BigData
10 Best Data Analytics Tools for Big Data Analysis (2021)
Big Data Analytics software is widely used in providing meaningful analysis of a large set of...
The ELK Stack is a collection of three open-source products — Elasticsearch, Logstash, and Kibana. They are all developed, managed ,and maintained by the company Elastic.
ELK Stack is designed to allow users to take to data from any source, in any format, and to search, analyze, and visualize that data in real time.
ELK provides centralized logging that be useful when attempting to identify problems with servers or applications. It allows you to search all your logs in a single place. It also helps to find issues that occur in multiple servers by connecting their logs during a specific time frame.
In this tutorial, you will learn
Here is the simple architecture of ELK stack
However, one more component is needed or Data collection called Beats. This led Elastic to rename ELK as the Elastic Stack.
While dealing with very large amounts of data, you may need Kafka, RabbitMQ for buffering and resilience. For security, nginx can be used.
Let's deep drive all of these open source products:
Elasticsearch is a NoSQL database. It is based on Lucene search engine, and it is built with RESTful APIS. It offers simple deployment, maximum reliability, and easy management. It also offers advanced queries to perform detail analysis and stores all the data centrally. It is helpful for executing a quick search of the documents.
Elasticsearch also allows you to store, search and analyze big volume of data. It is mostly used as the underlying engine to powers applications that completed search requirements. It has been adopted in search engine platforms for modern web and mobile applications. Apart from a quick search, the tool also offers complex analytics and many advanced features.
Features of Elastic search:
Advantages of Elasticsearch
Important Terms used in Elastic Search
Term | Usage |
Cluster | A cluster is a collection of nodes which together holds data and provides joined indexing and search capabilities. |
Node | A node is an elasticsearch Instance. It is created when an elasticsearch instance begins. |
Index | An index is a collection of documents which has similar characteristics. e.g., customer data, product catalog. It is very useful while performing indexing, search, update, and delete operations. It allows you to define as many indexes in one single cluster. |
Document | It is the basic unit of information which can be indexed. It is expressed in JSON (key: value) pair. '{"user": "nullcon"}'. Every single Document is associated with a type and a unique id. |
Shard | Every index can be split into several shards to be able to distribute data. The shard is the atomic part of an index, which can be distributed over the cluster if you want to add more nodes. |
Logstash is the data collection pipeline tool. It collects data inputs and feeds into the Elasticsearch. It gathers all types of data from the different source and makes it available for further use.
Logstash can unify data from disparate sources and normalize the data into your desired destinations. It allows you to cleanse and democratize all your data for analytics and visualization of use cases.
It consists of three components:
format
Features of Logstash
Advantage of Logstash
Kibana is a data visualization which completes the ELK stack. This tool is used for visualizing the Elasticsearch documents and helps developers to have a quick insight into it. Kibana dashboard offers various interactive diagrams, geospatial data, and graphs to visualize complex quires.
It can be used for search, view, and interact with data stored in Elasticsearch directories. Kibana helps you to perform advanced data analysis and visualize your data in a variety of tables, charts, and maps.
In Kibana there are different methods for performing searches on your data.
Here are the most common search types:
Search Type | Usage |
Free text searches | It is used for searching a specific string |
Field-level searches | It is used for searching for a string within a specific field |
Logical statements | It is used to combine searches into a logical statement. |
Proximity searches | It is used for searching terms within specific character proximity. |
Features of Kinbana:
Advantages and Disadvantages of Kinbana
In cloud-based environment infrastructures, performance, and isolation is very important. The performance of virtual machines in the cloud may vary based on the specific loads, environments, and number of active users in the system. Therefore, reliability and node failure can become a significant issue.
Log management platform can monitor all above-given issues as well as process operating system logs, NGINX, IIS server log for web traffic analysis, application logs, and logs on AWS (Amazon web services).
Log management helps DevOps engineers, system admin to make better business decisions. Hence, log analysis via Elastic Stack or similar tools is important.
Elk | Splunk |
Elk is open source tool | Splunk is a commercial tool. |
Elk stack does not offer Solaris Portability because of Kibana. | Splunk offers Solaris Portability. |
Processing speed is strictly limited. | Offers accurate and speedy processes. |
ELK is a technology stack created with the combination Elastic Search-Logstash-Kibana. | Splunk is a proprietary tool. It provides both on-premise and cloud solutions. |
In ELK Searching, Analysis & Visualization will be only possible after the ELK stack is setup. | Splunk is a complete data management package at your disposal. |
ELK does not support integration with other tools. | Splunk is a useful tool for setting up integrations with other tools. |
NetFlix
Netflix heavily relies on ELK stack. The company using ELK stack to monitor and analyze customer service operation's security log. It allows them to index, store, and search documents from more than fifteen clusters which comprise almost 800 nodes.
The famous social media marketing site LinkedIn uses ELK stack to monitor performance and security. The IT team integrated ELK with Kafka to support their load in real time. Their ELK operation includes more than 100 clusters across six different data centers.
Tripwire:
Tripwire is a worldwide Security Information Event Management system. The company uses ELK to support information packet log analysis.
Medium:
Medium is a famous blog-publishing platform. They use ELK stack to debug their production issues. The company also uses ELK to detect DynamoDB hotpots. Moreover, using this stack, the company can support 25 million unique readers as well as thousands of published posts each week.
Advantages
Disadvantages
Summary
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