The State Changers had an insightful meeting that revolved around optimizing performance, improving user experience, and handling large data with specific reference to caching strategies using different tools. A significant portion of the meeting was devoted to how platforms such as "Xano" can be used for these purposes. An in-depth discussion took place about different levels of dealing with large data and ways to enhance performance.
1. Data Storing Locally: The first option discussed focused on storing data locally on the frontend to provide immediate user experience. Persistent storage was recommended, especially for data that doesn't change frequently. 2. Grouped Information: The second option involved amalgamating more information into a single network transaction, thereby reducing the number of round trips and improving performance to a degree. 3. Utilizing Xano: Xano featured heavily, with solutions including using caching functionality to speed up repeat transactions. They mentioned the Time To Live (TTL) measurement, which could speed up retrieval by serving cached answers where input and user remain unchanged within a predetermined timeframe. 4. Using Redis for Background Tasks: It was discussed that advanced caching could be implemented in function stacks via background tasks but would offer less flexibility than on-demand solutions. Redis was given as an example due to its speed and ability for off-cycle information collection and delivery. These considerations were deemed important for those working in a no-code/low-code environment and led to discussions on balancing performance considerations with swift development turnarounds. The session concluded agreeing that a retrospective approach to finding and addressing bottlenecks is likely to bring about the most substantial improvements.
(Source: Office Hours 3/3 )
