What is Splunk? Beginners Tutorial

What is Splunk? Beginners Tutorial

In this article, we will be looking into Splunk overview, its architecture, features,life-cycle and different commands used in it.

What is Splunk?

The platform of Splunk allows us to get visibility into machine data generated from
different networks, servers, devices, and hardware.

It can give us insights into the application management, threat visibility, compliance, security, etc. so it is used to analyze machine data. The data is collected from the forwarder from the source and forwarded to the indexer. The data is stored locally on a host machine or cloud. Then on the data stored in the indexer the search head searches, visualizes, analyzes and performs various other functions.

Why use Splunk

  • It reduces troubleshooting and resolving time by offering instant results.
  • With the help of Splunk UI we can able to generate graphs, alerts, and dashboards on real-time data.
  • Summarizing and collecting valuable information from different logs and other important sources.
  • Offers most powerful search analysis, and visualization capabilities to empower users of all types.
  • It can easily search and investigate specific results using Splunk.
  • It allows you to troubleshoot any condition of failure for improved performance.
  • Helps us to monitor any business metrics and make an informed decision.
  • Splunk allows you to incorporate Artificial Intelligence into your data strategy.
  • Allows us to gather useful Operational Intelligence from your machine data
  • Allows us to create a central repository for searching Splunk data from various sources.

Splunk Features

Data Ingestion
Splunk can ingest a variety of data formats like JSON, XML and unstructured machine data like web and application logs. The unstructured data can be modeled into data the structure as needed by the user.
Data Indexing
The ingested data is indexed by Splunk for faster searching and querying on different conditions.
Data Searching
Searching in Splunk involves using the indexed data for the purpose of creating metrics, predicting future trends and identifying patterns in the data.
Splunk Alerts
Splunk alerts can be used to trigger emails or RSS feeds when some specific criteria are found in the data being analyzed.
Splunk Dashboards can show the search results in the form of charts, reports, and pivots, etc.
Data Model
The indexed data can be modeled into one or more data sets that are based on specialized domain knowledge. This leads to easier navigation by the end-users who analyze the business cases without learning the technicalities of the search processing the language used by Splunk.

Splunk Architecture and Different Components

The main components of Splunk are Forwarders, Indexers and Search Heads.
Deployment Server (or Management Console Host) will come into the picture in case of a larger environment.

Deployment servers act as an antivirus policy server for setting up Exceptions and Groups so that you can map and create a different set of data collection policies each for either window-based server or a Linux based server or a Solaris based server.

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Splunk Architecture

Splunk has four important components:

Indexer – It indexes the machine data

Forwarder – It collects data from a remote machine and then forward that data to index on a real-time basis.

Search Head – It Provides GUI for searching, analysis and visualization.

Deployment Server –Manages the Splunk components like indexer, forwarder, and search head in a computing environment.

SPL Commands in Splunk

Search Processing Language (SPL) is a language containing different commands, functions, arguments, etc, which we write to get the desired results from the data sets.

For example, when we obtain a result set for a search term, we may need to further filter that with more specific terms from the result set. For this, we may need some additional commands to be added to the existing command. This can be done by using SPL.

Categories Of SPL Commands

SPL commands are divided into five categories:

1.      Sorting Results – Ordering results and (optionally) limiting the number of results.

2.      Filtering Results – It takes a set of events or results and filters them into a smaller set of results.

3.      Grouping Results – Grouping events so you can see patterns.

4.      Filtering, Modifying and Adding Fields – Taking search results and generating a summary for reporting.

5.      Reporting Results – Filtering out some fields to focus on the ones.

Splunk Buckets and its Life-Cycle

A directory that contains indexed data is known as a Splunk bucket. It also contains events of a certain period. Bucket life-cycle includes the following stages:

Hot – It contains newly indexed data and is open for writing. For each index, there
are one or more hot buckets available.

Warm – Data rolled from hot.

Cold – Data rolled from warm.

Frozen – Data rolled from cold. The indexer deletes frozen data by default, but users can also archive it.

Thawed – Data restored from an archive. If you archive frozen data, we can later
return it to the index by thawing (defrosting) it.

Alerts in Splunk

An alert is an action that a saved search triggers on regular intervals set over a time range, based on the results of the search.

When the alerts are triggered, various actions occur consequently. For instance, sending an email when a search to the predefined list of people is triggered.

Three types of alerts:

1. Pre-result alerts: Most commonly used alert type and runs in real-time for an alt time span. These alerts are designed such that whenever a search returns a result, they are triggered.

2. Scheduled alerts: The second most common- scheduled results are set up to
evaluate the results of a historical search result running over a set time range on a regular schedule. You can define a time range, schedule and the trigger condition to an alert.

3. Rolling-window alerts: These are the hybrid of pre-result and scheduled alerts.

Like the former, these are based on real-time search but do not trigger each
time the search returns a matching result. It examines all events in real-time mapping within the rolling window and triggers the time that specific condition by that event in the window is met, like the scheduled the alert is triggered on a scheduled search.



My Name is Ankur Jain and I am currently working as Automation Test Architect.I am ISTQB Certified Test Manager,Certified UI Path RPA Developer as well as Certified Scrum Master with total 12 years of working experience with lot of big banking clients around the globe.I love to Design Automation Testing Frameworks with Selenium,Appium,Protractor,Cucumber,Rest-Assured, Katalon Studio and currently exploring lot in Dev-OPS as well. I am currently staying in Mumbai, Maharashtra. Please Connect with me through Contact Us page of this website.

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