Open Source Solutions for Log Analytics
A Better, Cheaper 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 organizations to look for more cost-effective alternatives. Open source log analytics solutions, with their customizability, speed, and affordability, have emerged as solid competitors of commercial software.
UNCOVER INSIGHTS, DEVELOP ACTIONABLE INTELLIGENCE THROUGH YOUR LOGS
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 customize 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 personalization, and fraud detection. We have assisted our customers in many open source migrations that delivered quantified ROI while minimizing business disruptions:
- See how our e-commerce customer increased conversions and improved operations with open source log analytics
- Read our case study about how we helped the Library of Congress leverage the Elastic Stack for log analytics
- 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: COST SAVINGS WITHOUT SACRIFICING POWERFUL FEATURES
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 customizable, 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 visualization 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 visualization.
Just like how we have helped our 800+ customers 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 customize your own log analytics stack? We can help you 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.