Why even do this?
Recently, I had an opportunity to help one of my clients with an interesting problem.
They had built an entire data lake and analytics solution on a public cloud platform for a specific region and wanted to deploy this solution to another area. The division responsible for managing the solution desired the solution implemented on a different public cloud platform.
The solution was built on the feature-rich services provided by the public cloud provider and to implement this solution on a different cloud platform would need a lot of re-work. My clients found themselves tied with the golden handcuffs.
This particular case may be a unique situation and might apply to big corporations, but a growing number of organizations now seek flexibility to implement their solutions on any of the widely available public/private cloud platforms. After all, one of the big promises made by the cloud was the flexibility of implementing solutions, so now how could it take that away.
What is the solution?
In recent years, Kubernetes has emerged as a gold-standard of implementing cloud-native yet cloud-agnostic solutions. Some of the benefits that stood out for me were:
- Solutions built on Kubernetes can use industry-standard patterns and tools. These applications are portable, ready to be deployed on any platform (public or private).
- It also is usually cheaper than using out-of-the-box services provided by cloud providers.
- As the applications become more complex and intricate, Kubernetes give more control in the hands of the dev teams, enabling them to build with ease.
- With a large number of software distributions available as docker images and helm charts, it is easy to configure them according to your needs.
The flip side is that the solutions built on Kubernetes need a lot more effort to support and manage.
Alright, now that we have laid the foundation, let us take a look at the high-level design of the proposed solution
#cloud-native #cloud-computing #kubernetes #data-lake #analytics #data analysis