Parallel Porting — Cloud Migration

The problem

Vodafone's porting workflow had to verify feasibility against multiple downstream systems before accepting a request. The legacy stack didn't scale gracefully under bursty load, and releases were risky and slow.

Approach

• 01Decomposed validation logic into event-driven microservices using AWS Lambda, SQS, DynamoDB, and S3 for serverless, cost-aware scale.
• 02Codified all infrastructure with AWS CloudFormation; container workloads moved to ECS for predictable scaling under bursty porting traffic.
• 03Wired CI/CD on Azure DevOps with zero-downtime deployments and fully automated release cycles.
• 04Stress-tested the platform with Locust (Python) load suites to validate stability at high concurrency before each major rollout.
• 05Hardened the supply chain with SonarQube and WhiteSource Renovate scans across releases.

Outcome

• Validation workflows simplified and processing efficiency improved.
• Zero-downtime releases via automated pipelines, with reproducible environments.
• Sustained high-concurrency load proven through repeatable Locust simulations.

Stack

• Java
• AWS Lambda
• AWS SQS · DynamoDB · S3
• AWS ECS
• AWS CloudFormation
• Azure DevOps
• Locust
• SonarQube · WhiteSource