In this article, Jonas Braun reports on the most common way to use Kubernetes: with cloud providers like Google GCP, Amazon AWS or Microsoft Azure. In the article, he looks at how to deploy these containers (i.e. applications or models) reliably and scalably for customers, other applications, internal services or computations with Kubernetes. Finally, the article gives an outlook on tools and further developments.
In order for companies to continue to be successful in a digital, software and data-driven age, the necessary technical prerequisites must be established. The use of cloud technology is seen as an important element in this process.
In this whitepaper we provide an overview of the range of services offered by the three largest providers for cloud computing, AWS, Azure and GCP.
This article presents five technologies that every data engineer should know and master for his daily work. Spark as a data processing tool in the big data environment, Kafka as a streaming platform, Airflow, and serverless architecture for coordination and orchestration are presented. Before that, the importance and role of SQL (Structured Query Language) and relational databases will be discussed.
In this blog post, Andre explains two approaches on how to secure a REST API: One works with nginx and the sub-request feature, the other implements the verification part in the API itself.