by Markus Breuer | Aug 5, 2020 | Big Data
Regular Expressions are a powerful tool to split texts into fragments. Furthermore, Apache Spark is an analytics engine and capable of processing large amounts of data sets. The feature of naming capturing groups makes the usage of regular expressions more accessible....
by Markus Breuer | Dec 15, 2019 | Big Data
Openshift offers many possibilities to embed files in pods. Furthermore, there are many reasons to include files in pods. So, embedding configuration files is a powerful mechanism. In this way, unchangeable containers become populated with dynamic content. In brief,...
by Markus Breuer | Nov 19, 2019 | Big Data
Openshift templates are Openshift’s answer to Kubernetes helm charts. In this way, an openshift template contains a list of objects. In consequence, applying an openshift template substitutes its placeholders. Also, it contains a parameter list. Openshift...
by Markus Breuer | Aug 31, 2019 | Big Data
Jenkins supports using docker container engine. As result, Jenkins pipelines are going towards server less builds. Using the built-in docker plugin in pipelines is pretty simple. In that way, pipeline performs native calls to docker. And in consequence, docker is...
by Markus Breuer | Aug 7, 2019 | Big Data
The term of service mesh is on every ones lips. Many people consider it synonymous with istio. But that is not correct at all. Of course, istio implements a service mesh. Independant from istio there exist different solutions. But what is a service mesh architecture?...
by Markus Breuer | Jul 14, 2019 | Big Data
GIT is a famous and powerful SCM for professionals. Behind the scenes it is a simple key value store. This article covers, how GIT uses key value store concepts. All high level operation rely on this basic. In this way, if you know how git uses key value store...
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