Common Splunk Interview Questions to Expect in 2023 - IQCode

Overview of Splunk and Its Significance in the Era of Machine Data

Splunk is a software platform tool that allows users to extract valuable business insights and analytics from large volumes of machine data generated by IoT devices, servers, and other sources. Splunk has gained significant prominence in recent years due to the surge of machine data from the IT infrastructure. This article aims to provide an overview of Splunk and answer frequently asked Splunk interview questions for both freshers and experienced candidates.

What is Splunk?

Splunk is a platform tool used for accessing, analyzing, and visualizing machine-generated data from multiple sources. It has been designed to transform machine data into powerful operational intelligence that offers real-time insights and analytics. Splunk is widely used for searching, monitoring, and reporting enterprise data.

Splunk's capabilities include application management, security and compliance, business and web analytics, among others. One of its essential features is its centralized indexing system, which eliminates the need for a separate database to store data, making it easy to search and retrieve specific information from vast amounts of data.

In summary, if an organization wants to make the best use of machine data, Splunk is an indispensable tool for achieving that goal.

Explanation of how Splunk works:

Splunk is a software that analyzes and searches through massive amounts of data. It can ingest data from various sources, such as logs and metrics, and provide insights into the data by creating visualizations, alerts, and reports.

Splunk works in three simple steps:

1. Data Input: Splunk can receive data from various sources, such as files, databases, APIs, and network streams. It can ingest structured and unstructured data as well as real-time and historical data.

2. Indexing: Splunk indexes the data it receives, making it easy to search and analyze. The indexing process applies metadata to the data, such as the source, time of creation, and location.

3. Searching and Analysis: Once data is indexed, Splunk can quickly search and analyze it using its powerful search language. Splunk provides various tools to visualize data, such as charts, graphs, and dashboards, to provide insights into the data.

Overall, Splunk can help organizations make better decisions by giving them visibility into their data and allowing them to make informed decisions based on that data.

Main Components of Splunk Architecture

Splunk architecture consists of three main components: - Forwarders: They collect, transform, and send the data to the indexer. - Indexers: They store and index the data received from the forwarders. - Search Heads: They provide a graphical user interface to search, analyze, and visualize the data stored in the indexers. These components work together to efficiently collect, store, and analyze large amounts of machine-generated data.

Splunk Forwarder Types

In Splunk, there are different types of forwarders that serve different purposes for data collection. These include:

1. Universal Forwarder: This is the most common type of forwarder used to collect data from various sources and send it to a Splunk indexer for indexing and further analysis.

2. Heavy Forwarder: This type of forwarder is used when additional processing of data is required before forwarding it to an indexer. Heavy forwarders can run scripts, filter data, and perform other actions on data.

3. Light Forwarder: This type of forwarder is a lightweight version of the universal forwarder and is used to collect data from a limited number of sources.

4. Deployment Server: This type of forwarder is used to deploy and manage configurations for Splunk forwarders across a network.

It's important to choose the appropriate forwarder type based on your specific data collection requirements and environment.

Advantages of using forwarders to get data into a Splunk instance

Forwarders offer several advantages when it comes to getting data into a Splunk instance, including:

1. Reduced network bandwidth: Forwarders allow for the efficient and secure transfer of data over the network, without the need to transfer the entire dataset every time new data is added.

2. Improved performance: By offloading data input processing to forwarders, heavy data input loads can be distributed across multiple endpoints, reducing the processing load on the central Splunk instance and improving overall performance.

3. Enhanced security: Forwarders can be configured to ensure secure communication and metadata protection throughout the data transfer process.

4. Greater flexibility: Forwarders can be configured to handle a variety of data inputs, including log files, network traffic, and scripted inputs, making it easier to collect and analyze data from multiple sources.

Overall, using forwarders can help organizations maximize the value and effectiveness of their Splunk instance by streamlining data input, improving performance and security, and enabling greater flexibility in data collection and analysis.

Splunk Dashboards: Overview and Types

In Splunk, a dashboard is a visual representation of data that allows users to analyze and monitor their data from various sources. There are several types of dashboards in Splunk:

1. Simple XML Dashboards: These are the most common type of dashboards in Splunk and are created using Simple XML code.

2. Advanced XML Dashboards: These dashboards provide greater flexibility and control over the layout and style of the dashboard, and are created using Advanced XML code.

3. JavaScript/CSS Dashboards: These dashboards use custom code written in JavaScript and CSS to create highly customized and interactive dashboards.

Overall, Splunk dashboards are a powerful tool for data analysis and monitoring, allowing users to gain insights into their data quickly and efficiently.

Explanation of a Splunk Query

A Splunk query is a search command that is used to extract and analyze data from various sources like logs, events, and metrics. The Splunk query language is very powerful and flexible, it allows users to perform simple as well as complex searches using different search commands, operators, and functions.

A Splunk query is composed of three key components: search, filter, and result. The search component defines the data sources that are searched, including indexes, data sources, and time ranges. The filter component is used to narrow down the search results by applying specific search criteria like keywords, fields, and tags. Finally, the result component specifies how the data should be processed and presented, like charts, tables, or raw data.


Suppose you want to search for all the errors in a web server logs. Using the Splunk query language, you can write a query like this:

index=web_logs error

In this query, “index=web_logs” specifies the source of data, and “error” identifies a search term to find all the logs that contain the error keyword. This will return all the log entries that contain the word “error” within the indexed web_logs.

Overall, Splunk queries provide insights into operational characteristics and user behavior from a large amount of data sources.

Different Types of Splunk License

Splunk offers several types of licenses based on the specific requirements of the organization. The main types of licenses include:

  • Free Splunk License: This license is free to use and is perfect for small businesses or personal projects.
  • Enterprise Splunk License: This license is designed for large organizations with complex needs and offers a wide range of features and capabilities.
  • Cloud Splunk License: This license is a cloud-based offering and is perfect for organizations that want the flexibility of Splunk in a cloud environment.
  • Trial Splunk License: This license is valid for a specific amount of time and allows users to test the features before committing to a specific license type.

It is essential to choose the right license type for your organization to ensure that you have the necessary features and capabilities for your specific needs.

Importance of License Master in Splunk

The License Master in Splunk is important because it manages and distributes licenses to all the other Splunk instances in an organization. It ensures that the Splunk deployments are compliant with the license agreement and that the indexing volume and features being used are properly licensed.

If the License Master becomes unreachable, it can lead to the other instances losing their licensing information and being unable to perform certain functions such as indexing. It's important to have redundancy and disaster recovery measures in place for the License Master to ensure that it remains accessible and operational.

Explaining License Violation and Troubleshooting

A license violation occurs when a user or organization violates the terms of a software license agreement. This can happen when the user exceeds the number of permitted installations or when they use the software in a manner that is not allowed by the agreement.

To handle or troubleshoot a license violation warning, the first step is to review the license agreement and determine what specific terms were violated. Then, the appropriate action must be taken to rectify the violation, such as purchasing additional licenses, uninstalling the software from unauthorized machines, or changing the way the software is being used.

It is important for individuals and organizations to adhere to software license agreements to avoid legal consequences and negative impacts on business operations.

Common Splunk Ports

These are some of the commonly used ports for Splunk:

TCP 8089 - Splunk's management port for accessing the management interface, including the REST API.

TCP 9997 - Port used by the Splunk Forwarder to send data to the Splunk Indexer.

TCP 8088 - HEC (HTTP Event Collector) port used by Splunk to collect events over HTTP.

TCP 514 - Port used for receiving syslog data from other systems.

Explanation of Splunk DB Connect

Splunk DB Connect is a tool that allows users to integrate Splunk with relational databases. With DB Connect, users can create inputs to pull data from databases, as well as outputs to write data back to databases. This tool supports a wide range of databases and database versions, including MySQL, Oracle, PostgreSQL, Microsoft SQL Server, and SAP HANA.

DB Connect works by using a JDBC driver to establish a connection with the database, and then executing SQL queries to retrieve or write data. Users can configure inputs to run on a schedule, or they can be triggered manually. Outputs can be configured to write data back to the database, or to an external file.

DB Connect also includes a UI for configuring inputs and outputs, as well as a set of pre-built queries for common use cases, such as importing data from Salesforce or ServiceNow. This makes it easier for users to get started with DB Connect, without needing to know SQL or other database-specific syntax.

Overall, Splunk DB Connect is a powerful tool for integrating Splunk with relational databases, allowing users to easily incorporate data from outside sources into their Splunk-based workflows.

Splunk Product Versions

The Splunk software comes in different versions, including Enterprise, Cloud, and Light. Each version caters to different user needs and requirements. The Enterprise version offers advanced features and comprehensive functionalities, ideal for large enterprises. The Cloud version is a subscription-based service hosted by Splunk, providing users with a cloud-based solution without the need for on-premise infrastructure. The Light version, also known as Splunk Free, is a freely available version with limited capabilities, suitable for small-scale or individual use.

Features not available in Splunk Free

Some of the features that are not available in the free version of Splunk are:

- Distributed search
- Search head clustering
- Indexer clustering
- Multi-site indexer clustering
- Advanced deployment management
- Monitoring console
- Splunk Enterprise Security
- Splunk IT Service Intelligence
- Machine learning toolkit
- Customization options for dashboards and visualizations

Splunk Alerts: Explanation and Available Options

Splunk alerts are notifications that are triggered based on specific search criteria. They help in identifying issues in real-time and can be configured to notify specific users or groups via various communication channels, such as email, SMS, or Slack.

There are several types of alerts available in Splunk, including scheduled alerts, threshold alerts, and real-time alerts. Here are some of the options available while setting up alerts:

1. Alert Type: As mentioned, the type of alert you choose will depend on your requirements. Scheduled alerts run at specified intervals, threshold alerts trigger notifications based on specific conditions, and real-time alerts trigger notifications as soon as a condition is met.

2. Search Criteria: This is the specific search that will trigger the alert. It can be simple or complex, depending on your requirements. You can also specify search parameters such as time range and indexes.

3. Trigger Conditions: This refers to the conditions that will trigger the alert based on the search criteria. For example, you can set up a threshold alert to trigger when the number of errors exceeds a specific value.

4. Notification Channels: You can choose how you want to receive the alert notifications - via email, SMS, or any other custom channel.

5. Schedule: For scheduled alerts, you can specify the interval at which the alert should run.

6. Actions: You can specify actions that should be taken when an alert is triggered, such as running a script or sending data to a third-party system.

Setting up alerts is a crucial step in making the most of Splunk's capabilities. With the right alerts in place, you can ensure timely identification of issues, leading to faster resolution and better system availability.

Understanding Summary Index in Splunk

In Splunk, a summary index is a secondary index that is created to store the summarized or aggregated data of your primary index. This summarized data can then be easily searched and analyzed without overloading or slowing down the primary index.

The summary index is created by defining a saved search containing the summary or aggregated data. The saved search is then run on a schedule to populate the summary index with the latest data.

Using a summary index provides several benefits, including faster searches of summarized data, reducing load on the primary index, and allowing historical data to be summarized so that long-term trends can be analyzed. Overall, it's an effective way to make your searches and analysis faster and more efficient in Splunk.

Excluding Events from Splunk Indexing

To exclude specific events from being indexed by Splunk, use the configurations available in the props.conf or transforms.conf files. These files can be edited directly in the system or through the Splunk web GUI. In props.conf, use the "TRANSFORMS-null" stanza to discard the event, while in transforms.conf, use the "REGEX" transform to match specific events and prevent them from being indexed. Additionally, custom scripts can also be used to filter and exclude events from being forwarded to Splunk.

Commands to Start/Stop Splunk Service

To start the Splunk service, run the following command in the terminal:

sudo systemctl start splunk

To stop the Splunk service, run the following command:

sudo systemctl stop splunk

Note: You might need to use


for administrative privileges to start/stop the Splunk service.

Importance of Time Zone Property in Splunk

The time zone property is a crucial aspect of Splunk, especially for systems and applications that operate across different time zones. It enables Splunk to convert timestamps appropriately and ensure consistency across all data sources. The correct time zone property ensures accurate reporting, effective correlation of events, and reliable troubleshooting of time-sensitive issues. In summary, the time zone property is vital for the proper functioning of Splunk, and its value must be set correctly.

Explaining the difference between Splunk App and Add-On

An add-on is a collection of specific features or functionalities that are designed to be integrated with an existing application. In the case of Splunk, an add-on aims to develop highly-specialized functionality to extend the capacity of core Splunk features.

On the other hand, a Splunk App is a complete package that includes a combination of dashboards, reports, saved searches, field extractions, and visualizations that provide full access to Splunk's features and functionalities. Splunk Apps may also include integrated add-ons, but their primary purpose is to provide a broader and richer user experience.

// Example of Splunk App and Add-On

(Splunk App)


(Splunk Add-On)

In this example,


is a complete Splunk package that provides a suite of features and functionalities to the Splunk user.


has been specifically designed to extend the capability of that app.

List of Important Configuration Files in Splunk

In Splunk, configuration files are used to specify and customize system and application settings. Some of the important configuration files that are used in Splunk are:


This file is used to configure web server settings such as ports, SSL, and authentication.


This file is used to define data inputs such as log files, network ports, and scripts that collect data.


This file is used to configure index settings such as storage locations, retention policies, and access control.


This file is used to define how data is processed and indexed, such as data transformations, sourcetypes, and field extractions.


This file is used to define custom transformations for data such as renaming, filtering, and masking.


This file is used to configure user authentication settings such as LDAP, SSO, and multi-factor authentication.


This file is used to configure server settings such as system resources, distributed search, and deployment apps.

These are just a few examples of the many configuration files that are used in Splunk. Understanding how to configure and customize these files is essential for effective use and administration of a Splunk environment.

Splunk Interview Questions for Experienced


is a popular tool used for searching, analyzing, and visualizing machine-generated data, such as log files. Below is one of the most commonly asked questions in a



Question 22: What are


commands, and what are some of the basic





commands are used to perform various operations on the data indexed in


. Here is a list of some of the basic



  • search

    : This command is used to search for data in Splunk.

  • index

    : This command is used to define the data that you want to index.

  • stats

    : This command is used for statistical operations like count, sum, average, and more.

  • eval

    : This command is used to evaluate or create new fields from existing fields.

  • timechart

    : This command is used to create time-based charts.

  • top

    : This command is used to display the top values of a field.

  • where

    : This command is used to filter the results of a search based on a condition.

These are just a few of the many


commands available. A


professional should have a good understanding of these commands and be able to use them effectively to analyze and extract valuable insights from machine-generated data.

Important Splunk Search Commands

Here are some of the important Splunk search commands:

index: <index_name>
source: <source_name>
sourcetype: <sourcetype_name>
earliest: <time_string>
latest: <time_string>
search: <search_string>
field: <fieldname>
rex: '<regular_expression>'<string>
dedup <fieldname>
top <number> <fieldname>

The above-mentioned commands can be used to search, filter, modify and visualize data in Splunk.

Differences between the stats and eventstats commands





commands are both used in Splunk to perform statistical analysis on the search results. However, there are some differences between these two commands:

  • stats

    command is used to calculate the aggregation of values over the entire search result set or a subset of it based on one or more fields.

  • eventstats

    command is used to add new statistical fields to each event or group of events in the search results rather than to summarize data.

  • stats

    command displays fields that are specified in the search, while


    command can display external fields that were not initially searched.

  • stats

    command is used after the event grouping while


    command is used for the calculation of statistics during the event grouping.

  • stats

    command can be used to calculate Summary Indexes while






are used for different purposes and should be selected depending on the required search result.

Commands in the "Filtering Results" category:


: Searches input files for lines matching a pattern and prints them.


: Searches input files for lines matching an extended regular expression and prints them.


: Searches input files for lines matching a fixed string and prints them.


: Filters adjacent matching lines from input.


: Sorts input.


: Translates or deletes characters from input.


: Searches files for lines that contain a specified pattern and performs specified actions on matching lines.


: Stream editor for filtering and transforming text based on a set of rules.

Explanation of Lookup Command and Differences between Inputlookup and Outputlookup Commands

The Lookup command is used in Splunk to combine fields from different data sources based on a common field. It is useful for creating reports that involve data from multiple sources, as it allows you to combine the data in a meaningful way.

There are two types of Lookup commands in Splunk: Inputlookup and Outputlookup.

The Inputlookup command is used to retrieve data from a lookup table and combine it with other data in a search. This is useful when you have a lookup table that contains additional information about your data, such as IP addresses, hostnames, or user IDs. You can use the Inputlookup command to combine the data from the lookup table with your search results.

The Outputlookup command is used to create or modify a lookup table based on the results of a search. This is useful when you want to save the results of a search as a lookup table for later use. The Outputlookup command can also be used to overwrite an existing lookup table or append data to an existing lookup table.

In summary, the Lookup command is used to combine fields from different data sources based on a common field, while Inputlookup and Outputlookup are two specific types of Lookup commands used for retrieving data from and creating/modifying lookup tables, respectively.

Splunk Btool Explained

Splunk Btool is a command-line utility tool that is used to extract configuration settings from different components of the Splunk environment. It can be used to troubleshoot configuration issues and also helps in understanding how different settings are configured in the system.

Btool extracts the details about the configuration files and the effective configurations that are applied to the data processing configuration files. It can help in understanding the hierarchy of configuration and how the configurations are inherited in the environment.

For example, suppose we want to know the configurations that are applied to a particular input file, we can use the Btool command to extract the details. Btool provides the option to validate the configurations for file settings, which helps in troubleshooting the configuration issues and uncovering configuration misconfigurations in the environment.

Overall, Splunk Btool can be used as a powerful tool to help system administrators and power-users in troubleshooting, performing debugging and understanding Splunk configurations.

Understanding File Precedence in Splunk

In Splunk, file precedence determines the order in which configuration files are loaded and processed. When multiple configuration files have the same setting or stanza, Splunk will use the value in the file with higher precedence.

There are default precedence settings for different types of configuration files in Splunk, but you can also adjust file precedence by placing configuration files in specific locations or by renaming them with a specific prefix or suffix.

It's important to understand file precedence when configuring your Splunk environment, as it can impact how your data is indexed and how your searches and reports are generated. Make sure to review the Splunk documentation on file precedence for more information on how to manage and control file precedence in your environment.

State the Differences between ELK and Splunk

Splunk and ELK are both popular tools used to process and analyze log files. However, there are some key differences between them:

  • Licensing: Splunk is proprietary software with costly licensing, while ELK is open-source and free.
  • Scalability: ELK has better horizontal scalability since it can be set up to handle a large number of log files with relative ease. Splunk, on the other hand, can be more challenging to scale horizontally.
  • Data Ingestion Techniques: Splunk has a wide variety of data ingestion techniques available out of the box, while ELK requires additional plugins to handle different data sources.
  • User Interface: Splunk has an easier-to-use and more polished interface, while ELK requires more technical knowledge and configuration to get up and running.
  • Learning Curve: While both tools can be challenging to learn, they have different learning curves. Splunk has more online resources and built-in training, making it easier for new users to learn. ELK may require more time and technical expertise to master.

Dispatch Directory

The dispatch directory is a part of the WordPress file system that contains all of the files related to the handling of requests to the website. It is responsible for routing HTTP requests to the appropriate files and functions, ensuring that the correct content is sent back to the user. This directory contains index.php, wp-blog-header.php, and other files that are responsible for loading WordPress and the appropriate theme or plugin. It is an essential component of the WordPress CMS, and any changes or modifications to this directory should be done with caution to avoid breaking the site's functionality.

State the Difference Between Search Head Pooling and Search Head Clustering

Search Head Pooling and Search Head Clustering are two different methods used in the distributed search architecture in Splunk.

Search Head Pooling: In Search Head Pooling, multiple Search Heads are configured to share the load and balance the user requests. The user request is passed on to one of the Search Heads, which then performs the search and returns the result to the user. Multiple Search Heads in the pool operate independently and do not share search artifacts, such as report acceleration or KV store data.

Search Head Clustering: On the other hand, Search Head Clustering is designed to provide a high availability and disaster recovery solution. In Search Head Clustering, multiple Search Heads are joined into a cluster and act as a single virtual Search Head. Users can connect to any node in the cluster, and the cluster automatically directs the user requests to the appropriate node. Clustered Search Heads also share search artifacts and configurations across the nodes in the cluster, which makes it easier to manage and maintain the environment.

In summary, Search Head Pooling is used to balance the search load among multiple Search Heads, while Search Head Clustering provides a highly available and disaster-resistant architecture by joining multiple Search Heads into a single entity.

Explanation of SF (Search Factor) and RF (Replication Factor)

In the context of distributed systems, SF (Search Factor) refers to the number of nodes that must be searched to satisfy a read request. RF (Replication Factor) refers to the number of copies that are made of each piece of data in the system.

For example, if a system has an SF of 2 and an RF of 3, it means that when a read request is made, at least 2 nodes must respond with the requested data to consider the request fulfilled. Additionally, each piece of data will have 3 copies distributed throughout the system to ensure redundancy and fault tolerance.

These factors play an important role in designing and optimizing distributed systems, and must be carefully considered to ensure efficient and reliable system operation.

Explanation of Fish Bucket and Fish Bucket Index

In the context of networking, a fish bucket refers to a mechanism that captures traffic that matches a specific set of criteria, such as a particular source or destination IP address, port number, or protocol type. This mechanism is commonly used in intrusion detection and prevention systems (IDPS) to identify suspicious or malicious network traffic.

A fish bucket index is a database-like structure that stores information about captured traffic, such as the date and time of capture, the source and destination IP addresses, the protocol type, and other relevant metadata. This index can be used to quickly search and retrieve captured traffic data, allowing security analysts to investigate potential threats more efficiently.

Overall, the fish bucket and fish bucket index are important tools in network security for identifying and mitigating potential threats.

Understanding Buckets in Splunk and their Lifecycle

In Splunk, buckets are logical partitions of data that are created to help the search process be more efficient. They are responsible for storing raw data that has been indexed by Splunk, and they can be located in multiple locations depending on the system configuration.

The bucket lifecycle includes four phases:

1. Hot Phase - During this phase, data is continuously indexed in a bucket. This is the first phase of the bucket lifecycle, and it lasts for a pre-defined period of time or until the bucket reaches a certain size limit. By default, this period is 10 days, but it can be modified based on the administrator's requirements.

2. Warm Phase - After the hot phase, the bucket enters the warm phase. During this phase, the bucket is no longer actively indexed, but it's still available for search. The warm phase is where the data is stored for a pre-defined time period until it's archived or moved to cold storage.

3. Cold Phase - Once the bucket enters the cold phase, it's no longer available for search, but it's still stored in its original location on the disk. This phase is typically used for backup and disaster recovery purposes.

4. Frozen Phase - In the frozen phase, the data is no longer searchable, and the original data file is compressed to save disk space. The frozen data is moved to a different location, and cannot be queried unless it's thawed. The thawing process involves moving the data to a new bucket and decompressing it.

Understanding the bucket lifecycle is critical to ensure your Splunk environment has the correct retention policies, disk space allocation, and system performance.

Setting Default Search Time in Splunk 6

In Splunk 6, you can set the default search time by following these steps:

1. Log in to the Splunk web interface 2. Click on the "Settings" menu 3. Click on "Search & Reporting" under the "Settings" menu 4. Under the "Time Range" section, select "Defaults" 5. In the "Earliest Time" and "Latest Time" fields, enter the desired time range 6. Click "Save"

By setting the default search time in Splunk 6, you can ensure that all searches start with the same time range. This can save time and prevent errors when working with large amounts of data.

What is the most effective way to delete search history in Splunk?

To clear the search history in Splunk, follow these steps:

  1. Click on the "Settings" menu
  2. Select "Clear Search History" option
  3. Choose the time range (Last 24 hours, Last 7 days, Last 30 days, or All Time) for which you want to clear your search history
  4. Click "Clear"

This will remove all of your search history data from Splunk.

Resetting the Splunk Admin (Administrator) Password

If you need to reset the password for the Splunk admin account, you can follow these steps:

1. Log in to the Splunk server with a user account that has administrative privileges.

2. Open the Splunk console and click on "Settings" in the menu.

3. Click on "Access controls" under the "Security" tab.

4. Click on the "Users" tab and find the "admin" user account.

5. Click on the "Edit" button next to the "admin" user account.

6. Enter a new password in the "New Password" and "Confirm Password" fields.

7. Click on the "Save" button to save the new password for the admin account.

That's it! You should now be able to log in to the Splunk console with the new password for the admin account.

Explanation of how Splunk avoids duplicate indexing of logs

Splunk uses a unique identifier called a "circuit breaker" to avoid duplicate indexing of logs. The circuit breaker keeps track of the event data that has already been indexed in the Splunk environment.

When Splunk receives a new event log, it checks the circuit breaker to see if that event has already been indexed. If it has, the event is discarded to avoid duplication. If it hasn't, the event is indexed and the circuit breaker is updated to include the new event.

This method ensures that log data is not indexed multiple times, which would cause unnecessary resource usage and potential errors in search results. Additionally, Splunk provides configuration options for fine-tuning the circuit breaker and avoiding false positives.

Commands to Restart Splunk Web Server and Splunk Daemon

To restart Splunk Web Server and Splunk Daemon, use the following commands:

For Splunk Web Server:

sudo systemctl restart splunkweb

For Splunk Daemon:

sudo systemctl restart splunk

Make sure to run these commands with administrative privileges. Restarting these services may cause a temporary interruption in the Splunk service.

Commands for Enabling and Disabling Splunk Boot Start:

To enable Splunk to start at boot on Linux:

/opt/splunk/bin/splunk enable boot-start

To disable Splunk from starting at boot on Linux:

/opt/splunk/bin/splunk disable boot-start

On Windows, open cmd as Administrator and run the following command to enable Splunk boot-start:

splunk enable boot-start -auth <username>:<password>

And to disable Splunk boot-start on Windows:

splunk disable boot-start

Note: Make sure to replace <username> and <password> with valid Splunk credentials.

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