Application Migration

Migrate and Re-Architect Machine Learning Applications on Google Cloud Platform

A UK media services company with a focus on interactive planning and purchasing required a solution to migrate Machine Learning applications deployed on ShinyServer from Azure to Google Cloud Platform and re-architect the applications to reduce code redundancy, introduce scalability and enhance performance.

Client Challenges and Requirements

  • Need for modern infrastructure to cater high availability and scalability requirements
  • Code redundancy as same code base was coped for multiple clients which resulted in increased Go-to-Market time
  • Certain operations were performance intensive resulting in increase page load time
  • Manual deployment process

Bitwise Solution

Bitwise implementation resulted in migration of the application with the re-architected applications. Implementation included:
test (4)

Data migration from SQLite and Azure VM local storage to Google Cloud Platform

code (1)

Redesign of the Shiny application to have single version of the code bae to reduce maintenance overheads and increase Go-to-Market time

feature (1)

Role based access control

framework

Build a platform for application testing – functional and performance and interactive debugging

synchronize (1)

DevOps Implementation

Group 3

GCP infrastructure setup and optimization considering - security, scalability, performance and cost optimization

Tools & Technologies We Used

GCP

Azure

CloudSQL

R, ShinyServer

Kubernetes / GKE

ISTIO, NGINX

Docker

OAuth

Key Results
Group 3

Kubernetes cluster setup for scalability and High Availability

code (1)

Acceleration of Business Flows

test (4)

DevOps Implementation

Group 3

Foundation for Enterprise Platform

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