Why Use ELK Stack?

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ELK is an acronym for Elasticsearch, Logstash and Kibana, a consolidated data-analyses system. The three open-source programs were originally separate projects, but were united into the ELK stack by open-source software developer Elastic to provide DBAs greater control and flexibility over database search and analysis functions. Companies both large and small can benefit from ELK’s analytics as the ELK stack has the ability to perform time-based analysis in conjunction with free open-source software. Stick with us to learn why you might use the ELK stack.

Elasticsearch, Logstash and Kibana

  • Elasticsearch is a free Java-based, open source, RESTful search engine designed, built, distributed and licensed by Apache. It can perform diverse indexing, search and analysis functions using common RESTful APIs and JSON files.

  • Logstash provides structure to data, such as parsing unstructured logs, and transmitting the data to Elasticsearch.

  • Kibana produces clear and vivid graphs and dashboards to help visualize the raw data returned by Elasticsearch.

Why Use ELK Stack?

In a data-driven world, databases must constantly handle increasingly larger amounts of data. Typically, analytic processes slow down as the amount of data a system handles continues to increase. The ELK stack can help increase these analytic processes. A brief overview of the benefits of the ELK stack include:

  • ELK is a total log-analysis platform for search, analyses and visualization of log-generated data from different machines.

  • ELK can securely pull, analyze and visualize data, in real time, from any source and format.

  • ELK can perform centralized logging to help identify any server and application-related issues across multiple servers and correlate the logs in a particular time frame.

  • ELK is geared to handle big data to provide crucial business insights.

  • ELK is simple to use, set up and is user friendly.

  • As an open-source program, Elk is highly cost effective.

Log Analytics

Dozens of servers running multiple applications results in a lot of data to analyze. Logs are one of the most critical, but often overlooked, data sources. Within a company’s web-server logs, each individual log file holds mostly unstructured information that is difficult, or sometimes, impossible to interpret. ELK is able to quickly analyze the log data and to identify opportunities as well as possible vulnerabilities.

It is critical to understand how the system is working whenever problems arise. Having the ability to quickly locate the needed information will help expedite operations-related tasks and resolve problems. Additionally, adding metrics to correlate logs provides increased visibility to help see the log history, what is currently happening and also predict where a trend is headed.

DBAs typical have to log on to multiple machines and comb through numerous files when an error occurs. The larger the system is the bigger a nightmare this becomes. ELK being able to turn this migraine-sized problem into a minor annoyance is a major reason as why use ELK stack.

Problems with ELK Stack

When DBAs first begin analyzing logs they often experience data-structure, or mapping, problems. Mappings is defined as what fields a documents has and what the purpose of those fields are intended to do. The ability of a field’s functions will depend on the field’s configuration. Users can sometimes experience performance related issues, such as finding the most efficient way to utilize mapping on their servers.


To answer the question, “Why Use ELK Stack?,” ELK Stack is one of the most popular and easy-to-learn log-analyses platforms in use worldwide. Even though ELK is well suited to handling big data for large corporations, the ELK stack is also a very valuable suite for smaller companies running smaller systems. While there are some very good tutorials on how to get started with the open-source platform, the Elk stack is fairly intuitive for even moderately experienced DBAs. For users with non-standard logs, Apache can be used to run Logstash to transfer data to Elasticsearch and then create visualizations with Kibana. While building a complicated dashboard may not be a snap initially, all it takes is a little patience and practice to become proficient. In addition to all the amazing features and benefits the ELK stack offers users, its hard to beat free.

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