Building a Robust API for Datalogics: A Developer's Experience with Automation and Data-Driven Decision Making

Last updated May 20, 2024

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As a developer at Datalogics, I was tasked with taking their existing command-line applications and transforming them into a SaaS-based product, the first phase of this project involved building an API that would allow users to access and leverage the company's powerful in-house tools to process files.

To accomplish this, I utilized various technologies such as Node.js for the source code, Python and shell scripts once it was deployed to AWS within the EC2s and Lambda functions, and Jenkins for testing. One of the critical things I learned during this process was the importance of automation when scaling an application, as the API began to grow in popularity and usage, it became clear that automating certain processes were crucial to maintaining efficiency and reliability.

Another important lesson I learned was the value of collecting data to inform project prioritization, by gathering and analyzing usage data, I identified areas of the API that were most in demand and prioritized development efforts accordingly, this helped us to focus our time and resources on the features and functionality that would have the largest impact on our users.

Overall, building the API for Datalogics was a challenging but incredibly rewarding experience, I learned a great deal about the importance of automation and data-driven decision-making in the development process. I am excited to continue applying these lessons as I tackle future projects.