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Satellite Data Migration & Image Processing on Public Cloud

Cloud hosted solution provided a 200,000:1 price-performance advantage


  • Migrate 50 years of satellite image data & processing to a cloud native solution at a public cloud service provider
  • Cloud expertise and experience modernizing, refactoring very large on-premise solution stack to a cloud native alternative
  • Training and hands-on experience working in deep cloud native environments
  • Database modernization and refactoring into distributed data model
  • Containerization of legacy C code processing kernels


  • Fully public cloud hosted solution that processes Landsat data from raw radio signals to finished TIFF images made available worldwide
  • Migrated image processing/rendering software to a Docker containers & refactored code for standard, uniform, libraries, RPMs & build options
  • Migrated 11+ million scene & data artifacts from on-premise to cloud based data lake
  • Processed 117,000 scenes from satellite systems from raw data to finished images on cloud native solution
  • Demonstrated same code containers running both as cloud native instances & at on an on-site container cluster
  • Migrated & refactored 80TB OLTP database from on-premise instance to a combination of a data lake, NoSQL, SQLite, data warehouse & OLTP
  • Cloud native CI/CD pipeline for all build, test & deployment tasks

Tools & Technologies

AWS Batch Lambda, ElastiCache, CloudTrail, Cloudwatch, ECS, Amazon S3, Redshift, Amazon SQS & SNS, Anthena, DynamoDB, Oracle, Ansible, Github, Jenkins, Docker

Key benefits

  • Improved image processing performance by 100x than on-premise
  • Made image processing 2,000X cheaper in the cloud than on-premise – $100.00/scene on-premise vs $0.05/scene in the cloud
  • Cloud hosted solution provided a 200,000:1 price-performance advantage over doing the same work on premise
Case Study KeyPoints