Problem statement In the previous post, « How we migrated applications from Heroku to AWS » I described the migration
C2i Genomics empowers physicians, patients, and researchers with ultra-sensitive, personalized whole-genome cancer detection. C2i Genomics’ SaaS solution utilizes a cloud-based
C2i Genomics empowers physicians, patients, and researchers with ultra-sensitive, personalized whole-genome cancer detection. C2i Genomics’ SaaS solution utilizes a cloud-based
C2i Genomics empowers physicians, patients, and researchers with ultra-sensitive, personalized whole-genome cancer detection. C2i Genomics’ SaaS solution utilizes a cloud-based
by Nir Shney-dor and Oleksii Davydov There are many ways you can embark on your machine learning journey using AWS
Problem statement Our customer uses Customizations for AWS Control Tower for the account vending. A new account in the specific
Inputs and requirements Our customer had a production-running application in Heroku, consisting of several containerized Web applications and APIs (dynos),
Problem statement Our customer has an environment split between cloud providers, partially due to isolation and partially due to other
WorkSpaces Web is a low-cost, fully managed Linux-based service that provides a secure browser-based platform for accessing internal and external