What Is Splunk? "Splunking" of Data and More
Splunk is a big data platform that simplifies the task of collecting and managing massive volumes of machine-generated data and searching for information within it. The technology is used for business and web analytics, application management, compliance, and security.
Splunk is an advanced and scalable form of software that indexes and searches for log files within a system and analyzes data for operational intelligence. The software is responsible for splunking data, which means it correlates, captures, and indexes real-time data, from which it creates alerts, dashboards, graphs, reports, and visualizations. This helps organizations recognize common data patterns, diagnose potential problems, apply intelligence to business operations, and produce metrics.
Splunk’s software can be used to examine, monitor, and search for machine-generated big data through a browser-like interface. It makes searching for a particular piece of data quick and easy, and more importantly, does not require a database to store data as it uses indexes for storage.
A Brief History of Splunk
Splunk was founded in 2003 by Rob Das and Eric Swan, who aimed to provide a solution to the “information caves” that organizations struggled with. The name Splunk came from the term “spelunking,” which is a term describing the hobby of exploring caves. The co-founders developed the technology to create a search engine that could log files stored within a system’s infrastructure. They aimed to market it in bulk, enabling the technology to be deployed in any use case.
Splunk’s first version launched in 2004 and gradually grew in popularity with organizations, which increasingly purchased enterprise licenses.
Why Do We Need Splunk?
Splunk is particularly noted for its high performance and scalability, as well as the innovative way in which it collects and presents data. However, the technology can be quite complex to set up and manage.
Key benefits of Splunk include:
- The technology creates analytical reports through interactive charts and graphs, which it can then share with users.
- A Splunk log is highly scalable and easy for organizations to implement.
- It is able to find useful information within organizations’ data without users having to identify it themselves.
- It saves searches and tags that it recognizes as important information, which helps organizations make their systems smarter.
- Its dashboard offers an enhanced graphical user interface (GUI) and real-time visibility.
- Instant results ensure users spend less time troubleshooting and resolving issues.
- It provides improved performance by troubleshooting conditions and monitors business metrics to enable informed decisions.
- It enables organizations to build artificial intelligence (AI) into their data strategies and gain operational intelligence from their machine data.
- It can gather any form of data, including CSV, JSON, and log formats.
- Organizations can create a central repository that allows them to search Splunk data from multiple sources and extract data through functionalities like Rex in Splunk.
Common disadvantages of the technology include:
- Deploying Splunk can become expensive when managing large volumes of data.
- Optimizing searches to improve speed can be tricky and impractical.
- The tool’s dashboards are not as reliable as other tools such as Tableau.
- Open-source tools are constantly aiming to replace Splunk.
Features of Splunk
Accelerate Development and Testing
Splunk features a rich development environment that enables users to rapidly build applications through approved programming frameworks and languages.
Build Real-time Data Applications
Splunk users can build real-time data applications by using software development kits (SDKs) to drive big data insights. This removes the need for large-scale development and helps developers quickly get started with the Splunk platform.
Developers can quickly get up and running on Splunk without requiring large-scale development or major spending on hardware. This provides a great return on investment (ROI) and a rapid time-to-value return.
Agile Statistics and Reporting with Real-time Architecture
Splunk provides powerful analytics that enables organizations to more easily and quickly analyze their data.
Offers Search, Analysis, and Visualization Capabilities to Empower Users of All Types
Splunk’s intuitive user experience ensures improved productivity by providing instant access to applications and content. This allows users of all types to take advantage of the software’s search, analysis, and visualization capabilities.
What Are the Different Versions of Splunk?
Universal Forward (UF)
This is a lightweight element that forwards or pushes data from the server into the heavy Splunk forwarder. It can easily be installed on the application side or at the client side.
Load Balancer (LB)
The load balancer improves the distribution of organizations’ workloads across multiple computing resources. It distributes application or network traffic across a cluster of servers.
Heavy Forwarder (HF)
The heavy forwarder is the heavy element that enables organizations to filter data and accumulate error logs.
The indexer processes incoming data in real time. It is also responsible for storing and indexing filtered data, such as date, hosts, sources, and time. It helps improve the performance of the Splunk platform.
Search Head (SH)
This is a Splunk instance that enhances the distribution of searches to other indexers. The search head does not have its own instance but is used to boost intelligence and reporting.
Deployment Server (DS)
The deployment server helps deploy a configuration, such as updating the UF’s configuration file. It can also be used to share data between Splunk components.
License Manager (LM)
A Splunk Enterprise state known as a license slave is controlled by a license master. Within a single instance, the license master helps out as the license manager. A Splunk license is based on organizations’ quantity and usage, which are examined daily.
How Splunk Works
Splunk works through a forwarder collecting data from remote machines and forwarding it on to an index. An indexer then processes that data in real time and stores and indexes it on the disk. End-users then interact with Splunk through the search head, which enables them to search, analyze, and visualize data.
Splunk vs. ELK Stack vs. Sumo Logic
Splunk certification makes data analysis easy because forwarders are preconfigured for a wide range of data sources. Splunk was the first log analysis software to go to market and remains the market leader.
ELK Stack is made up of three open-source systems, Elasticsearch, Kibana, and Logstash, which are all managed by Elastic. Elasticsearch is a NoSQL database, data processing tool Logstash populates Elasticsearch with data, and Kibana enables analysis through dashboards and visualizations.
Sumo Logic is a cloud-based analytics tool launched in 2010 and is a challenger to Splunk. Like Splunk, it transforms machine-generated data into actionable insights and simple-to-understand visual charts and graphs.
How Fortinet Can Help
The Fortinet FortiGate App for Splunk combines security information and event management (SIEM) with leading threat prevention solutions. This Fortinet tool aggregates, analyzes, and visualizes data and log events and improves detection, recovery, and response to advanced threats. It enables organizations to spot anomalous behavior, sort and deduplicate threats, and discover security breaches across various domains and geographic locations.
Additionally, it absorbs a high volume of logs in real time and offers visual insights that examine threat intent, backdoor viruses, and unexpected information flows across organizations’ cloud and data-center environments.