THE CUSTOMER
AlfaSage is an online video startup based in Cambridge, United Kingdom. Their products 20Hz and nGage help music and video publishers get the most from their content. 20Hz is a service for managing the content, while nGage is the engine that helps monetize content.
THE BRIEF
As a startup, AlfaSage needed to work flexibly and cost-effectively and provide solutions to their clients without sacrificing security. With a tighter budget than established competitors, their small team still needed to support multiple application versions to simultaneously explore various new customer-driven feature requests.
THE REQUIREMENTS
- Extensive AWS (Amazon Web Services) architectural knowledge
- DevOps best practices to enable fast development
- Consulting skills to fully understand the solution
"We chose Green Custard because of their in-depth knowledge of the technologies and understanding of what we are trying to achieve. They provided us with Cloud DevOps capability and as a result, we have been able to create and control multiple different environments covering the full development life-cycle."
Ian "Jamie" Jamieson,
CTO at AlfaSage Limited
THE SOLUTION
Amazon Elastic Container Service and AWS CloudFormation offer a unique combination of flexibility and automation. In addition, AWS provides many other services that enable a small development team to focus on customers and explore new features in parallel.
After examining AlfaSage's current application, we configured a micro-service architecture using Amazon Elastic Container Service and Docker backed up with AWS CloudFormation and AWS CodeBuild for faster and easier deployments. Leveraging Amazon Elastic Container Registry tags and git, the deployment system supports multiple environments and versions seamlessly in London region.
AlfaSage is now able to control the full development lifecycle easily. Using these technologies they are able to trial new features in a secure way on clones of the production environment and with full isolation across different customer deployments. After a new feature has been successfully trialled, it can be deployed easily and quickly using the automated deployment pipeline tailored to their Git workflow.
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