2: Start and stop Splunk Enterprise 3: Restart the KV store
Question #44
Before users can use a KV store, an admin must create a collection. Where is a collection is defined?
- A . kvstore.conf
- B . collection.conf
- C . collections.conf
- D . kvcollections.conf
Correct Answer: C
C
Explanation:
A collection is defined in the collections.conf file, which specifies the name, schema, and permissions of the collection. The kvstore.conf file is used to configure the KV store settings, such as the port, SSL, and replication factor. The other two files do not exist1
C
Explanation:
A collection is defined in the collections.conf file, which specifies the name, schema, and permissions of the collection. The kvstore.conf file is used to configure the KV store settings, such as the port, SSL, and replication factor. The other two files do not exist1
Question #45
By default, what happens to configurations in the local folder of each Splunk app when it is deployed to a search head cluster?
- A . The local folder is copied to the local folder on the search heads.
- B . The local folder is merged into the default folder and deployed to the search heads.
- C . Only certain . conf files in the local folder are deployed to the search heads.
- D . The local folder is ignored and only the default folder is copied to the search heads.
Correct Answer: B
B
Explanation:
A search head cluster is a group of Splunk Enterprise search heads that share configurations, job scheduling, and search artifacts1. The deployer is a Splunk Enterprise instance that distributes apps and other configurations to the cluster members1. The local folder of each Splunk app contains the custom configurations that override the default settings2. The default folder of each Splunk app contains the default configurations that are provided by the app2.
By default, when the deployer pushes an app to the search head cluster, it merges the local folder of the app into the default folder and deploys the merged folder to the search heads3. This means that the custom configurations in the local folder will take precedence over the default settings in the default folder. However, this also means that the local folder of the app on the search heads will be empty, unless the app is modified through the search head UI3.
Option B is the correct answer because it reflects the default behavior of the deployer when pushing
apps to the search head cluster.
Option A is incorrect because the local folder is not copied to the local folder on the search heads, but merged into the default folder.
Option C is incorrect because all the .conf files in the local folder are deployed to the search heads, not only certain ones.
Option D is incorrect because the local folder is not ignored, but merged into the default folder.
Reference: 1: Search head clustering architecture – Splunk Documentation 2: About configuration files C Splunk Documentation 3: Use the deployer to distribute apps and configuration updates – Splunk Documentation
B
Explanation:
A search head cluster is a group of Splunk Enterprise search heads that share configurations, job scheduling, and search artifacts1. The deployer is a Splunk Enterprise instance that distributes apps and other configurations to the cluster members1. The local folder of each Splunk app contains the custom configurations that override the default settings2. The default folder of each Splunk app contains the default configurations that are provided by the app2.
By default, when the deployer pushes an app to the search head cluster, it merges the local folder of the app into the default folder and deploys the merged folder to the search heads3. This means that the custom configurations in the local folder will take precedence over the default settings in the default folder. However, this also means that the local folder of the app on the search heads will be empty, unless the app is modified through the search head UI3.
Option B is the correct answer because it reflects the default behavior of the deployer when pushing
apps to the search head cluster.
Option A is incorrect because the local folder is not copied to the local folder on the search heads, but merged into the default folder.
Option C is incorrect because all the .conf files in the local folder are deployed to the search heads, not only certain ones.
Option D is incorrect because the local folder is not ignored, but merged into the default folder.
Reference: 1: Search head clustering architecture – Splunk Documentation 2: About configuration files C Splunk Documentation 3: Use the deployer to distribute apps and configuration updates – Splunk Documentation
Question #45
By default, what happens to configurations in the local folder of each Splunk app when it is deployed to a search head cluster?
- A . The local folder is copied to the local folder on the search heads.
- B . The local folder is merged into the default folder and deployed to the search heads.
- C . Only certain . conf files in the local folder are deployed to the search heads.
- D . The local folder is ignored and only the default folder is copied to the search heads.
Correct Answer: B
B
Explanation:
A search head cluster is a group of Splunk Enterprise search heads that share configurations, job scheduling, and search artifacts1. The deployer is a Splunk Enterprise instance that distributes apps and other configurations to the cluster members1. The local folder of each Splunk app contains the custom configurations that override the default settings2. The default folder of each Splunk app contains the default configurations that are provided by the app2.
By default, when the deployer pushes an app to the search head cluster, it merges the local folder of the app into the default folder and deploys the merged folder to the search heads3. This means that the custom configurations in the local folder will take precedence over the default settings in the default folder. However, this also means that the local folder of the app on the search heads will be empty, unless the app is modified through the search head UI3.
Option B is the correct answer because it reflects the default behavior of the deployer when pushing
apps to the search head cluster.
Option A is incorrect because the local folder is not copied to the local folder on the search heads, but merged into the default folder.
Option C is incorrect because all the .conf files in the local folder are deployed to the search heads, not only certain ones.
Option D is incorrect because the local folder is not ignored, but merged into the default folder.
Reference: 1: Search head clustering architecture – Splunk Documentation 2: About configuration files C Splunk Documentation 3: Use the deployer to distribute apps and configuration updates – Splunk Documentation
B
Explanation:
A search head cluster is a group of Splunk Enterprise search heads that share configurations, job scheduling, and search artifacts1. The deployer is a Splunk Enterprise instance that distributes apps and other configurations to the cluster members1. The local folder of each Splunk app contains the custom configurations that override the default settings2. The default folder of each Splunk app contains the default configurations that are provided by the app2.
By default, when the deployer pushes an app to the search head cluster, it merges the local folder of the app into the default folder and deploys the merged folder to the search heads3. This means that the custom configurations in the local folder will take precedence over the default settings in the default folder. However, this also means that the local folder of the app on the search heads will be empty, unless the app is modified through the search head UI3.
Option B is the correct answer because it reflects the default behavior of the deployer when pushing
apps to the search head cluster.
Option A is incorrect because the local folder is not copied to the local folder on the search heads, but merged into the default folder.
Option C is incorrect because all the .conf files in the local folder are deployed to the search heads, not only certain ones.
Option D is incorrect because the local folder is not ignored, but merged into the default folder.
Reference: 1: Search head clustering architecture – Splunk Documentation 2: About configuration files C Splunk Documentation 3: Use the deployer to distribute apps and configuration updates – Splunk Documentation
Question #47
When implementing KV Store Collections in a search head cluster, which of the following considerations is true?
- A . The KV Store Primary coordinates with the search head cluster captain when collection content changes.
- B . The search head cluster captain is also the KV Store Primary when collection content changes.
- C . The KV Store Collection will not allow for changes to content if there are more than 50 search heads in the cluster.
- D . Each search head in the cluster independently updates its KV store collection when collection content changes.
Correct Answer: B
B
Explanation:
According to the Splunk documentation1, in a search head cluster, the KV Store Primary is the same node as the search head cluster captain. The KV Store Primary is responsible for coordinating the replication of KV Store data across the cluster members. When any node receives a write request, the KV Store delegates the write to the KV Store Primary. The KV Store keeps the reads local, however. This ensures that the KV Store data is consistent and available across the cluster.
Reference: About the app key value store
KV Store and search head clusters
B
Explanation:
According to the Splunk documentation1, in a search head cluster, the KV Store Primary is the same node as the search head cluster captain. The KV Store Primary is responsible for coordinating the replication of KV Store data across the cluster members. When any node receives a write request, the KV Store delegates the write to the KV Store Primary. The KV Store keeps the reads local, however. This ensures that the KV Store data is consistent and available across the cluster.
Reference: About the app key value store
KV Store and search head clusters
Question #48
In the deployment planning process, when should a person identify who gets to see network data?
- A . Deployment schedule
- B . Topology diagramming
- C . Data source inventory
- D . Data policy definition
Correct Answer: D
D
Explanation:
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
D
Explanation:
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
Question #49
How does IT Service Intelligence (ITSI) impact the planning of a Splunk deployment?
- A . ITSI requires a dedicated deployment server.
- B . The amount of users using ITSI will not impact performance.
- C . ITSI in a Splunk deployment does not require additional hardware resources.
- D . Depending on the Key Performance Indicators that are being tracked, additional infrastructure may be needed.
Correct Answer: D
D
Explanation:
ITSI can impact the planning of a Splunk deployment depending on the Key Performance Indicators (KPIs) that are being tracked. KPIs are metrics that measure the health and performance of IT services and business processes. ITSI collects, analyzes, and displays KPI data from various data sources in Splunk. Depending on the number, frequency, and complexity of the KPIs, additional infrastructure may be needed to support the data ingestion, processing, and visualization. ITSI does not require a dedicated deployment server, nor does it affect the number of users using ITSI. ITSI in a Splunk deployment does require additional hardware resources, such as CPU, memory, and disk space, to run the ITSI components and apps
D
Explanation:
ITSI can impact the planning of a Splunk deployment depending on the Key Performance Indicators (KPIs) that are being tracked. KPIs are metrics that measure the health and performance of IT services and business processes. ITSI collects, analyzes, and displays KPI data from various data sources in Splunk. Depending on the number, frequency, and complexity of the KPIs, additional infrastructure may be needed to support the data ingestion, processing, and visualization. ITSI does not require a dedicated deployment server, nor does it affect the number of users using ITSI. ITSI in a Splunk deployment does require additional hardware resources, such as CPU, memory, and disk space, to run the ITSI components and apps
Question #50
When using the props.conf LINE_BREAKER attribute to delimit multi-line events, the SHOULD_LINEMERGE attribute should be set to what?
- A . Auto
- B . None
- C . True
- D . False
Correct Answer: D
D
Explanation:
When using the props.conf LINE_BREAKER attribute to delimit multi-line events, the SHOULD_LINEMERGE attribute should be set to false. This tells Splunk not to merge events that have been broken by the LINE_BREAKER. Setting the SHOULD_LINEMERGE attribute to true, auto, or none will cause Splunk to ignore the LINE_BREAKER and merge events based on other criteria. For more information, see Configure event line breaking in the Splunk documentation.
D
Explanation:
When using the props.conf LINE_BREAKER attribute to delimit multi-line events, the SHOULD_LINEMERGE attribute should be set to false. This tells Splunk not to merge events that have been broken by the LINE_BREAKER. Setting the SHOULD_LINEMERGE attribute to true, auto, or none will cause Splunk to ignore the LINE_BREAKER and merge events based on other criteria. For more information, see Configure event line breaking in the Splunk documentation.