Processing 14 GB files with Rust — Azure Stacks

Processing 14 GB files with Rust — Azure Stacks

We leverage the local docker for development and testing; however, to complete the entire SDLC, we still need to build a CI/CD pipeline.

We leverage the local docker for development and testing; however, to complete the entire SDLC, we still need to build a CI/CD pipeline. If you just land to this article and the links below can help you get more context of this series of weekend codes & write.

For part 3, we will focus on:

  1. Move data to Azure ADLS gen2 blob storage.
  2. Add a new code read & process the data from blob storage.
  3. Azure Pipeline build and ship the code.
  4. Create an AKS cluster and deploy it to production.

The reason I’m using Azure Stacks here, I have used both GKE and EKS in production job/application before, so I decided to use Azure Stacks here. As I have mentioned in part 2.

Doing it, it's much better than just read the comparison articles.

High-level Workflow

1. Create resource-group

2. Move data to ADLS gen2 via azcopy

3. Add new code to handle & process the file from Azure ADLS gen2

4. Create an Azure Container Register

5. Create an Azure pipeline

6. Create an AKS

7. kubectl apply secret and app deployment.

azure-kubernetes-service azure-pipelines azure azure-container-registry rust

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