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Open Source Solutions for Log Analytics

Maximising ROI with A Cost-Effective Approach to Log Management and Analysis

Log analysis is a powerful way to improve operational performance in IT and business. For most systems administrators, development operations (DevOps), and business analysts, commercial log analytics products offer ease of use, powerful advanced features, and a large ecosystem of useful plug-ins.

However, the exponential growth of data from application and server logs - plus the associated licensing/storage costs - have led many organisations to look for more cost-effective alternatives. Open source log analytics solutions, with their customisability, speed, and affordability, have emerged as solid competitors of commercial software.


Days of open source's limited functionalities, security, or control have passed. In the age of big data and advanced search techniques, open source log analytics solutions enable you to:

  • Implement secure log file management for high-volume transaction systems that are intolerant of data loss.
  • Scale and customise to full-fledged enterprise-class analytics platform for business intelligence.
  • Execute complex queries from large datasets in seconds via a user-friendly interface, without relying on SQL.

Common log analytics use cases include risk management, compliance, security analysis, market intelligence, e-commerce personalisation, and fraud detection. We have assisted our customers in many open source migrations that delivered quantified ROI while minimising business disruptions. 

Click here to view our v-blog on how we leveraged open source big data to process 600+ GB daily for more efficient, cost-effective log analytics.


Open source log analytics stacks can provide a full range of commercial products' features combined with:

  • Enhanced agility and flexibility
  • Reduced licensing costs
  • Real-time search, analysis, alerts, and reports
  • On-premise or in the cloud without a dedicated cluster
  • Analysis of all machine generated logs (structured and unstructured)
  • Fully customisable, distributed architecture

For instance, Elastic’s open source Elasticsearch, Logstash, and Kibana (ELK stack) can reduce your licensing costs and thus increase your ROI. The ELK stack can store multiple petabytes of data in one cluster and combine clusters for horizontal scaling, providing a powerful tool for log analytics as well as a versatile foundation for other big data applications.


  • Elasticsearch: direct import of log files into a search engine for indexing and easy access through search
  • Logstash: collection, storage, and parsing of logs
  • Kibana: reporting and visualisation capabilities using a browser interface

With the addition of Beats – Elasticsearch data shippers that support all data types - the ELK stack has grown into the new, fully-integrated Elastic Stack. Together, Elasticsearch, Logstash, Kibana, and Beats bring an enhanced open source log analytics platform for real-time data analysis and visualisation. 


Just like how we have helped our 800+ customers to implement successful search and analytics projects, we bring our experience and partnerships with open source big data leaders like Elastic, Solr, Hadoop, and Cloudera to provide you:

  • Deep expertise and a vendor agnostic approach, from strategy to implementation and support
  • Lower total cost of ownership of your log analytics solution
  • Ability to leverage NoSQL and big data technologies for faster results and more accurate decision-making
  • Rapid deployment with immediate visibility into events and operational trends
  • Community-driven, business-focused enhancement processes

Looking to customise your own log analytics stack? We can help you to build it from a wide range of both open source and commercial tools, such as Solr, Flume, Hue, Lucidworks, Pentaho Analytics and Data Integration, HighCharts, D3 Charts, Search Technologies' Aspire, and others. 


Contact us to get started or find out if open source log analytics solutions are right for you. Still evaluating your options? Read our blog on open source vs. commercial log analytics tools.