Gigantic amounts of data are being generated at high speeds by a variety of sources such as mobile devices, social media, machine logs, and multiple sensors surrounding us. All around the world, we produce vast amount of data and the volume of generated data is growing exponentially at a unprecedented rate. The pace of data generation is even being accelerated by the growth of new technologies and paradigms such as Internet of Things (IoT).
Where we left off: AWS had taken the Elasticsearch software and launched their own cloud offering in 2015, and Elastic N.V. had doubled down on an “open core strategy.” Once AWS decides to offer a project like Elasticsearch, it immediately becomes a truly formidable competitor to anyone trying to do the same, even the company behind the software itself. AWS has huge scale, operational expertise, and various network effects that really compound.
Logging your Java applications is essential to getting visibility into application performance and troubleshooting problems. But, with a variety of available libraries and configuration options, getting started logging in Java can be challenging.
As shown in Elasticsearch Key Metrics, the setup, tuning, and operations of Elasticsearch require deep insights into the performance metrics such as index rate, query rate, query latency, merge times, and many more. Sematext provides an excellent alternative to other Elasticsearch monitoring tools.
