IT systems and applications generate more and more machine data due to millions of mobile devices, Internet of Things, social network users, and other new emerging technologies. However, organizations experience challenges when monitoring and managing their IT systems and technology infrastructure. They struggle with network and server monitoring/troubleshooting, security analysis, custom application monitoring and debugging, compliance standards, and others.
This session discusses how to solve the challenges of analyzing Terabytes and more of different log data to leverage the “digital business” – a term defined by Gartner and others to explain that IT is not just a tool to enable a business, but IT is the business.
The main part of the session compares different solutions for operational intelligence and log analytics to create “digital business”, such as Splunk, TIBCO LogLogic and the open source “ELK stack” (ElasticSearch, Logstash, Kibana).
A common use case will be demonstrated in a live demo: Monitoring, analyzing and correlating a complex E-Commerce transaction running through different custom applications such as a Java EE web application, an integration middleware and analytics processes.
The end of the session explains the distinction of the discussed solutions to Apache Hadoop, and how they can complement each other in a big data architecture.
Keywords:
Big Data, Log Management, Log Analytics, IT Operations Analytics, ITOA, Gartner, Forrester, SIEM, Security, Open Source, Cloud, SaaS, Middleware, Hardware Appliance, SOA, Microservices, Hadoop, Data Warehouse, Stream Processing, Event Processing, TIBCO, LogLogic, TIBCO Unity, Splunk, IBM, QRadar, Papertrail, Loggly, fluentd, sumologic, ELK Stack, Logstash, Elasticsearch, Kibana, Graylog, AppDynamics, New Relic