My group is building a full-stack data pipeline for creating, testing, and deploying trading strategies for the company, Levrum. The goal is to deliver a web application that will assess/utilize these trading algorithms with the intent of showing their people that algorithm-assisted investing could be a more successful/ lower risk approach.
A favorite technology that we are utilizing for our project is AWS Cloud Services. We are mainly using AWS Elastic Beanstalk and AWS Lambda. AWS Elastic Beanstalk is the heart of our application and without it we wouldn’t be able to host it onto the web. it is a platform that simplifies deployment and management of our web application and services. It gives us the ease of being able to deploy our application without having to worry about the fundamental infrastructure. The reasons for choosing to use AWS Cloud Services instead of others are easy deployment, database integration, and good documentation. Elastic Beanstalk made it easy to set up and connect our application to a non-relational database, MongoDB. AWS Cloud Services also provides well-written documentation that made integrating our application onto the cloud seamless. AWS Lambda is a serverless compute service that allows us to run a portion of our code where it involves high computation due to the amount of data that is being utilize/calculated. It allows us to run code in parallel to handle to amount of data being computed. Even though AWS Elastic Beanstalk had well-written documentation, it took some time to get everything set up and running. Reducing the learning curve even further for beginners would be a way to improve the service by providing more extensive documentation and even more user friendly interface. As AWS Lambda is a serverless application, troubleshooting code could be rather difficult. Providing more debugging tools would make easier for the developers to debug their problems.
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