How BluePi helped India's Leading AD-Tech Company Migrate to AWS

Customer

AD Company

Location

India

Segment

Media

Solution

Migration

Customer Profile

The client is a subsidiary of a major Media Group that was established in 2006. A front-runner in technology and innovation in the digital performance advertising space and headquartered in New Delhi; the company is a leading Global Mobile AdTech Platform that boasts of:

  • 120M+ visitors
  • Published Partners 10K+
  • 30K+ leads on mobile
  • 5M+ app installs

Objective

The company was hosting its high traffic ad serving platform on a third-party data center out of the US. Due to steady growth in business and traffic, the current platform appeared rigid, and difficult to manage. The platform itself was built on a modern NoSQL store and a sophisticated technology stack, however, the underlying platform was prohibiting the full use of the platform.

Problem Statement

  • No Downtime:- Possibility of bringing down site was not there due to high traffic. Migration was done without bringing site down.
  • Parallel Runs:- In order to maintain the atomicity, data was sent in parallel to legacy and AWS servers.
  • Huge Dataset:- Data of volume close to 1 TB was migrated during the project.
  • Complex Stack:- Application stack included MongoDB/MySQL.

BluePi’s Solution

Migration is not always a simple task. One needs to make a detailed plan – including a roll-back plan if things don’t work as intended. It is, therefore, imperative that BluePi spends a good amount of time upfront to understand the current Infrastructure thoroughly before provisioning on AWS, doing a Performance run and migrating all the data eventually. And that’s how it panned out even in this case. And, it doesn’t end there – BluePi then went on to Optimize queries and runtime before going ahead with Automated Deployments using DevOps.

Value Added

  • 1000 concurrent user requests at time of switch-over
  • Cost Saving by reducing the servers.
  • Simplified infrastructure.

AWS Service used

AWS, MongoDB, EC2, RDS, Apache, ELB, Redis, Gearman

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