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Serverless Cloud Deployment Decreases Message Transformation Complexity and Cost Using AWS Lambda

Customer Scenario

Logistics companies pass messages between partners and customers, potentially millions of times a day. This makes a licensed iPaaS platform very useful, but it can be costly to own and scale. The transformation of messages needs to be handled seamlessly since the target systems our client interacts with are highly varied across their client and partner ecosystem. What is a well-formed message for one system is unsuitable for another. Additionally, the volume of logistics-related events processed, such as shipment tenders, is significant, and the messages themselves are business-critical so that freight can be shipped in a timely manner across the world.

Solution Approach

Big Compass leveraged AWS Lambda as the environment for the microservices. By using a serverless compute solution, the transformations are executed at scale and at a substantially lower cost than using an always-on iPaaS platform. The transformations are created using a configuration-based approach, allowing the Lambda function to dynamically pull in transformation configurations which reduces dependency on code and eliminates deployments for new or updated transformations. DynamoDB, SQS, and S3 were used to persist data, allowing transformation executions to be replayed later if needed.


With millions of messages processed per day, the fact that the customer has seen no unhandled errors since the deployment of the solution alone would be impressive. But in addition to the reliability benefits, the new solution also provided the ability to add new transformation without coding or deployments, while the combination of on-demand compute savings with the serverless architecture, increased reliability, and limited developer intervention has resulted in a cost reduction of 25% and an increase in integration productivity of 30%.

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