The ELK Stack: Elasticsearch, Logstash, Kibana.

ELK Stack is the leading open-source IT log management solution designed to offer a centralized logging solution free of cost. Elasticsearch, Logstash, and Kibana are used together to form an end-to-end stack (ELK Stack) and real-time data analytics tool that provides actionable insights from almost any type of structured and unstructured data source. Each of these products plays a different role in delivering one seamless stack:

• About Elasticsearch
• Elasticsearch Uses
• About Logstash
• Logstash uses
• About Kibana
• Kibana uses
• Why is ELK stack so popular?
• How does ELK Stack work?
• Advantages and Disadvantages
• Conclusion

Elasticsearch: Storage and analytics engine

Elasticsearch is an essential component of the ELK Stack designed for data ingestion, storage, analysis, and visualization. It is a distributed, free and open search and analytics engine for all data types, including textual, numerical, geospatial, structured, and unstructured.

What is Elasticsearch used for?

The speed and scalability of Elasticsearch and its ability to index many types of content makes it useful for so many cases

- Application search
- Logging and log analytics
- Security analytics
- Business analytics
- Site search
- Enterprise search
- Metrics and container monitoring
- Performance monitoring
- Geospatial data analysis and visualization

Logstash: Collection and transformation agent

Logstash is a free and open server-side data processing pipeline that ingests data from a multitude of sources, transforms it, and then sends it to your favorite "stash."

What is Logstash used for?

Logstash filters each event, identifies named fields of the building structure, and transforms them to converge on a standard format for better analysis and business value. It dynamically changes and prepares your data regardless of design or complexity:

- Ease overall processing, independent of the data source, format, or schema.
- Derive structure from unstructured data
- Decipher geo coordinates from IP addresses
- Anonymize PII data, exclude sensitive fields completely

Kibana: Search and data visualization

Kibana is a centralized hub for built-in solutions developed on the ELK stack. It also acts as a user interface for monitoring, managing, and securing the cluster.

What is Kibana used for?

Kibana's tight integration with Elasticsearch and the giant Elastic Stack makes it ideal for supporting the following:

Searching, viewing, and visualizing data indexed in Elasticsearch and analyzing the data by creating bar charts, pie charts, tables, histograms, and maps. A dashboard view combines these visual elements to then be shared via browser to provide real-time analytical views into large data volumes in support of use cases such as:

- Logging and log analytics
- Infrastructure metrics and container monitoring
- Application performance monitoring (APM)
- Geospatial data analysis and visualization
- Security analytics
- Business analytics

Monitoring, managing, and securing an Elastic Stack instance via the web interface.

Centralizing access for built-in solutions developed on the Elastic Stack for observability, security, and enterprise search applications.

Why is the ELK stack so popular?

ELK stack is high in demand because of its log analytics capability. The need for log management ad analytics solutions to monitor the infrastructure, server logs, application logs, etc., has led the ELK stack to become so popular in the log analytics space. It offers a robust solution for developers and DevOps engineers to gain valuable insights on failure diagnosis, performance, and monitoring.

How does the ELK stack work?

The Logstash gets the logs from inconsistent formats and over different protocols and places these logs into a system called Elasticsearch. Elasticsearch allows you to perform accurate time searches and analyses of your data. Kibana then provides a visualization and exploration system on top of Logstash and Elasticsearch so you can easily understand your data in terms of charts and graphs.

Advantages and Disadvantages of ELK stack

Advantages

- Quick installation
- Easy to deploy vertically and horizontally
- Readily available libraries for various programming languages
- It offers remarkable insights and eliminates the need to log into a hundred log data sources
- host of language clients, including Ruby. Python. PHP, Perl, .NET, Java, and JavaScript, and more

Disadvantages

- Different components In the stack can become challenging to handle when you move on to a complex setup.
- There's nothing like trial and error. Thus, the more you do, the more you learn along the way.

Conclusion

Server applications require a centralized logging system, which can be challenging to maintain and sometimes expensive. ELK server stack is instrumental in resolving issues related to centralized logging systems, and we hope that with the help of this article, you now have a fair idea of when and how to use the ELK stack in a real-time scenario.