Resperate

Report Generation: One of the primary challenges we faced was generating reports from multiple HTML pages and converting them into PDF format. To accomplish this, we utilized Puppeteer, a Node.js library that leverages Chromium to scan a page and convert it into PDF. Memory and Timezone Issues: We encountered memory limitations in Firebase, the platform we were using for the project. As Puppeteer is a heavy package that requires nearly 2 GB of memory, we had to increase the memory limit for a particular function to address this issue. We also had to account for timezone differences between the GMT timezone used by Firebase and the local timezone of the user. To tackle this, we stored the user's local timezone in the database to calculate the local time accurately.

The Approach: We took a clear approach to building the system, creating a flowchart on Twilio's end for all incoming and outgoing messages. We also created different schedulers in the system to ensure that users received messages at the appropriate times. The Solution: As the technology partner for this project, we developed a range of solutions, including: A system for users to choose their preferred time to receive scheduler messages A gift card option that allows users to gift the device to others A custom report page to render BMP and Therapeutic values in the form of charts A custom QA tool to test the full week of messages in just a few minutes

The Results: Through our work on this project, we were able to achieve the following results: Reduced build time by 30% by automating infrastructure provisioning Reduced message latency by 70-80% and improved overall performance Effectively managed multiple scheduler fluctuations Released new application features faster, meeting customer expectations and improving user experience.