IT applications and microservices generate terabytes of distributed log data from mobile devices, the Internet of Things, social networks, and other emerging technologies. Organizations struggle to monitor and manage their IT systems and technology infrastructure with distributed microservices and cloud architectures, custom application monitoring and debugging, network and server monitoring and troubleshooting, security analysis, and compliance standards.
Kai Wähner discusses how to solve the challenges of monitoring and analyzing terabytes of different distributed machine data to leverage the digital business. Kai compares open source frameworks and SaaS cloud solutions for operational intelligence and log analytics, such as Graylog, the ELK stack, Papertrail, Splunk, and TIBCO LogLogic Unity, explains how these differ from big data stores such as Hadoop, and offers a live demo demonstrating how to analyze distributed microservices before concluding with view of the new concept IT operations analytics (ITOA).
Kai Wähner is a technology evangelist at Confluent. Kai’s areas of expertise include big data analytics, machine learning, deep learning, messaging, integration, microservices, the internet of things, stream processing, and blockchain. He’s regular speaker at international conferences such as JavaOne, O’Reilly Software Architecture, and ApacheCon and has written a number of articles for professional journals. Kai also shares his experiences with new technologies on his blog.
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