Data Systems Architecture — Past, Present and Future

Data Systems Architecture (Past and Present)
  1. Config, state, and metrics management are more complex, and there are tools purposefully built to address these problems.
  2. You want to minimize the overall footprint of your application to be as small as possible.
  3. As Murphy’s law states, if anything can go wrong, it will. You want to avoid correlated failures.
Computational Storage Architecture
  1. Think and design service as a function scope (small and very specific) which can be deployed in millions of storage nodes.
  2. Consider cross-platform application stack. .NET Core , Java, etc.
  3. Consider serverless architecture, chances are the cloud providers will eventually transition to computational storage.
  4. Unikernels is another exciting area which is gaining lots of traction recently. (Unikernels deserves a separate post by itself which I hoping to cover in the future blog posts).

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Cloud and Distributed Computing Enthusiast with 13+ years of experience; Works @ Microsoft; Opinions are my own and not the views of my employer.

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Karthik Mahalingam

Karthik Mahalingam

Cloud and Distributed Computing Enthusiast with 13+ years of experience; Works @ Microsoft; Opinions are my own and not the views of my employer.

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