In this Splunk tutorial, you will learn Splunk from the basics to get a clear idea of why Splunk is the go-to tool when it comes to machine-generated data. Splunk is a powerful engine extensively used for searching, investigating, monitoring, troubleshooting, alerting, and reporting on machine-generated data which is such a big part of today’s data-driven world. Splunk can be called Google for machine-generated data.
In this tutorial on Splunk, you will learn the following topics :
What is Splunk?
First, let us compare Splunk with ELK (Elastic, Logstash, Kibana) stack which also does a similar kind of job.
||ELK (ElasticSearch, Logstash, and Kibana)
|Technology used for indexing
||C++ based proprietary
||Java-based Apache Lucene
|Technology used for searching
||Apache Lucene based
|Language used for search
||Splunk Processing Language
|REST API for search interface
Splunk is used for extracting value out of machine-generated data. It can be thought of as a data mining tool for big data applications. Splunk can effectively handle big data with no decrease in performance. The best part of Splunk is that it does not need any database to store its data as it extensively makes use of its indexes to store the data.
Splunk is an absolutely fast engine and provides lightning-fast results. You can troubleshoot any issue by resolving it with instant results and doing an effective root cause analysis. Splunk can be used as a monitoring, reporting, analyzing, security information, and event management tool among other things. Splunk takes valuable machine-generated data and converts it into powerful operational intelligence by delivering insights through reports, charts, and alerts.
Watch this Splunk Tutorial video:
The Splunk Architecture comprises three main components. These components are as follows:
- Splunk Forwarder
- Splunk Indexer
- Search Head
Now let us understand the meaning of all these components so as to better understand the entire Splunk Architecture.
The Splunk Forwarder is used to collate real-time data so as to enable real-time data analysis by the users. The Splunk Forwarder collects all of the log’s data and sends it to the indexer. In carrying out all these activities, the Splunk Forwarder consumes less processing power than other traditional monitoring tools. There are 2 types of Splunk Forwarders. These are:
- Splunk Universal Forwarder
- Splunk Heavy Forwarder
The Splunk Indexer is used for indexing and storing the data that is received from the Splunk Forwarder. It basically transforms data into events, stores and adds them to an index, which in turn enhances searchability. The data received from the Splunk Forwarder is first parsed so as to remove any unwanted data and then the indexing is done. In this entire process, the Splunk Indexer creates the following files and later bifurcates them into various directories called buckets:
- Compressed raw data
- Indexes pointing to raw data (.TSIDX files)
- Metadata files
Splunk Search Head
It is basically a graphical user interface where the user can perform various operations as per his/her requirements. In this stage, the users can easily interact with Splunk and perform search and query operations on Splunk data. The users can feed in the search keywords and get the result as per their requirement.
The following diagram shows how the above components work together in the Splunk Architecture:
What is Splunk used for?
Splunk is a software platform used for performing monitoring, searching, analyzing and visualizing real-time machine-generated data. Its usage in indexing, correlating and capturing real-time data is very important and highly recognized. Also, Splunk is used in producing and creating graphs, dashboards, alerts and interactive visualizations.Using Splunk, organizations can easily access data and arrive at solutions to complex business problems too.
Features of Splunk
Here in this section of the Splunk tutorial, we will discuss some of the top features of Splunk.
- One of the biggest strengths of Splunk is real-time data processing
- The input data for Splunk could be in any format like CSV, JSON, and others
- You can easily search and investigate a particular result with Splunk
- It lets you troubleshoot any condition of failure for improved performance
- You can monitor any business metrics and make an informed decision
- It is possible to visualize and analyze the results through powerful dashboards
- You can analyze the performance of any IT system with the Splunk tool
- Splunk even lets you incorporate Artificial Intelligence into your data strategy.
Know how Splunk Integrated with Hadoop is the best combination for extracting quick insights in this Splunk Analytics for Hadoop blog.
Applications of Splunk
We will discuss some of the applications of Splunk to give you a brief idea about the vast possibilities of Splunk.
- You can deploy Splunk for web analytics to understand KPIs and improve performance
- It is used in IT operations to detect intrusion, breaches, and network abusers
- Tracking, analyzing, and fine-tuning digital marketing initiatives with Splunk
- Working in conjunction with the Internet of Things is a big part of Splunk’s future
- It is used in industrial automation systems to see everything is working as expected
- Advising cybersecurity personnel on the best course of action for securing IT systems.
Watch this Splunk Tutorial for Beginners video:
Splunk Dashboards contain data visualization displays such as tables, charts, lists, maps etc. Each of these panels provide the visualization results using a base. You can build and edit dashboards using the Splunk Web dashboard editor, which is the user interface in Splunk Light. The created dashboards can also be edited using Simple XML source code.
The following steps can be used to build the dashboard :
- Firstly, you need to add content. This can be done by creating searches that power up the dashboard, saving searches as reports, or creating panels for reuse.
- Next step will be to create or design the user interface. For designing, perform dashboard modifications using panels, visualizations and forms.
- Next step is adding interactivity. Though this is an optional step, users may give it a try. This step basically involves adding interactivity to the dashboard using forms.
- Next step would be to customize the dashboard. Users can add custom features to enhance the customization.
- Finally, use Splunk Web Dashboard Editor to build and edit your dashboard.
Why should you learn Splunk?
In this section of the Splunk tutorial, you will find out why you need to learn Splunk. As we discussed before, Splunk is the Google for machine data, and going forward this machine data will be a major chunk of the big data that is being generated at breakneck speeds. So if you learn Splunk then you have a very bright future thanks to the increased deployment of Splunk in mission-critical applications cutting across industry verticals. Today, regardless of the industry vertical, It is being implemented for indexing data, facilitating Splunk search and investigation, mapping knowledge to search, scheduling alerts, and creating extensive reports and visualizations to aid business growth.
Interested in learning Splunk? Enroll in our Splunk Training now!
This Splunk tutorial is meant as the first step for anybody who wants to learn Splunk and excel in their career. Software developers, system administrators, database experts, search analysts can benefit from this Splunk tutorial.
There are no prerequisites for learning from this Splunk tutorial. If you have a knowledge of Data Analytics concepts, then it is good. In this, you will learn the basics of Splunk, and in the next tutorial, you will learn Introduction to Splunk