Log Analytics and Operational Intelligence for Distributed Microservices.
IT systems and applications generate more and more distributed 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 distributed Microservices and Cloud architectures, custom application monitoring and debugging, network and server monitoring / troubleshooting, security analysis, compliance standards, and others.
This session discusses how to solve the challenges of monitoring and analyzing Terabytes and more of different distributed machine data to leverage the “digital business”. The main part of the session compares different open source frameworks and SaaS cloud solutions for Log Management and operational intelligence, such as Graylog , the “ELK stack”, Papertrail, Splunk or TIBCO LogLogic Unity). A live demo will demonstrate how to monitor and analyze distributed Microservices and sensor data from the “Internet of Things”.
The session also explains the distinction of the discussed solutions to other big data components such as Apache Hadoop, Data Warehouse or Machine Learning, and how they can complement each other in a big data architecture.
The session concludes with an outlook to the new, advanced concept of IT Operations Analytics (ITOA).
Presented at O'Reilly Software Architecture Conference in London UK 2016. #OreillySACon.
Keywords:
Log analytics, , Operational Intelligence, big data, machine data, IoT, Internet of Things, microservices, log management, SIEM, SOA, ITOA, analytics, Hadoop, spark, apache, open source ,TIBCO, LogLogic, Splunk, IBM, QRadar, Greylog, ELK Stack, ELK, Elasticsearch, Logstash, Kibana, Loggly, Papertrail, sumologic, event processing, streaming analytics, data discovery, visual analytics, data warehouse, live datamart, StreamBase, Apama, Infosphere, Oracle, Microsoft Azure, Amazon AWS