Summary

In this chapter, we discussed various virtualization platforms. First, we briefly covered the architectures of the virtualization, containerization, and container orchestration frameworks. Then, we deployed VMs, Docker containers, and Kubernetes containers and ran an application on top of them. In doing so, we learned how to configure Dockerfiles and Kubernetes deployment scripts. After that, we discussed the Hadoop architecture and the various Hadoop distributions that are available on the market. Then, we briefly discussed cloud computing and its basic concepts. Finally, we covered the decisions that every data architect has to make: containers or VMs? Do I need big data processing? Cloud or on-premise? If the cloud, which cloud?

With that, we have a good understanding of some of the basic concepts and nuances of data architecting, including the basic concepts, databases, data storage, and the various platforms these solutions run on in production. In the next chapter...