Log management and security | SIEM | ELK Stack
Apr 10, 2023

ELK Stack – Unlocking the value of Data Visualization and Log Management

Vishal Dilip Sanghi

The Need

In today’s changing dynamics of business, various specialized IT tools have been introduced. These tools are specialized in monitoring multiple IT infrastructure domains like servers, network devices, storage/backup devices, etc. These tools of modern businesses generate vast amounts of logs and monitoring data daily. Organizations face critical challenges in using this data. It is not humanly possible to analyze these data with the use of regular Excel or basic tools. Hence, there is a need for a specialized tool like ELK stack, which not only provides a mechanism of capturing the data but also provides the analytics and visualization engine to provide insightful information from the raw data to do the right decision-making.

This article helps explore the details around the ELK stack, its importance in today’s business era, and its relevance to various IT domains and log management strategies.

ELK Stack

ELK Stack (Elasticsearch, Logstash, Kibana, and Beats) has emerged as a powerful open-source solution for capturing log data, analyzing log data, and providing insightful visualization for decision-making. It mainly consists of four major components:

  1. Elastic Search
  2. Logstash
  3. Kibana
  4. Beats

Elasticsearch: Elasticsearch provides high-speed search capabilities, real-time analytics, and scalability. As a distributed search and analytics engine, Elasticsearch stores and indexes data for processing the right information useful for decision-making.

Logstash: Logstash is used for ingesting data from different sources, including logs, metrics, and web applications. It is a data processing pipeline that collects, transforms, and filters data from various sources and sends it to Elastic Search.

Kibana: Kibana provides a user-friendly interface to create visualizations, dashboards, and reports based on the data processing done at Elastic Search. It is a data visualization and exploration tool that enables users to interact with data stored in Elasticsearch.

Beats: Beats is a set of data shippers that collect log data from various sources and send it to Logstash for processing the data and ingesting into the data processing pipeline.

Why ELK Stack?

There are several reasons why organizations are using the ELK Stack for log management across various IT domains. Some of the key reasons include:

Scalability: The ELK Stack can handle large volumes of log data, making it a suitable solution for organizations with huge amount logs as well as time series data.

Customization: The ELK Stack is highly customizable, allowing organizations to adjust the solution to their needs and requirements.

Flexibility: The ELK Stack can be utilized for a wide range of log management across various IT domain use cases, from simple log monitoring to complex processing of time series data for decision making and anomaly detection.

Integration: The ELK Stack can be easily integrated with different tools and systems, providing organizations with a comprehensive log management and time series data management solution.

ELK Stack – Usage in Key IT Domains

Application / Website Performance Management

Customer experience is the key and digital customer interaction is the new normal. That is why at Microland, we focus on “Making Digital Happen” for our customers.

Digital customer interaction refers to how businesses use several digital channels, such as websites, mobile apps, social media platforms, and messaging apps to engage with their customers. As more and more customers prefer to interact with businesses online, digital interaction is becoming increasingly important in today's digital age.

Studies show that 40% of web users expect a load time of 2 seconds or less. As load time increases, visitors will abandon your site. Poor performance impacts site usability, meaning people leave before you can convert them. A slow-loading website often results in page abandonment, lost revenue, and visitors never returning.

  • Customers who do not have confidence in your site’s performance will abandon it within 3 seconds
  • A slow website can increase abandonment by 75%.
  • The first five seconds of page-load time is crucial for conversion rates

The ELK stack can play a major role in solving such problems on the real-time as well as in some cases proactive basis. This depends upon how deep organization can use the ELK platform. Ideally there is no limit to it. In this use case, the ELK stack can help organizations do the following:

  • Monitor, analyze, and alert on performance and uptime across organization IT infrastructure.
  • Centralized operations management for ingesting different types of data across multiple toolsets.
  • Efficiently collect and store granular data, such as detailed event logs, resource usage metrics, and application traces, with their timestamps to troubleshoot website errors and performance on real-time basis.
  • Deliver comprehensive insights across the entire ecosystem, including cloud-native apps, backend dependencies, and third-party services.
  • Measure key performance indicators (KPIs) for end user experience with custom dashboards and custom visualizations specific to organization needs.
  • Accelerate root cause and anomaly detection with machine learning and actionable insights. This is where proactive actions can be taken even before the issue occurs.

On top of what is mentioned above, Elastic Search component capabilities will help organizations understand the user's browsing behavior, improving customer retention and optimizing costs.

While this use case especially talks about application/website performance management, the concept applies to various other areas of the IT infrastructure domain. The use cases can be at the application or hardware component levels. However, the insightfulness that an organization gets will remain almost the same.

Log Management Strategy and Approach

Define Objectives: Organizations need to understand their goals to make the most of log management with the ELK Stack. These goals will help to determine the specific requirements for the solution, such as the types of logs to collect and the incidents to detect.

Plan your Project: Organizations must plan their ELK Stack project once the objectives are defined. Planning your project includes determining hardware and software requirements, choosing the right Beats for their environment, and planning their log pipeline.

Implement Best Practices: To ensure effective log management with the ELK Stack, organizations should implement the following best practices:

  • Properly configure logging on all systems and applications
  • Use role-based access control (RBAC) to restrict access to log data to authorized users only
  • Use encryption to secure log data in transit and at rest
  • Regularly review logs for signs of security incidents
  • Archive the log data on the regular basis to keep the system performance consistent

Additional Tip

There are various useful Integrations of ELK Stack with other data visualization tools available as open source in the internet market. An excellent alternative to replacing only the Kibana visualization engine is Grafana which provides many more functional capabilities. 

Final Thought

The ELK Stack is a powerful open-source solution that provides powerful data analytics that can handle large-scale data processing and analysis tasks. IT and DevOps teams can use the ELK Stack to monitor system logs, application logs, and other types of log data to identify issues and improve system performance in real-time or proactively. The ELK Stack is highly scalable and flexible, making it an ideal log management solution for various organizations.

Organizations can also effectively manage their logs and secure their systems and applications by centralizing log data, utilizing Kibana for log analysis, implementing alerts and notifications, regularly monitoring records, and evaluating and fine-tuning the ELK Stack.

However, implementing the ELK Stack requires careful planning, a knowledgeable team, and effective implementation and usage strategies. Organizations can effectively implement the ELK Stack and achieve their log management objectives by following the right strategy, proper project planning, and using various best practices that EKL documentation provides.