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Splunk SPLK-2002 Exam Questions
- Topic 1: Introduction: This section of the exam measures the skills of the Enterprise Solutions Architect and covers the foundational understanding of planning and executing a Splunk deployment. It introduces key concepts, including the definition of deployment plans and outlines the overall process.
- Topic 2: Project Requirements: This section evaluates the competencies of the Splunk Administrator and focuses on identifying environment-specific needs such as user volume and technical requirements. It includes the use of checklists and available resources to ensure all deployment needs are clearly understood.
- Topic 3: Infrastructure Planning: Index Design: Designed for the Enterprise Solutions Architect, this section addresses how to design and size indexes correctly. It also covers estimating storage requirements unrelated to smart store configurations and understanding relevant apps for deployment.
- Topic 4: Infrastructure Planning: Resource Planning: This domain assesses the expertise of the Enterprise Solutions Architect and deals with sizing considerations, hardware specifications, and storage needs for different Splunk components. It also considers security, privacy, and specialised sizing for apps like ES and ITSI.
- Topic 5: Clustering Overview: This section is intended for the Splunk Administrator and provides knowledge about search head clustering and related storage needs that are not smart store-specific. It introduces key concepts essential for managing clustered environments.
- Topic 6: Forwarder and Deployment Best Practices: Aimed at the Splunk Administrator, this section covers best practices for designing the forwarder tier and managing Splunk components using deployment tools. It emphasises effective configuration management.
- Topic 7: Performance Monitoring and Tuning: This section of the exam measures the skills of the Splunk Administrator and focuses on optimizing performance using configuration files such as limits.conf, indexes.conf, and props.conf. It also includes methods to improve search efficiency.
- Topic 8: Splunk Troubleshooting Methods and Tools: Designed for the Splunk Administrator, this domain provides understanding of available Splunk diagnostic tools and resources essential for identifying and resolving issues effectively.
- Topic 9: Clarifying the Problem: This section targets the Splunk Administrator and includes identifying relevant internal logs and indexes within Splunk. It supports accurate root cause analysis during troubleshooting.
- Topic 10: Licensing and Crash Problems: This section assesses the abilities of the Splunk Administrator to identify and resolve issues related to licensing limits and platform crashes during deployment and daily operations.
- Topic 11: Configuration Problems: This domain evaluates the Splunk Administrator's understanding of input configuration issues that may arise during deployment or log collection stages.
- Topic 12: Search Problems: Aimed at the Splunk Administrator, this section explores challenges related to search performance and introduces the Job Inspector tool to investigate query-related problems.
- Topic 13: Deployment Problems: This section focuses on the Splunk Administrator and includes diagnosing issues related to data forwarding and deployment server operations.
- Topic 14: Large-scale Splunk Deployment Overview: This domain measures the Enterprise Solutions Architect’s ability to design and manage Splunk server roles and configure license masters effectively in clustered environments.
- Topic 15: Single-site Indexer Cluster: Intended for the Enterprise Solutions Architect, this section introduces the key aspects of configuring a Splunk single-site indexer cluster, covering essential operational settings.
- Topic 16: Multisite Indexer Cluster: This domain is designed for the Enterprise Solutions Architect and provides knowledge of multisite cluster configurations, including upgrades, migration, and redundancy planning.
- Topic 17: Indexer Cluster Management and Administration: This section assesses the Splunk Administrator’s skills in managing indexer clusters, including monitoring, peer management, app bundle handling, and storage utilisation strategies.
- Topic 18: Search Head Cluster: Targeted at the Enterprise Solutions Architect, this domain explores the architecture and configuration of search head clusters, necessary for scaling searches across large deployments.
- Topic 19: Search Head Cluster Management and Administration: Designed for the Splunk Administrator, this section covers day-to-day operations such as managing the deployer, handling captaincy, and maintaining or removing search head members.
- Topic 20: KV Store Collection and Lookup Management: This final section measures skills of the Splunk Administrator in managing KV Store collections within clustered Splunk environments, supporting dynamic data storage and lookup functionalities.
Free Splunk SPLK-2002 Exam Actual Questions
Note: Premium Questions for SPLK-2002 were last updated On Nov. 04, 2026 (see below)
Which of the following is true regarding Splunk Enterprise's performance? (Select all that apply.)
The following statements are true regarding Splunk Enterprise performance:
Adding search peers increases the search throughput as search load increases. This is because adding more search peers distributes the search workload across more indexers, which reduces the load on each indexer and improves the search speed and concurrency.
Adding search heads provides additional CPU cores to run more concurrent searches. This is because adding more search heads increases the number of search processes that can run in parallel, which improves the search performance and scalability. The following statements are false regarding Splunk Enterprise performance:
Adding search peers does not increase the maximum size of search results. The maximum size of search results is determined by the maxresultrows setting in the limits.conf file, which is independent of the number of search peers.
Adding RAM to an existing search head does not provide additional search capacity. The search capacity of a search head is determined by the number of CPU cores, not the amount of RAM. Adding RAM to a search head may improve the search performance, but not the search capacity. For more information, seeSplunk Enterprise performancein the Splunk documentation.
When Splunk indexes data in a non-clustered environment, what kind of files does it create by default?
When Splunk indexes data in a non-clustered environment, it creates index and .tsidx files by default. The index files contain the raw data that Splunk has ingested, compressed and encrypted. The .tsidx files contain the time-series index that maps the timestamps and event IDs of the raw data. The rawdata and index files are not the correct terms for the files that Splunk creates. The compressed and .tsidx files are partially correct, but compressed is not the proper name for the index files. The compressed and meta data files are also partially correct, but meta data is not the proper name for the .tsidx files.
(Which of the following data sources are used for the Monitoring Console dashboards?)
According to Splunk Enterprise documentation for the Monitoring Console (MC), the data displayed in its dashboards is sourced primarily from two internal mechanisms --- REST API calls and metrics.log.
The Monitoring Console (formerly known as the Distributed Management Console, or DMC) uses REST API endpoints to collect system-level information from all connected instances, such as indexer clustering status, license usage, and search head performance. These REST calls pull real-time configuration and performance data from Splunk's internal management layer (/services/server/status, /services/licenser, /services/cluster/peers, etc.).
Additionally, the metrics.log file is one of the main data sources used by the Monitoring Console. This log records Splunk's internal performance metrics, including pipeline latency, queue sizes, indexing throughput, CPU usage, and memory statistics. Dashboards like ''Indexer Performance,'' ''Search Performance,'' and ''Resource Usage'' are powered by searches over the _internal index that reference this log.
Other tools listed --- such as btool (configuration troubleshooting utility) and diag (diagnostic archive generator) --- are not used as runtime data sources for Monitoring Console dashboards. They assist in troubleshooting but are not actively queried by the MC.
Reference (Splunk Enterprise Documentation):
* Monitoring Console Overview -- Data Sources and Architecture
* metrics.log Reference -- Internal Performance Data Collection
* REST API Usage in Monitoring Console
* Distributed Management Console Configuration Guide
(What is the expected performance reduction when architecting Splunk in a virtualized environment instead of a physical environment?)
The Splunk Enterprise Capacity Planning Manual states that running Splunk in a virtualized environment typically results in a performance reduction of approximately 20% to 45% compared to equivalent deployments on physical hardware.
This degradation is primarily due to the virtualization overhead inherent in hypervisor environments (such as VMware, Hyper-V, or KVM), which can affect:
Disk I/O throughput and latency --- the most critical factor for indexers.
CPU scheduling efficiency, particularly for multi-threaded indexing processes.
Network latency between clustered components.
Splunk's documentation strongly emphasizes that while virtualized environments offer operational flexibility, they cannot match bare-metal performance, especially under heavy indexing loads.
To mitigate performance loss, Splunk recommends:
Reserving dedicated CPU and I/O resources for Splunk VMs.
Avoiding over-commitment of hardware resources.
Using high-performance SSD storage or paravirtualized disk controllers.
These optimizations can narrow the performance gap, but a 20--45% reduction remains a realistic expectation under typical conditions.
Reference (Splunk Enterprise Documentation):
* Splunk Enterprise Capacity Planning Manual -- Virtualization Performance Considerations
* Splunk on Virtual Infrastructure -- Best Practices and Performance Tuning
* Indexer and Search Head Hardware Recommendations
* Performance Testing Guidelines for Splunk Deployments
If .delta replication fails during knowledge bundle replication, what is the fall-back method for Splunk?
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 works2: Start and stop Splunk Enterprise3: Restart the KV store
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