Introduction: In the modern era of data-driven decision-making, organizations are constantly seeking innovative solutions to harness the power of big data. One such solution is the deployment of Hadoop/HDFS and Spark on Kubernetes—a strategic endeavor that requires careful planning and execution. In this blog post, I will explore the process of deploying these technologies on Kubernetes, unlocking new possibilities for data management and analysis. This is the same solution that we used when we started to build our no code/low code data pipeline and visualization platform DataSetu. For Datasetu we needed to create a Data lake for processing huge dataset with high performance. This how we went about it, Chapter 1: Setting the Foundation with Kubernetes Before embarking on our journey to the data lake, it's essential to establish a solid foundation. Kubernetes serves as the cornerstone of our infrastructure, providing the orchestration and scalability needed to manage our distributed
A mixed bag of suggestions on various technical aspects.