AWS Cloud Migration of IOT based ship tracking platform
A leading provider of global maritime vessel tracking services wanted to migrate their vessel tracking system to AWS. Their existing vessel tracking system processed more than 500 million IOT messages per day. They wanted to modernize and migrate their platform to AWS and handle 3x workload. DataGrokr helped migrate their platform to AWS, rearchitected the solution, rewrote the data ingestion pipelines and designed a new IOT device registration framework using latest AWS IOT Core services to help them achieve their objectives.
About the Client
The client is a leading provider of global maritime vessel tracking services. Their flagship product is used by many organizations to track the location of cargo ships and to detect congestion in shipping lanes.
Client’s need and Problem statement
Client’s existing solution had several single points of failure and their legacy infrastructure was flagged for potential security concerns. The system had reached limits of vertical scaling. The management of IOT devices was piecemeal and had several operational challenges. All of these factors let them to the decision to migrate to the cloud and they were looking for a reliable engineering partner who can help them with the cloud migration.
Tech Stack
Our solution and outcomes
- We designed, developed and deployed a cloud native solution based on AWS Well Architected framework focusing specifically on reliability and security. The new solution can handle ~1.5 billion messages per day (3x original throughput) and application availability of 99.9%
- Rewrote the data transfers from the receivers (IOT devices) to server and the data ingestion pipelines by making use of AWS services such as Kinesis, ECS and Glue.
- Implemented processes for device enrolment and management with AWS IoT Core using MQTT protocols with mTLS
- Increased throughput of data ingestion and removed single points of failure by migrating to serverless architecture
- Improved data posture with encryption of data at rest and in motion