What is Log Analytics?
Log analytics is the science of analyzing raw data to make conclusions about that information. This information will be helpful to optimize processes to increase the overall efficiency of a business or system. When an analyst tries to find out an error or try to find out on which server it is actually running and then evaluate the logs, this will be a very time-consuming and tedious process. Here we are going to discuss how to visualize or Log data using the various visualization solutions. Log analysis allows us to place large logs in a central place and analyze it. Log analysis can be centralized or decentralized.
What is ELK Stack?
ELK Stack is a combination of three open-source tools which form a log management tool/platform that helps in deep searching, analyzing, and visualizing the log generated from different machines. It is a combination of Elasticsearch, Logstash, and Kibana. Each of these components has its role to play.
Elasticsearch is a tool that plays a major role in storing the log in the JSON format, indexing it, and allowing the searching of the logs. Elasticsearch is a tool that generally works on the data which has been collected. The data collected is being converted into or indexed to retrieve useful information when required.
- It’s a search engine/search server like any other search engine.
- No SQL-based database, i.e., cannot use SQL for queries; that’s why it’s fast in performance.
- Based on Apache Lucene and provides RESTful API
- Provides horizontal scalability, and reliability for real-time search
- It uses indexes to search, which makes it faster
Why use Elasticsearch
Elasticsearch provides approximation methods to provide relevant results for count distinct or percentage queries. It also has some support for streaming ingestion.
- Replace document store like MongoDB, Raven DB
- Blazingly fast search performance
- Highly Scalable
- De-normalized datastore
Logstash is an open-source tool used to collect, parse and filter Syslog as the input. Whatever data is coming from the servers, it is centrally taken, or it is centrally pulled by the Logstash tool into a central place, and it is further kept at a place where the Elasticsearch works upon that data. So, its primary role is to collect, parse, and Syslog data as the input.
So, it works as a pipeline where from one end, the data is input from the servers, which are there in the server form; from the other end, the Elasticsearch takes out the data and converts it into useful information. It centralized the data processing, collects, parses, analyzed the structured and unstructured data. Some of the features of Logstash are as follows:
- Data Pipeline tool
- Centralizes the data processing
- Collects parsed data and analyzes a large variety of structured/unstructured data and events
- Provides plugins to connect to various types of input sources and platforms
Kibana is a web interface which is allowing us to search, display and compile data. It is responsible for presenting the data in the visual format in the user interface. It shows reports in the form of charts, bar graphs, and other graphical representations. It is also very capable of providing any information in the form of a report. Its expertise can extend by using different plugins.
- Visualization tool
- Provides real-time analysis, summarization, representation in the form of charts, and debugging capabilities
- Provides an intuitive and user-friendly interface
- Allows sharing of snapshots of the logs searched through
- Permits saving the dashboard and managing multiple dashboards
Companies Using ELK Stack
Author: SVCIT Editorial Copyright
Silicon Valley Cloud IT, LLC.