The punch is deployed in production for small, medium or large-scale applications, on the cloud or on premise, for various use cases such as cybersecurity, applicative or system monitoring. In this short blog we highlight a few concrete sizing example Read more…
Before diving into leveraging OmniSci, let us quickly recap the well-known database story. Relational databases have long been the standard for storing pre-processed data. Although they cannot keep up with today’s applications requirements in terms of raw performance and volumetry, Read more…
Craig 5.2.1 Release We are happy to share the latest development, new features and stories coming together with the craig.5.2.1 release. First of all the craig 5.2.1 leverages Elastic 6.5, Kibana 6.5, Spark 2.4 and Storm 1.1.3 releases. As you can guess, Read more…
Replay available: Related posts: – PySpark to PML
In the punch, we do not use logstash for high-performance logs parsing. Why is that? Mainly because logstash is nor easily scalable nor does it provide an end-to-end acknowledgment pattern. This is a serious lack because we cannot afford to lose logs whatever Read more…
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To process and analyze data for typical analytics or machine learning use cases, it is common to hit storage and processing power issues. If the dataset is too big to be stored on your laptop drive, if it cannot be Read more…
