Splunk Core Certified Consultant (SPLK-3003) practice questions

Exam overview SPLK-3003

Domain coverage 8 domains

• Introduction (5%)
• Monitoring Console (8%)
• Security and Users (8%)
• Data Ingestion (15%)
• Event Processing (14%)
• Search Performance Optimization (14%)
• Deployments (18%)
• Search Head Clusters (10%)

Sample questions 12 of 113 shown

1. Q1 Deploying Splunk (5%)

   Define Splunk Validated Architectures (SVA). What is the purpose of Splunk Validated Architectures?

   1. To define minimum hardware requirements for Splunk deployments
   2. To provide tested and certified reference architectures for Splunk Enterprise deployments
   3. To list all compatible third-party software for Splunk
   4. To specify the default configuration settings for all Splunk instances

   Splunk Validated Architectures (SVA) are tested and certified reference architectures that provide proven deployment patterns for Splunk Enterprise. They help architects design reliable, scalable, and performant deployments based on Splunk's testing and validation, reducing risk in production environments.
2. Q2 Deploying Splunk (5%)

   Articulate how and why Splunk grows from standalone environment to distributed environment with indexer and search head clustering.

   1. A standalone deployment is sufficient for all enterprise needs
   2. As data volume and user count grow, Splunk should be scaled from standalone to distributed by separating indexers and search heads, and eventually adding clustering for high availability and scale
   3. Distributed deployments are less reliable than standalone deployments
   4. Clustering is only needed for search performance, not data redundancy

   As data volume grows and more users access Splunk, a standalone deployment becomes insufficient. The natural evolution is to separate indexers and search heads, add forwarders for data collection, and implement indexer clustering for data redundancy and search head clustering for high availability and search capacity.
3. Q3 Deploying Splunk (5%)

   Explain the difference between high availability and disaster recovery and how both can be addressed in Splunk.

   1. HA and DR are the same concept in Splunk
   2. HA ensures continuous operation during component failures (via clustering), while DR ensures data and service recovery after a catastrophic site failure (via multi-site clustering and backup strategies)
   3. HA is only for search heads; DR is only for indexers
   4. Neither HA nor DR can be achieved with Splunk

   High Availability (HA) in Splunk addresses component-level failures through indexer clustering (replication factor) and search head clustering (multiple members). Disaster Recovery (DR) addresses site-level failures through multi-site indexer clustering with site_replication_factor and site_search_factor settings, ensuring data and service continuity across geographic locations.
4. Q4 Deploying Splunk (5%)

   Which of the following represents the correct PS best practice mapping for Splunk roles to functions?

   1. Indexer → Search, Search Head → Index, Forwarder → Collect
   2. Indexer → Index, Search Head → Search, Forwarder → Collect
   3. Indexer → Collect, Search Head → Index, Forwarder → Search
   4. Indexer → Search, Search Head → Collect, Forwarder → Index

   In Splunk's architecture, the indexer role is responsible for indexing (processing and storing data), the search head role is responsible for executing searches and presenting results, and forwarders are responsible for collecting data from sources and forwarding it to indexers.
5. Q5 Deploying Splunk (5%)

   In preparation for the deployment of a new environment for a customer, which approach should be used per PS best practices?

   1. Deploy all components on a single server and scale later
   2. Plan the architecture based on requirements gathering, data volume estimates, and use case identification
   3. Use the default configuration for all components without planning
   4. Deploy the maximum number of indexers regardless of data volume

   Per Splunk Professional Services best practices, deployment planning should start with thorough requirements gathering including data sources, volume estimates, user counts, and use cases. The architecture is then designed based on these requirements to ensure proper sizing, performance, and scalability.
6. Q6 Deploying Splunk (5%)

   In a multi-tiered Splunk architecture, which components should be separated for optimal performance?

   1. Deployment server and license master
   2. Search head, indexer, and forwarder functions should be on separate tiers
   3. All components should run on the same server
   4. Only forwarders should be separated

   In a multi-tiered Splunk architecture, search head, indexer, and forwarder functions should be separated onto different tiers for optimal performance, scalability, and resource allocation. This allows each component to be sized and managed independently based on its workload requirements.
7. Q7 Monitoring Console (8%)

   How does Monitoring Console (MC) initially identify the server role(s) of a new Splunk instance?

   1. The MC uses a REST endpoint to query the server
   2. Roles are manually assigned within the MC
   3. Roles are read from distsearch.conf
   4. The MC assigns all possible roles by default

   The Monitoring Console identifies the server role(s) of a new Splunk instance by using a REST endpoint to query the server. This automatic discovery process allows the MC to determine whether an instance is an indexer, search head, cluster master, or other role.
8. Q8 Monitoring Console (8%)

   Monitoring Console (MC) health check configuration items are stored in which configuration file?

   1. healthcheck.conf
   2. alert_actions.conf
   3. distsearch.conf
   4. checklist.conf

   MC health check configuration items are stored in checklist.conf. This file defines the health checks that the Monitoring Console performs, including their thresholds, frequency, and the conditions under which alerts are triggered.
9. Q9 Monitoring Console (8%)

   Which instance is suitable to configure as the Monitoring Console in a Splunk deployment?

   1. A dedicated standalone instance
   2. The cluster master node
   3. A production search head
   4. The deployer sharing with the cluster master

   The Monitoring Console should ideally be installed on a dedicated standalone instance for optimal performance. While it can be installed on a search head or cluster master, a dedicated instance ensures that monitoring does not impact production search or clustering operations.
10. Q10 Monitoring Console (8%)

    In a single indexer cluster, where should the Monitoring Console (MC) be installed?

    1. Deployer sharing with master cluster
    2. License master that has 50 clients or more
    3. Cluster master node
    4. Production search head

    In a single indexer cluster, the Monitoring Console can be installed on the cluster master node. This provides easy monitoring access to all cluster components. For larger deployments, a dedicated MC instance is recommended.
11. Q11 Monitoring Console (8%)

    In an environment that has Indexer Clustering, the Monitoring Console (MC) provides dashboards to monitor environment health. As the environment grows over time and new indexers are added, which steps would ensure the MC is aware of the additional indexers?

    1. No changes are necessary; the Monitoring Console has self-configuration capabilities
    2. Using the MC setup UI, review and apply the changes
    3. Remove and re-add the cluster master from the indexer clustering UI page to add new peers, then apply the changes under the MC setup UI
    4. Each new indexer needs to be added using the distributed search UI, then settings must be saved under the MC setup UI

    When new indexers are added to a cluster, the MC setup UI should be used to review and apply configuration changes. The MC identifies servers through server roles, and applying changes in the MC setup ensures the new indexers are properly registered for monitoring.
12. Q12 Monitoring Console (8%)

    Describe how Monitoring Console uses server roles and groups.

    1. MC assigns random roles to discovered instances
    2. MC uses server roles (search head, indexer, cluster master, etc.) and groups to organize and monitor instances, applying appropriate dashboards and health checks based on each role
    3. Server roles in MC are only used for display purposes
    4. MC only monitors instances with the "indexer" role

    The Monitoring Console uses server roles to determine which dashboards and health checks apply to each instance. For example, indexers get indexing performance dashboards, search heads get search performance dashboards, and the cluster master gets cluster health dashboards. Groups allow logical organization of instances.

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