Splunk is an analytics platform for monitoring, searching, analyzing, and visualizing machine-generated big data from websites, applications, servers, and cloud services. It helps organizations to gain valuable insights from their data. Splunk provides real-time insights from streaming data and can be used to monitor and alert on any performance or security issues.
Audience
This Splunk tutorial is designed for beginners who have limited or no knowledge of the Splunk platform. In this tutorial, you will learn the basics of Splunk, how to install and configure Splunk, how to search and analyze data in Splunk, and how to use Splunk to monitor and alert on real-time data. You will also learn about Splunk’s features and capabilities, and how to use them to gain valuable insights from your data. By the end of this tutorial, you will be able to confidently use Splunk to monitor and analyze data.
Prerequisites
1. Basic knowledge of Linux/Unix commands
2. Understanding of data structures and algorithms
3. Basic knowledge of web technologies such as HTML, XML, and JSON
4. Knowledge of programming languages such as Python and JavaScript
5. Familiarity with databases such as MySQL and Oracle
6. Understanding of networking concepts such as TCP/IP and DNS
Splunk – Overview
Splunk is a software platform designed to search, analyze, and visualize machine-generated data such as logs, metrics, and events. It enables users to identify, investigate, and gain insights into their data in real time. Splunk is used to monitor, investigate, and troubleshoot IT systems and applications. It also provides visibility into user behavior and security threats. Splunk can be used to monitor, analyze, and act on data from any source, including cloud, big data, and IoT. It helps users to quickly identify and resolve performance and security issues, as well as gain insights into their operations.
Splunk is available in three different product categories
1. Splunk Enterprise: This is the flagship product of Splunk, which provides organizations with powerful operational intelligence for machine data. It can be used for log management, security, compliance, application performance, IT operations, and more.
2. Splunk Cloud: Splunk Cloud is a cloud-based platform that provides organizations with all the same capabilities of Splunk Enterprise but with the added benefits of elastic scalability, high availability, and secure access.
3. Splunk Light: Splunk Light is a lightweight version of Splunk Enterprise, designed for small to medium-sized businesses. It offers a limited set of features and is easy to install and use, with no additional hardware needed.
Splunk Features
1. Advanced Search: Splunk allows users to search through large data sets using powerful search commands and filtering options.
2. Dashboards and Visualizations: Splunk provides an easy-to-use interface for creating dashboards and visualizing data.
3. Data Management: Splunk provides a comprehensive data management solution, allowing users to store, index, and access data from multiple sources.
4. Scalability: Splunk can handle large volumes of data, allowing users to scale up or down quickly and easily.
5. Security: Splunk provides industry-standard security measures to protect user data.
6. Alerts and Reports: Splunk provides customizable alerting and reporting capabilities to quickly identify and respond to anomalies.
7. Machine Learning: Splunk provides a powerful machine learning platform to quickly analyze and identify patterns in data.
Splunk – Environment
Splunk is a popular data analysis and monitoring platform used by organizations to collect, index, and analyze data from a variety of sources. It can be used to gain insight into data generated by an organization’s infrastructure, applications, security systems, and more. The platform is designed to help users quickly access, search, and act on data. Splunk allows users to create dashboards, reports, alerts, and alerts to monitor and analyze data in real time. It also provides powerful analytics capabilities to help organizations uncover insights from their data. Splunk is available in both on-premise and cloud-based versions, and is often integrated with other business applications to provide a comprehensive view of an organization’s data.\
Linux Version
Splunk is available for Linux in two versions: Enterprise and Free. The Enterprise version is the full-featured Splunk platform, with all the bells and whistles. The Free version is a limited version of the Enterprise version, with some features and functionality disabled. The Free version is available for Red Hat, CentOS, and Ubuntu.
Windows Version
Splunk is available for Windows as both an on-premises installable application and an SaaS offering. The on-premises version of Splunk is available in three editions: Enterprise, Lite, and Free. The Enterprise edition of Splunk for Windows is a full-featured platform that enables real-time visibility of machine data and log data. It can be used to monitor, analyze, and visualize massive amounts of machine data and logs. The Lite edition of Splunk is a lightweight version of Splunk designed for small data sets and limited use cases. The Free edition of Splunk is a limited version of the Enterprise edition and is available for non-commercial use and for evaluation purposes.
Splunk – Interface
Splunk is a powerful data analytics and visualization tool that allows users to collect, store, analyze, and visualize large volumes of data from multiple sources in an easy-to-use interface. It enables users to quickly search, analyze, and visualize data from different sources, such as web logs, application logs, social media data, and more. The tool provides a comprehensive set of tools to help users quickly identify trends and patterns in their data and make sense of it. It also provides a wide range of visualization tools to help users gain insights into their data.
Splunk – Data Ingestion
Splunk is a powerful data ingestion and search engine platform. It can ingest all types of data from various sources, such as logs and metrics, and transform it into actionable insights. Splunk’s data ingestion capabilities are vast, and include the ability to ingest data from a wide variety of sources, including log files, databases, streaming data, and application logs. The platform also has capabilities to parse and process data, as well as to provide machine learning and artificial intelligence for further analysis. Additionally, Splunk can also be used to create custom data pipelines for more complex analysis. With Splunk, users have access to an end-to-end solution for ingesting, analyzing, and visualizing data.
Gathering The Data
To gather data in Splunk, you need to first connect a data source to your Splunk instance. Depending on the type of data source, you can either use the Splunk Web GUI or the Splunk CLI to configure the data source. Once the data source is connected, Splunk will automatically start collecting data from the source and indexing it into its searchable data repository. You can then use Splunk’s search and analytics capabilities to analyze the data and generate insights.
Uploading data
1. Go to the Splunk Home page.
2. Click “Add Data” in the left navigation menu.
3. Select the type of data you want to upload.
4. Follow the instructions provided to upload the data.
5. Once the data is uploaded, it will be indexed and ready for searching.
Selecting Source Type
When configuring a data source in Splunk, users can select the source type. Source type is a way to classify data and determine how Splunk should interpret and process it. Splunk provides a number of predefined source types, such as Apache access logs, JSON, XML, and syslog. For data that does not fit one of these predefined source types, users can create a custom source type. The source type determines how Splunk parses and indexes the data, and what fields it extracts.
Input Settings
In Splunk, users can configure settings for different objects like alerts, data inputs, search, etc. To access the settings, users need to go to the Settings option in the Splunk bar. This will enable users to access the settings for different objects like alerts, data inputs, search, etc. Users can then configure the settings as per their requirements.
Review Settings
Splunk has a variety of settings that users can modify to customize their experience. These can be found under the Settings section of the Splunk interface. Some of the available settings include:
• General Settings – This includes options such as language preferences, time zone, and user preferences.
• App Settings – These settings allow users to configure their Splunk apps, including setting up data inputs, alerts, and reports.
• Data Input Settings – This includes setting up data inputs for indexing, such as files and logs.
• Index Settings – These settings control how the indexing works, including how the data is stored and how it is retrieved.
• Security Settings – These settings allow users to control who can access Splunk and which data they can view.
• Search Settings – This includes setting up search preferences and options for searches.
• Alert Settings – This includes setting up alert policies and conditions for when to trigger an alert.
• Scheduled Reports – This includes setting up scheduled reports that can run on a regular basis.
• Dashboard Settings – These settings allow users to customize their Splunk dashboards, including adding new visualizations and widgets.
Splunk – Source Types
Splunk source types are used to define the type of data that is being indexed. This helps Splunk to interpret the data and properly categorize it for searching and reporting. Some common Splunk source types include:
– Apache Access Logs
– Apache Error Logs
– Windows Event Logs
– Linux System Logs
– Network Packet Logs
– Database Logs
– Application Logs
– Firewall Logs
– Email Logs
– Webserver Logs
– Custom Logs
Supported Source Types
1. Files and directories – Splunk can collect data from files and directories on local and remote machines. This includes log files, text files, rich media files, etc.
2. Network Protocols – Splunk can collect data from network protocols such as HTTP, FTP, SSH, TCP, and UDP.
3. Databases – Splunk can collect data from databases such as MySQL and Oracle.
4. Web Services – Splunk can collect data from web services such as REST APIs, SOAP, and XML-RPC.
5. Message Queues – Splunk can collect data from message queues such as Kafka, RabbitMQ, and JMS.
6. Scripts – Splunk can collect data from custom scripts written in any language.
7. Cloud Services – Splunk can collect data from cloud services such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
Source Type Sub-Category
The Source Type Sub-Category in Splunk refers to the type of data source that is being used, such as log files, Windows Event Logs, packet captures, and so on. The source type sub-category is used to help Splunk determine how to process the data and what searches, reports, and dashboards to create.
Pre-Trained Source Types
1. Splunk Enterprise Security (ES): ES is a security information and event management platform that provides a comprehensive and real-time view of the security posture of an organization. It enables organizations to detect and investigate threats and malicious activities, as well as respond to incidents quickly and effectively.
2. Splunk Cloud: Splunk Cloud combines the power of Splunk software with the convenience, scalability, and reliability of the cloud. It is designed to make it easy to ingest, search, analyze, and visualize data in the cloud.
3. Splunk UBA: Splunk UBA (User Behavior Analytics) is a cloud-based application that enables organizations to detect, investigate, and respond to user behavior anomalies. It analyzes user activities and provides insights into user patterns, enabling organizations to quickly detect and investigate threats, as well as respond to suspicious activity.
4. Splunk App for AWS: The Splunk App for AWS is an application that provides insights into AWS resources and services, including EC2, RDS, EBS, ELB, and S3. It helps organizations to optimize their AWS costs, improve security, and monitor resource utilization.
5. Splunk App for Azure: The Splunk App for Azure is an application that provides insights into Azure resources and services, including Virtual Machines, Storage, Networking, and App Services. It helps organizations to optimize their Azure costs, improve security, and monitor resource utilization.
Splunk – Basic Search
Splunk basic search is a basic search query language used to search through data stored in Splunk. The syntax consists of a keyword followed by a set of parentheses containing a field name and an operator, such as “sourcetype=”, followed by a value. For example, the following query would return all log events from the source type “syslog”:
sourcetype=syslog
Combining Search Terms
In Splunk, you can combine search terms by using the “OR” operator. For example, if you wanted to search for events that contain either the word “error” or the phrase “system outage”, you could use the following search:
error OR “system outage”
Using Wild Card
Wild cards can be used in Splunk in order to search for similar results. The asterisk (*) is used as a wild card character in Splunk, and it is used to represent any character or set of characters. For example, if you wanted to search for all files that have a .txt extension, you could use the search query: “*.txt”. This would return all files with a .txt extension, regardless of what the filename is.
Refining Search Results
Splunk offers a variety of ways to refine search results, including using the search bar, using filtration and sorting options, using search commands, and using the field picker.
1. Using the Search Bar:
The search bar in Splunk allows users to enter specific keywords or phrases to refine their search results. For example, if users search for a specific term and then enter an additional term in the search bar, Splunk will return results that include both terms.
2. Using Filtration and Sorting Options:
Splunk also offers filtration and sorting options that allow users to refine search results. These options allow users to narrow down the search results by specific criteria, such as time range, source, or host.
3. Using Search Commands:
Splunk also offers a variety of search commands that allow users to refine their search results. Examples of search commands include “stats”, “dedup”, and “sort”.
4. Using the Field Picker:
The field picker in Splunk allows users to select specific fields from a search result to refine their results further. This can be used to narrow down the search results and focus on the fields that are most relevant to the query.
Splunk – Field Searching
Field searching in Splunk is the process of searching through data that has been indexed and organized into fields. It uses the Splunk query language to search through the indexed data and find relevant information. Field searching allows users to quickly and easily find the data they need. It also allows users to narrow their search to specific fields, which can be particularly useful when working with large datasets. Field searching can help users find more targeted and accurate results faster and easier than traditional keyword searches.
Choosing the Fields
When choosing fields in Splunk, it is important to consider the data that you need to access and analyze. It is also important to think about how the data will be used in Splunk, as well as the types of searches and reports that you need to be able to generate. Additionally, you should consider the size of the data set and the types of fields that will be necessary to store and access the data. The fields should also be chosen to minimize the amount of data that is stored in Splunk and to reduce the amount of disk space needed. Finally, it is important to consider the cost of the fields, as some of them may require additional licenses or fees.
Field Summary
The Field Summary in Splunk provides an overview of a given field in a dataset. It shows the number of occurrences for each value that is contained in the field, as well as the percentage of total occurrences for each value. Additionally, it shows the total number of unique values, the minimum, maximum, and average values, and the standard deviation for the field. This overview can be used to gain insights into the data contained in the field, such as the range and distribution of values, which can be used to inform data analysis and decision-making.
Using Fields in Search
In Splunk, fields can be used in searches to narrow down the results of a particular search query. For example, if you wanted to find all events with the keyword “error” in a specific log file, you could use the following search query:
index=mylogfile error | table _time, host, sourcetype, message
This search query would return all events that contain the keyword “error” in the log file “mylogfile”. By adding fields to the search query, you can further refine the results. For example, if you wanted to only see events from the “error” sourcetype, you could use the following search query:
index=mylogfile sourcetype=error | table _time, host, sourcetype, message
This search query would only return events from the “error” sourcetype that contain the keyword “error” in the log file “mylogfile”. Additionally, you could add other fields to the search query to further refine the results, such as host, message, or source.
Splunk – Time Range Search
Splunk supports time range searches, which allow users to search data within a specified time frame. This is done by using the time range picker, a graphical tool that allows users to select a time range in the Splunk search bar. The time range picker can be used to select a relative or absolute time frame, such as “last 7 days” or “between 10/01/2018 and 10/31/2018”, respectively. This feature is particularly useful for quickly narrowing down search results to a specific time period.
Selecting a Time Subset
1. In Splunk, open the Search page.
2. Enter the time range or time range selector that you want to use in the Search field.
3. Select a relative or absolute time range from the drop-down menu.
4. Select the earliest and latest times you want to filter to in the upper-right corner of the search bar.
5. Click the Run button to run the search with the specified time range.
Earliest and Latest
The earliest version of Splunk is Splunk 1.0 which was released in 2006. The latest version of Splunk is Splunk 8.0 which was released in 2020.
Nearby Events
Nearby events can be found in Splunk by using the “Nearby” search command. This command will search for events that occurred within a specified radius of a given location. The command takes two arguments: the coordinates of the location to search around and the radius to search within. For example, to find all events that occurred within 5 miles of the coordinates 41.88, -87.63, you could use the following search:
nearby lat=41.88 long=-87.63 radius=5miles
Splunk – Sharing Exporting
Splunk provides a number of ways to share and export data.
Using Splunk’s web interface, you can easily share the results of your searches with colleagues by simply clicking the “Share” button at the top of the search results page. This will generate a unique URL that can be shared with others, allowing them to view the same results.
You can also export search results in various formats, including CSV, JSON, and XML. To do so, click on the Export button at the top of the search results page and select the desired file format.
For larger data sets, you can also use Splunk Web to export data to an external data store such as Amazon S3 or Microsoft Azure. To do so, click on the Export button at the top of the search results page and select the desired external data store.
Finally, you can also use the Splunk REST API to programmatically export data from Splunk. This allows you to export data in any format you desire, and automate the export of search results.
Sharing the Search Result
1. To share the search result with an external user, click on the “Share” button located on the top right side of the search result page.
2. Select the “Share Result” option from the dropdown menu.
3. Enter the recipient’s email address and select the desired sharing options.
4. Click on the “Share” button to share the search result.
Finding the Saved Results
The saved searches can be found in the Saved Searches section of the Splunk interface. To access the saved searches, click on the “Searches & Reports” tab from the left-hand side of the Splunk interface. All the saved searches you have created or that have been shared with you will be listed in this section.
Exporting the Search Result
1. To export the search result in Splunk, navigate to the “Actions” menu located on the right side of the search results page and select “Export results.”
2. Select the format you would like to export the results in, such as CSV, XML, or JSON.
3. Choose whether you would like to export the entire search result or just the results displayed on the page.
4. Select the time range for the exported results.
5. Click the “Export” button to export the results.
Splunk – Search Language
Splunk Search Language (SPL) is the language used to interact with Splunk’s search and reporting capabilities. It is used to search and analyze data in Splunk, as well as to create alerts, reports, and dashboards. SPL is a powerful and expressive language that provides a wide range of features for data analysis and manipulation. SPL is comprised of various components such as search commands, functions, operators, and macros.
Components of SPL
1. SPL Core Library: The SPL Core Library defines a set of interfaces and classes that are used to manage collections, data, and objects. It provides the tools for object-oriented programming in PHP.
2. SPL Types Library: The SPL Types Library provides specialized data types for working with numbers, strings, and objects. It also defines a set of type-safe functions for working with these data types.
3. SPL Iterators Library: The SPL Iterators Library provides a set of iterators that can be used to traverse data structures, such as arrays and objects.
4. SPL Exceptions Library: The SPL Exceptions Library provides a set of exception classes that can be used to handle errors and exceptions.
5. SPL Autoload Library: The SPL Autoload Library provides a set of classes that can be used to automatically load classes when they are needed.
6. SPL Functions Library: The SPL Functions Library provides a set of utility functions that can be used to perform common tasks, such as sorting data or manipulating strings.
Splunk – Search Optimization
1. Avoid using wildcards: Wildcards are a useful tool for searching, but they can significantly slow down your search and make it less efficient. Instead of using wildcards, consider using exact matches and keyword search.
2. Use Boolean operators: Boolean operators such as AND, OR, and NOT can help you narrow down search results and be more precise in your searches.
3. Utilize field searches: Use field searches to narrow down your search to a specific field or set of fields. This will help you quickly find the information you need.
4. Utilize search modifiers: Search modifiers such as “earliest”, “latest”, and “relative_time” can help you refine your search and focus on the information you need.
5. Leverage indexed fields: Indexed fields can be used to quickly search large datasets and return precise results.
6. Utilize reporting commands: Reporting commands such as “stats”, “timechart”, and “top” can help you summarize your search results and make them easier to interpret.
7. Replace wildcards with regular expressions: Regular expressions can help you quickly search large datasets and return precise results. Regular expressions can be used in place of wildcards to make searches more efficient.
Analyzing Search Optimisations
Search optimisations are techniques used by businesses and webmasters to increase their visibility on search engine results pages, so that their webpages are more likely to be seen by potential customers. These optimisations can range from using specific keywords in the content and titles of webpages, to creating backlinks from other websites, to creating a sitemap for the website. By analysing the effectiveness of search optimisations, businesses can determine which ones are the most effective and then focus their efforts on those techniques. This can help them better target their audience and improve their overall online presence.
Turning Off Optimization in Splunk
To turn off optimization in Splunk, you can do the following:
1. Go to Settings -> Advanced Search -> Search Optimization
2. Uncheck the box next to “Enable search optimization”
3. Click “Save” to apply the changes.
Splunk – Transforming Commands
Splunk is a powerful search and analytics tool that can help organizations of any size to quickly and easily search, analyze, and visualize large amounts of data. It is also used to create custom commands and workflows that can be used to quickly and efficiently process data.
One example of a Splunk transformation command is the ‘stats’ command. This command is used to calculate summary statistics from a given dataset. It can be used to calculate the average, median, sum, and many other statistics from a given dataset. It can also be used to group data by certain fields and calculate metrics for each group.
Another example of a Splunk transformation command is the ‘eval’ command. This command can be used to perform calculations on fields, create calculated fields, convert data types, and more. It can also be used to perform complex mathematical and logical operations on data.
Finally, another example of a Splunk transformation command is the ‘transaction’ command. This command can be used to group events together into transactions based on certain criteria. It can be used to group events together by time, value, or other criteria. This command can be used to quickly and easily find patterns in data.
Splunk – Reports
Splunk provides a powerful and versatile reporting and analysis platform to help organizations identify and act on insights from their data. Reports in Splunk are constructed by extracting data from indexed sources, transforming it into visualizations, and then formatting it into a report. Reports can be used to gain insight into trends, patterns, and correlations, as well as to identify anomalies and outliers. Splunk offers a variety of reporting options, including dashboards, charts, tables, and alerts. Reports can be scheduled to run on a predetermined basis and can be shared with other users in the organization. Reports can also be exported to external formats, such as PDF and CSV, for further analysis or distribution.
Report Creation
Splunk is a powerful analytics platform that can be used to generate reports from the data it collects. Reports can be created by leveraging the Splunk Query Language (SPL). SPL allows users to search and analyze their data to generate insights. Reports can be generated in various formats including HTML, CSV, PDF, and XLSX. Additionally, Splunk dashboards can be used to create graphical representations of the data. Reports can be scheduled to run on a regular basis, and alerting can be enabled to send notifications when certain conditions are met.
Report Configuration
Splunk offers a large array of reporting options. To configure reports in Splunk, users must first create a search query to retrieve the desired data. Once the query is complete, users must select the “Reporting” option from the search bar. This will open a new window with various options for creating and customizing the report. The user can then choose a visualization type, adjust the display settings, and add any additional formatting. Once complete, the user can save the report for later use.
Modifying Report Search Option
1. Navigate to the Settings section of your app.
2. Under Search & Reporting, select Report Search.
3. Select the Edit button next to the report search option you’d like to modify.
4. You can now modify the Search String, Title and Description of the report.
5. Once you have made your changes, click the Save button.
6. You have now successfully modified the Report Search option in Splunk.
Splunk – Dashboards
Splunk dashboards enable users to view data from multiple sources in a single view. They provide easy-to-use, graphical representations of the data, allowing users to quickly identify and investigate trends. Dashboards can be created from any source data that is indexed in Splunk, including application logs, system logs, network traffic, server performance metrics, and more. Dashboards can be customized to display data in a wide variety of ways, including charts, tables, and more. Splunk dashboards are designed to be interactive, allowing users to filter and drill-down into data sets, as well as to compare data from different sources. Splunk dashboards can also be shared with other users, allowing them to view and interact with the data.
Creating Dashboard
1. Log into Splunk.
2. Click on the “Dashboards” tab.
3. Click “Create New”.
4. Enter a name for your dashboard.
5. Choose a visualization type.
6. Add inputs and/or searches.
7. Click “Save” to save your dashboard.
Adding Panel to Dashboard
1. Log into your Splunk instance.
2. Click the “Dashboards” icon in the top navigation bar.
3. Select the dashboard you want to add the panel to.
4. Click “Edit” in the top right corner of the dashboard.
5. On the left-hand side of the screen, you’ll see a list of panels.
6. Select the type of panel you want to add. This could be a chart, table, single value, or event timeline.
7. Once you have selected the panel type, click “Add” on the right-hand side.
8. Enter the search query for your panel, and click “Run”.
9. Once the search has completed, you will be able to adjust the visualization settings.
10. When you’re happy with the panel, click “Save” at the bottom of the page.
11. The panel will be added to your dashboard.
Splunk – Pivot and Datasets
Splunk is a software platform that enables users to search, analyze, and visualize large volumes of data. It provides a wide range of tools, including Pivot and Datasets, to make data analysis easier.
Pivot is a tool that allows users to quickly analyze data by creating interactive charts and tables that display data in a graphical format. It allows users to drill down into the data to get more detailed insights. Pivot also enables users to compare different data sets side-by-side and filter data based on user-defined criteria.
Datasets is a tool that allows users to easily create and manage data sets. It provides a graphical user interface for creating and editing data sets and allows users to customize the data sets by adding data columns, sorting columns, setting filters, and more. It also provides a built-in search feature to quickly locate data within a data set.
Creating a Dataset
1. Log into Splunk and navigate to the “Data Inputs” page.
2. Click the “Create New” button and select “Upload File”.
3. Select the file you would like to upload and click “Next”.
4. Enter a name for the dataset and click “Next”.
5. Select the index for the dataset and click “Next”.
6. Select “Create Dataset” and click “Finish”.
7. The dataset will be created and you can start searching and analyzing the data.
Selecting a Dataset
The dataset you select in Splunk will depend on the type of data you are looking for. Splunk has several publicly available datasets that you can use, such as the U.S. Census Bureau, Twitter, and the Open Data Portal. Additionally, you can also upload your own datasets to Splunk. To select a dataset in Splunk, you will need to decide what type of data you want to analyze, and then use Splunk’s search interface to find a dataset that meets your requirements. Once you have selected a dataset, you can begin to explore the data and create visualizations and dashboards.
Choosing Dataset Fields
When choosing dataset fields in Splunk, it is important to consider the types of analysis that you want to run. For example, if you are looking to analyze user behavior, you may want to include fields such as user ID, page views, page visits, and time spent on each page. If you are looking to analyze transaction data, you may want to include fields such as transaction ID, time of purchase, type of product purchased, and customer ID. Additionally, you may want to include fields that are specific to the data you are collecting, such as product name or customer age. Depending on the type of analysis you are looking to do, you may also need to include fields that provide additional context, such as geographic location or device type.
Creating Pivot
1. First, log into Splunk and click on the “Search & Reporting” tab in the top navigation bar.
2. Type in the search query you would like to use to create the pivot.
3. Once the search results are displayed, click on the “Pivot” button in the top navigation bar.
4. Select the field you want to use to create the pivot.
5. Select the “Row” aggregation to group your data.
6. Select the “Column” aggregation to define the columns for your pivot.
7. You can also add additional aggregations to the pivot by clicking on the “Add Aggregation” button.
8. Once you have configured the pivot, click on the “Run Pivot” button to generate the results.
Choose Dataset Action
There are several dataset actions available in Splunk, depending on the dataset type.
For example, if you are working with a table, you can use the following actions:
– Search
– Rename
– Sort
– Filter
– Group
– Add Column
– Join
– Split
– Merge
– Aggregate
– Pivot
– Timechart
– Statistics
If you are working with a chart or graph, you can use the following dataset actions:
– Zoom
– Pan
– Hover
– Select
– Highlight
– Legend
– Threshold
– Annotations
– Annotations from Table
– Show Values
Choose the Pivot Fields
The pivot fields available in a pivot table include: Sum, Count, Average, Max, Min, Product, Count Numbers, Percentage of, Running Total in, and Difference From.
Splunk – Lookups
Splunk lookups are a powerful feature that allows you to enrich data by automatically matching it with external data sources. Splunk lookups enable you to quickly and easily add additional context to your data, such as customer information, location data, or threat intelligence. This additional context helps you to better understand your data, find insights, and take action. Lookups are used to add fields to events that are not in the original data source. Lookups can be configured to match on a single field, multiple fields, or even to return entire records. They can be used with both real-time and historical data. Lookups are typically used to match fields in Splunk events with fields in an external data source, such as a CSV file, a database, or an API.
Steps to Create and Use Lookup File
1. Create a lookup file: First, create a lookup file, which is a separate file from the main file. This file should contain two columns, one for the key and one for the value. The key is the variable you want to match with the main data, and the value is what you want to add to the main data.
2. Load the lookup file: Once the lookup file is created, it should be loaded into the main file. This can be done in a variety of ways, depending on the software you’re using, such as importing the file or pasting the data into the main file.
3. Set up the lookup: Once the lookup file is loaded, it needs to be set up as a lookup. This is done by setting the key column as the lookup reference and the value column as the lookup value.
4. Use the lookup: Finally, the lookup should be used to add the value from the lookup file to the main file. This can be done by using a formula or by creating a lookup column in the main file. The lookup column will automatically fill in the values from the lookup file when the key matches.
Create Lookup File
1. Create a spreadsheet with two columns:
Column A: Unique Identifier
Column B: Description
2. Enter a unique identifier in the first row of Column A and a corresponding description in Column B.
3. Repeat step 2 for each row, entering a unique identifier and its corresponding description.
4. Save the file as a .csv (comma-separated values) file.
Splunk – Schedules and Alerts
Splunk enables users to schedule searches and alerts to run at regular intervals. Scheduled searches and alerts can be used to monitor and analyze data in real time and respond to specific conditions.
Scheduled searches can be used to detect patterns or trends in data and create reports for analysis. They can also be used to track changes in system behavior over time and identify potential problems.
Alerts can be created to respond to specific conditions or events. Alerts can be sent to a variety of destinations, including email, SMS, and custom webhooks. Alerts can also be used to trigger actionable responses, such as running a script or updating a ticketing system.
Splunk also offers a range of alerting options for administrators, such as setting thresholds for alerts, specifying time frames for alerts, and setting alert frequency.
Creating a Schedule
1. From the Splunk Home page, select “Settings” and then select “Scheduled Searches”.
2. Select “New” to create a new search.
3. Enter the search query you wish to run, and select the time range in which you want the search to run.
4. Select the frequency (daily, weekly, monthly, etc.) at which you want the search to run.
5. Under “Action”, select what you want the search to do when it completes. You can save the results to a dashboard, create an alert, or send an email.
6. To save your changes, click “Save As” and enter a name for your search.
7. Click “Save” to finish creating your search.
Important Features of Scheduling
• Automated Scheduling: Splunk provides an automated scheduling system that allows you to schedule data collection, indexing, and report generation on a regular basis. This helps to ensure that data is always up to date and that reports are generated on a regular basis.
• Customizable Reports: Splunk allows users to customize reports to meet their specific needs. This means that users can create reports that are tailored to the data they are analyzing and to the specific business requirements.
• Real-Time Monitoring: Splunk provides real-time monitoring of data, enabling users to quickly detect any changes or anomalies in their data. This helps to ensure that data is being collected and monitored in a timely manner.
• Advanced Alerts: Splunk provides advanced alerting capabilities that allow users to create custom alerts and set thresholds for when they should be triggered. This helps to ensure that users are immediately notified of any potential issues or changes in their data.
• Scalable Architecture: Splunk’s architecture is designed to scale with the size of your data, allowing you to easily add capacity as needed. This helps to ensure that you have the capacity to handle large amounts of data without any performance degradation.
Schedule Actions
Actions in Splunk are used to automate tasks and to help you respond quickly to events. Actions can be scheduled to run on a regular basis, such as daily or weekly, or they can be triggered by specific events. Actions are defined in Splunk’s Settings > Actions menu. Common actions include sending an alert email, creating a ticket, or running a script. You can create custom actions using the Splunk SDK and configure them to run when a certain condition is met.
Splunk – Knowledge Management
Splunk’s Knowledge Management feature is an AI-driven platform that helps organizations capture and organize information to ensure that it is easy to access and use. It enables users to quickly and easily find and share the right information with the right people. The Knowledge Management feature makes it easy to store and share data in a secure and organized manner, allowing users to quickly access the data they need when they need it. The feature allows users to search for data, create custom dashboards, and automate processes. It also helps organizations improve their decision-making capabilities by offering insights into their data.
Knowledge Object
A Knowledge Object in Splunk is any type of data, such as an event, field, or search result that can be used to enhance the search experience. Knowledge Objects can be created, managed, and shared within an organization to help users quickly and effectively search and analyze data. Examples of Knowledge Objects include pre-defined searches, field extractions, and event types.
Uses of Knowledge Objects
Knowledge Objects in Splunk can be used in various ways, such as:
1. Building Dashboards: Knowledge Objects can be used to create dynamic, interactive dashboards that provide users with key insights into their data.
2. Automating Alerts: Knowledge Objects can be used to automate the process of setting up alerts, which can be used to notify users of important events or changes in their data.
3. Identifying Trends: Knowledge Objects can be used to identify trends in data and help users better understand their data and make informed decisions.
4. Improving Searches: Knowledge Objects can be used to improve search accuracy and speed, which can be especially useful for large datasets.
5. Enhancing the User Experience: Knowledge Objects can be used to create a better user experience by providing more relevant results and more intuitive interfaces.
Splunk – Subsearching
Subsearching is a feature of Splunk that enables users to refine or narrow search results by performing additional searches on the original search results. It enables users to break up large, complex searches into smaller, more manageable chunks for better performance and more accurate results. This feature is especially useful for conducting searches on large datasets and for getting deep insights into data. Subsearching can be used to filter data by fields, values, time ranges, and other criteria. It also allows for the combination of multiple searches using Boolean logic.
Splunk – Search Macros
Splunk search macros are a feature that allows users to define and reuse customized search strings or parts of search strings in a Splunk query. They are similar to functions or variables in programming languages, but they are specific to Splunk. Macros allow users to quickly create longer and more complex searches, and to reuse searches in multiple contexts. They also help to reduce the amount of typing required to enter a query.
Macro Creation
To create a macro in Splunk, you need to perform the following steps:
1. Log in to Splunk and go to Settings > Advanced Search.
2. Click the “Macros” tab.
3. Click the “+” icon to create a new macro.
4. Enter a name for the macro and then enter the search query you want to use for the macro.
5. Click the “Save” button to save the macro.
6. To use the macro, enter “| macro name” in your search query.
Macro Scenario
A macro scenario in Splunk involves creating a macro to retrieve data from the Splunk platform. This macro can be used to automate tasks such as searching, reporting, and alerting. The macro can be written in Python, JavaScript, or other languages, and can be customized to fit the user’s specific needs. For example, a macro could be written to search for specific events in the Splunk platform, analyze the results, and then alert the user if any of the results match a certain criteria. Additionally, the macro could be used to generate reports on a regular basis, or to create custom dashboard views that can be used to track key performance indicators.
Defining the Macro
Macros in Splunk are user-defined variables used to store and reference frequently used values. They are used to make searches more efficient by reducing the amount of work that must be done to customize a search. Macros are most commonly used in search strings, but they can also be used in reports, dashboards, and other parts of the Splunk interface. Examples of common macros include a list of user names, a list of IP addresses, or a list of search terms.
Using the Macro
The Macro in Splunk can be used to automate complex searches and to quickly retrieve data from a large data set. It can also be used to create custom search commands, alerting, and dashboards. For example, you can create a macro that searches for a specific keyword and returns the results in a specific format. You can also use the macro to create custom alerts, dashboards, and reports. Additionally, you can use the macro to generate automated reports on a weekly or monthly basis.
Splunk – Event Types
Event types are tags that can be used to classify and categorize events in Splunk. Event types can be used to quickly identify and filter out specific types of events. They can also be used to set up alerts and dashboards, and to apply field extractions and field aliases. Examples of event types include web traffic, authentication, system errors, and application logs.
Using a Search
Using a search in Splunk is a straightforward process. First, open the Splunk search bar and enter a query. The query can be a simple keyword or phrase, or it can be a more complex search expression. Once the query is entered, Splunk will return a list of results based on the search criteria. From there, users can refine the search parameters to narrow down the results. Additionally, Splunk has numerous advanced search operators that enable users to construct more complex search queries.
Creating Event Type
1. Log in to Splunk Enterprise.
2. Select Settings > Fields > Event Types.
3. Select New Event Type.
4. Enter a name for the event type.
5. Select the source type that this event type applies to from the drop-down menu.
6. Enter a description of the event type.
7. Enter a list of keywords that will match the event type (optional).
8. Select the severity level for the event type.
9. Enter a list of fields and values that will match the event type (optional).
10. Select Save.
Using New Event Type
1. Log into Splunk.
2. Click on the “Settings” tab at the top of the screen.
3. Select the “Data Inputs” option.
4. Select the “Event Types” option.
5. Click “New” on the top right of the page.
6. Enter the name and description of the new event type.
7. Select the source type you want to assign to the new event type.
8. Click “Save” to save the new event type.
9. Add any additional fields to the new event type, as needed.
10. Click “Save” to save the changes.
Viewing the Event Type
To view the event type in Splunk, users can click the “Events” tab on the left-hand side of the Splunk window. This will display the various events that have been logged in Splunk, along with the event type for each. From here, users can filter the events by type and view the details of each event.
Using the Event Type
The Event Type in Splunk is a way of categorizing different types of events. It can be used to group events into meaningful categories, filter events to find the ones you are interested in, and create custom visualizations and reports. It is also used to identify certain types of events, such as performance issues, security threats, and anomalies.
Splunk – Basic Chart
Splunk is a powerful data analytics and visualization platform. It offers a wide range of charting and visualization capabilities, from basic line and bar charts to more complex graphs, like time series analysis and scatter plots. Splunk also provides an extensive library of pre-built chart types, as well as the ability to customize and create your own. Additionally, Splunk allows users to combine multiple data sources into a single chart, which enables users to visualize correlations between datasets. Finally, Splunk offers data drill-down capabilities, giving users the ability to quickly and easily explore a data set for deeper insight.
Creating Charts
Charts can be created in Splunk by using the Visualizations App. This app allows users to create and customize their own graphical representations of data using a wide variety of chart types. The app also provides options for editing axes, colors, and labels, as well as for creating interactive charts. Additionally, users can save and share their visualizations with other users, allowing for collaboration and data exploration.
Changing the Chart Type
Step 1: Select the chart type from the chart setup panel.
Step 2: To select a chart type, click on the chart type drop-down menu and select the desired chart type.
Step 3: Click the “Apply” button to save the changes.
Step 4: The chart will be updated to reflect the new chart type.
Formatting a Chart
To format a chart in Splunk:
1. Select the chart you want to format on the dashboard.
2. Click the gear icon in the upper right corner of the chart.
3. On the left side of the window, select the “Appearance” tab.
4. Adjust the settings for Fill, Border, Grid, Legend, and Title to change the appearance of the chart.
5. Select the “Data” tab to adjust the data settings for the chart.
6. Select the “Axes” tab to adjust the axis settings for the chart.
7. Select the “Marks” tab to adjust the mark settings for the chart.
8. When you’re done, click the “Apply” button at the bottom of the window to save your changes.
Splunk – Overlay Chart
Splunk’s Overlay Chart feature allows users to compare multiple metrics on the same graph. This makes it easy to visualize trends, identify correlations, and compare performance across multiple datasets. The Overlay Chart can be used to compare performance metrics across different time periods, as well as to compare different metrics to each other, such as sales and customer satisfaction. Furthermore, users can customize the chart to show multiple data points, or to focus on a specific data point. This makes it easy to identify areas of improvement or areas that need further investigation.
Chart Scenario
A Splunk chart scenario could involve creating a chart to display data from a log file. For example, an administrator could create a chart to visualize the number of login attempts within a certain time period. The chart would show the number of successful logins, the number of failed logins, and the total number of attempts. This data would help the administrator identify any potential security issues and provide insight into user access patterns. Additionally, the chart could be used to compare login attempts over different time periods to identify any trends or patterns.
Creating Chart Overlay
1. Go to the Splunk Dashboard and click on “Create New”
2. Select “Visualization” from the dropdown menu
3. Select “Chart Overlay” from the visualization options
4. Configure the chart overlay settings, such as the chart type, x and y axis, colors, etc.
5. Once you have configured the chart overlay, click “Save As” to give it a name
6. Click “Done” to finish the creation of the chart overlay.
Splunk – Sparklines
Splunk Sparklines are a feature of Splunk that allows users to quickly visualize data in an interactive, graphical format. They enable users to quickly identify trends, correlations, and other patterns in their data. Splunk Sparklines are interactive, allowing users to hover over data points to get details such as exact values, or to drill down into data to see more granular information. Splunk Sparklines are customizable, allowing users to select color, size, and other display options to best suit their needs.
Selecting the Fields
The fields in Splunk can be selected by using the fields command. This command enables users to select specific fields and values from the search result. It can be used to filter out specific fields and values from the search result. Additionally, the fields command can be used for selecting fields from a specific source, performing statistical operations on fields, and performing field-value manipulations.
Creating the Sparkline
In Splunk, a sparkline can be created by using the sparkline chart option in the Chart Editor. The sparkline chart is a single-series chart that displays its values as a line. To create a sparkline:
1. In the search results page, click the Visualization tab and select Chart.
2. In the Chart Editor, select the sparkline chart option.
3. Select the field that contains the data to be displayed in the sparkline.
4. Select additional settings such as display type, line type, color, and other styling options as desired.
5. Click Apply to save the sparkline.
Changing the Time Period
To change the time period in Splunk, click the Time Picker in the upper right corner of the Splunk window. This will open the Time Picker panel. From here, you can select a specific time period, or you can choose an option to customize the time range. When you have selected the time period you would like, click the ‘Set Time Range’ button to apply the changes.
Splunk – Managing Indexes
Indexes are the repositories for the data ingested into Splunk. Managing indexes is an important part of Splunk administration. This includes creating and deleting indexes, configuring retention policies and setting up replication for data redundancy.
1. Creating Indexes
To create a new index, go to Settings → Indexes → New Index. Here, you can specify the index name and the number of shards (partitions) for the index.
2. Deleting Indexes
To delete an index, go to Settings → Indexes → select the index → Delete.
3. Retention Policies
Retention policies can be configured to ensure that data is not stored indefinitely. Go to Settings → Indexes → select the index → Edit → Retention tab. Here, you can specify the retention period for the index.
4. Replication
For data redundancy, it is possible to replicate the data across multiple indexes. This is useful for ensuring that data is not lost in case of any hardware failure. To configure replication, go to Settings → Indexes → select the index → Edit → Replication tab. Here, you can specify the indexes to replicate data to.
Checking Indexes
Indexes are used in Splunk to store and organize all of the data that is collected and searched. Indexes are stored in the $SPLUNK_HOME/var/lib/splunk/ directory, and each index is stored in its own unique directory. Each index contains several files containing information about the data stored in the index.
To view the indexes that have been created in Splunk, you can use the “indexes” command. The command will list all of the indexes that have been created, and the amount of data stored in each of them. You can also view the configuration of each index by using the “list index” command. This will display information such as the index name, the total size, the size of each source type, and the number of buckets. Finally, you can view the contents of each index by using the “search index” command. This will list all of the events that have been stored in the index.
Creating a New Index
1. Navigate to Settings > Indexes.
2. Click “New Index”.
3. Enter a name and description for the index.
4. Select the appropriate data type for the index.
5. Select the retention policy for the index.
6. Choose any optional settings for the index, such as cold/frozen bucket rolling, etc.
7. Click “Save” to create the new index.
Indexing the Events
To index events in Splunk, follow these steps:
1. Log into the Splunk web interface.
2. Click the “Settings” menu and select “Data inputs”.
3. Select the type of data source you want to index (e.g. log files, Windows Event logs, etc.)
4. Follow the on-screen instructions to set up the data input.
5. Select an index for the data source.
6. Click “Save” to save the data input.
7. Repeat steps 3-6 to add additional data inputs.
Splunk – Calculated Fields
Splunk’s Calculated Fields feature is a way for users to create their own custom fields using powerful mathematical and statistical functions. This allows users to quickly generate insights and new metrics from their existing data. Calculated Fields can be used to perform calculations on individual records, across an entire dataset, or across multiple datasets. Calculated Fields can be used to build reports, dashboards, and alerts that are tailored to the specific needs of the user.
Using the eval Function
The eval function in Splunk allows you to use arbitrary expressions to create or modify existing fields. It is used to calculate the value of a field based on the values of other fields. For example, you could use the eval function to calculate the difference between two different fields, or to create a new field based on the values of multiple fields.
Adding New Fields
To add a new field in Splunk, you can use the ‘Set Fields’ command in the search bar. This command allows you to add new fields and assign values to them.
You can also add new fields in the Splunk GUI by going to Settings > Fields > Field Extractions > New Field Extraction. From here, you can add new fields and specify their values.
Displaying the calculated Fields
Once the fields are calculated in Splunk, they can be displayed either in the search results or in a dashboard. To display the calculated fields in the search results, you can use the Splunk Search Processing Language (SPL) to add the fields to the search query.
To display the calculated fields in a Splunk dashboard, you can add the fields to the dashboard using the Splunk Dashboard Editor. The Dashboard Editor allows you to select the fields to add and then customize the display options. You can also add filters and other visualizations to the dashboard to further customize the view.
Splunk – Tags
Splunk tags are assigned to Splunk objects to categorize them, such as searches, reports, and dashboards. Tags can be used to organize and filter objects, as well as to make it easier to find them. Tags can also be used to share objects with other users. In addition, tags can be used to set permissions on objects, as well as to trigger alerts and notifications.
Creating Tags
To create tags in Splunk, navigate to Settings > Tags. Click the + New Tag button to create a new tag. Enter the tag name, description, and color. Then click Save. Tags can be applied to saved searches and reports. To apply tags to a saved search or report, open the search or report in the Search & Reporting app, and click the Add Tag icon. Select the appropriate tags and click Save.
Splunk – Apps
Splunk Apps are add-on components to Splunk Enterprise that extend its functionality. Applications can add new data inputs, dashboards, visualizations, data models, and more. Splunk Apps are developed by both Splunk and third-party developers, and are available in Splunkbase, Splunk’s online app store.
Listing Splunk Apps
1. Splunk IT Service Intelligence (ITSI)
2. Splunk Enterprise Security (ES)
3. Splunk App for Windows Infrastructure
4. Splunk App for AWS
5. Splunk Phantom
6. Splunk UBA
7. Splunk Insights for Infrastructure
8. Splunk Security Essentials App
9. Splunk App for Enterprise Security
10. Splunk App for Unix and Linux
App Permissions
Splunk apps may require permissions in order to access data or perform certain functions. The permissions required for an app will vary depending on the app’s purpose and the type of data it accesses. Generally, an app may require read, write, or execute permissions for files, access to databases, and various network privileges. It is important to ensure that any permissions granted to an app are necessary and appropriate for the app’s purpose.
App Marketplace
The Splunk App Marketplace is a directory of apps, add-ons, and other solutions built by Splunk customers, partners, and independent developers that provide unique value to Splunk users. The Marketplace includes apps, add-ons, and custom solutions that extend the functionality of Splunk Enterprise, Cloud, and Splunk Light. It also includes apps that are available on the Splunkbase website. From the Marketplace, users can browse and install apps, add-ons, and custom solutions to their Splunk instance. The Marketplace also provides a platform to connect developers and customers to promote, deploy, and monetize their apps and solutions.
Splunk – Removing Data
Splunk provides several ways to remove data from its platform. These include:
1. Archiving and Deleting Data: Splunk allows an admin to archive and delete data from indexes and searchable objects. This can be done through the Splunk Web UI or through command line interface.
2. Purging Data: Splunk provides a feature called ‘Purge’ which allows users to delete events that have been stored in indexes for a certain amount of time. This feature can be configured using the Splunk Web UI or through the command line interface.
3. Filtering Data: Splunk allows users to filter data by creating saved searches and filters. This allows users to specify which events they want to keep or discard.
4. Splunk’s Data Retention Settings: Splunk allows users to control the amount of data that is stored and retained in indexes. This can be configured via the Splunk Web UI or through the command line interface.
Assigning Delete Privilege
The delete privilege allows a user to delete data from a database. To assign the delete privilege to a user, the administrator must grant the privilege to the user. This can be done with the GRANT command in SQL, which assigns the privilege to the user for a specific table, view, or stored procedure. For example:
GRANT DELETE ON table_name TO user_name;
Identifying the data to be removed
The data to be removed in Splunk can be identified by the user. Splunk offers a variety of search commands that can be used to identify and delete specific data. For example, the “delete” command can be used to delete specific events or data from the Splunk index. Additionally, the “remove” command can be used to remove specific fields or values from the Splunk index.
Deleting the Selected Data
To delete data in Splunk, you will need to use the “delete” command. This command will allow you to delete any data that matches the provided search criteria. For example, if you wanted to delete all events from the last 24 hours that contain the word “error”, you would run the command:
delete sourcetype=”*” earliest=-24h “error”
This command will delete all events from the last 24 hours that include the word “error”. You can also use the “delete” command to delete specific events by specifying an index, source, or host. For example, if you want to delete all events from a specific source, you can run the command:
delete source=”my_source”
This command will delete all events from the specified source.
Splunk – Custom Chart
Splunk custom charts are charts that are created and customized by the user. They can be created using Splunk’s graphical user interface, or by writing and coding custom queries. Custom charts can be used to visualize and analyze data, compare trends and correlations, and identify patterns and trends in data. Splunk custom charts can be used to create and customize any type of chart, including line charts, bar charts, scatter plots, and pie charts.
Axis Customization
In Splunk, users can customize the X-axis of a chart. The following steps can be used to customize the X-axis:
1. Select the chart visualization type by clicking on the Visualization tab and selecting the type of chart to be displayed.
2. Once the chart has been created, click on the “Edit” button in the upper right corner of the chart to bring up the Chart Editor.
3. Select the “Axes” tab from the Chart Editor and then select the “X Axis” option.
4. From here, users can customize the layout and appearance of the X-axis. This includes changing the axis label, range, scale, and intervals.
5. When finished, click “Apply” to save the changes.
Legend Customization
Splunk offers a variety of customization options to customize Legends. This includes changing the color, font, and size of a legend, as well as adding text labels, annotations, and other visual elements. In addition, Splunk allows users to customize the legend by adding custom labels, adding data points, and even creating custom charts. This makes it easy for users to create visualizations that convey their data in an intuitive and meaningful way.
Splunk – Monitor Files
Splunk can be used to monitor filesystem activity. Splunk can collect, parse, and store log data from various sources, including files residing on disk. This enables Splunk to monitor filesystem activity and detect changes in file or directory properties, including file creation, modification, and deletion. It can also detect changes in file size and ownership, as well as generate reports on file access and usage. Splunk can also alert administrators of any unusual or suspicious activity on the filesystem.
Add files to Monitor
1. Log in to Splunk web interface.
2. Select the “Settings” tab.
3. Select “Data inputs” from the left side menu.
4. Select “Files & Directories” from the list of input types.
5. Click “New” to add a new data input.
6. Enter the path for the files you want to monitor.
7. Select the interval for data collection from the drop-down menu.
8. Configure other settings as needed.
9. Click “Save” to save the changes.
10. Repeat steps 5-9 for each file that needs to be monitored.
Splunk – Sort Command
The Splunk sort command is used to sort search results by field or fields. This command can be used to sort the results by one or more fields. The syntax for the sort command is:
| sort [field1, field2, …] [asc|desc]
The sort command takes two parameters – fields and direction (ascending or descending). The field parameter is a list of one or more fields to sort by. The direction parameter is optional and can be either “asc” for ascending or “desc” for descending. If the direction parameter is omitted, the results will be sorted in ascending order by default.
Sorting By Field Types
In Splunk, you can sort results by field types by using the sort command. The sort command allows you to sort the results by one or more fields. The syntax for the sort command is: sort <fieldname> [<asc|desc>] … The fieldname argument is the field that you want to sort by. The asc or desc argument indicates whether you want to sort the results in ascending or descending order. You can also specify multiple fields to sort by, in which case the results will be sorted in the order specified. For example, the following command will sort the results by the field “Source” in ascending order, then by the field “Host” in descending order: sort Source asc Host desc
Sorting up to a Limit
One way to do sorting up to a limit in Splunk is to use the “top” command. This command allows you to specify a limit to the number of results you wish to return. For example, if you wanted to return the top 10 results from a search, you could use the following syntax:
| top limit=10
This would return the top 10 results from your search query. You can also sort the results in a variety of ways, such as by count, size, etc. For more information, please see the Splunk documentation.
Using Reverse
Reverse can be used in Splunk to reverse the order of results. For example, if you have a table of data in Splunk with the most recent information at the top, you can use the Reverse command to reverse the order of the results so that the most recent information is at the bottom. This can be helpful if you need to view the data in chronological order.
Splunk – Top Command
The top command is a Splunk search command that is used to retrieve the top or bottom results from a search result set. It is used to limit the number of search results that are returned by a search query. It is useful when a user wants to retrieve only the most relevant or important results from a large search result set.
Top Values for a Field
1. Count: Counting the total number of occurrences of the field.
2. Top Values: Identifying and displaying the most common values for the field.
3. Maximum: Identifying and displaying the highest value for the field.
4. Minimum: Identifying and displaying the lowest value for the field.
5. Mean: Calculating and displaying the average value for the field.
6. Median: Calculating and displaying the middle value for the field.
7. Mode: Identifying and displaying the most frequent value for the field.
8. Range: Calculating and displaying the difference between the highest and lowest values for the field.
Top Values for a Field by a Field
Splunk allows users to find the top values for a field by a field by using the stats command. For example, to find the top values for a field called “user_id” by a field called “country”, the following search can be used:
index=* | stats count by user_id, country | sort -count | head 5
Show Options
Splunk offers several options to users. These options include:
1. Monitoring: Splunk allows users to monitor their environment and detect any potential issues. It provides real-time visibility into system performance and can alert users to any anomalies or changes.
2. Searching: Splunk offers users the ability to search through their data using keywords or specific criteria. The search results can be used to identify trends or correlations in the data.
3. Reporting: Splunk allows users to create reports from their data. Reports can be used for analysis and to identify areas of improvement.
4. Dashboards: Splunk offers users the ability to create custom dashboards to visualize their data. Dashboards can be used to quickly identify trends and potential areas of improvement.
5. Analytics: Splunk provides users with the ability to run analytics on their data. Analytics can be used to gain insights into the data and to identify patterns and correlations.
Splunk – Stats Command
The Splunk stats command is a statistical reporting command used to generate summary statistics of specified fields or expressions. It can be used to calculate the mean, count, sum, min, max, and other statistical values of the fields in the search results. It can also be used to group the search results by specified fields, and to sort the results in descending order. The stats command can also be used to create statistical trends over time, and to display the results in a graphical chart.
Finding Average
In Splunk, you can use the “stats avg” command to calculate the average across a set of results. This command can be used in combination with the “eval” command to create a new field with the average value. For example, the following command would calculate the average of the “sales” field and store the result in a new field called “average_sales”:
eval average_sales=avg(sales) | stats avg(average_sales)
Finding Range
The range in the stats command is used to restrict the results to the specified range of values for the specified field. This is typically used with numeric fields and the range is specified using the following syntax:
<field> [<=] <start_value> to <end_value> [<=]
For example:
stats count by status
where status <= 200 to 400
This will restrict the results to a range of values from 200 to 400 for the field “status”.
Finding Mean and Variance
Mean and variance can be calculated in Splunk by using the stats command. The syntax for this is:
| stats avg(<field>) as mean, stdev(<field>) as variance by <field>
This command will return the mean and variance of the specified field grouped by the specified field.