This is a contribution for the Redis AI Challenge Beyond the Cache.
What I built: a Tenant Management System, a practical intranet application for keeping track of tenants in an apartment complex. The application allows the community manager to quickly search for tenants and check their status. It is a production app with real users. For this challenge, I refactored the backend originally based on MongoDB and migrated it to Redis Cloud as the main database. I also updated parts of the code to better leverage Redis capabilities.
Application flow: the administrator logs in on the sign-in page and generates a token to create operators. The operator uses that token to register on the sign-up page and access the application. When the operator wants to work, they only need to log in with their username and password. The operator can add tenant data, update it, search by name or by tower and unit, and delete records. The administrator does not perform these operations directly. To log out, simply refresh the browser and return to the sign-in page.
Demo and resources: Live App https://appsrwredis.vercel.app/; Frontend GitHub https://github.com/hendram/appsrwredis; Backend GitHub https://github.com/hendram/appsrwbackredis; Video demo https://youtu.be/1EOcjdAILKM; Grafana Dashboard https://hendramulyanto.grafana.net/public-dashboards/96264835006547138bb3e458282704a0?from=2025-08-06T03:06:36.007Z&to=2025-08-06T03:52:16.348Z&timezone=browser. Default credentials for testing: administrator user admin password 123456. Test operator user aa password 123456.
Test data used: list of operator names https://github.com/hendram/appsrwbackredis/blob/master/operator-name-list.txt; list of resident names https://github.com/hendram/appsrwbackredis/blob/master/residents-name-list.txt; timeseries log for name searches https://github.com/hendram/appsrwbackredis/blob/master/timeseries-log-namesearch.txt; timeseries log for tower and unit searches https://github.com/hendram/appsrwbackredis/blob/master/timeseries-log-towerunitsearch.txt.
How I used Redis Cloud: in this project, Redis Cloud is the main database, not a simple cache. It is used for real-time storage, queries, and monitoring. Features used: RedisJSON to store each tenant's structure with fields such as name, tower, unit, and status; RediSearch for fast full-text searches on fields such as name and towerunit, enabling efficient searches even with data growth; RedisTimeSeries to record how many records each search query returns per operator, feeding time series that show activity over time; integration with Grafana Cloud using the Redis Data Source plugin to build live dashboards that query RedisTimeSeries and show search volumes, most active operators, and usage patterns. Redis Cloud as a managed platform simplifies deployment and includes modules such as RedisJSON and RediSearch ready to use, which allowed replacing the MongoDB-based backend entirely.
Results and observability: this approach demonstrates that Redis Cloud can be a complete backend for real-time applications, supporting not only storage and search but also advanced observability when combined with Grafana. Recording search behavior by operator helps understand usage patterns and improve the experience of operational users.
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Conclusion: the migration from MongoDB to Redis Cloud improved latency, offered faster searches with RediSearch, stored structured data with RedisJSON, and monitored real-time activity with RedisTimeSeries and Grafana. This architecture demonstrates how Redis can be the foundation of a robust and scalable tenant management system, and how companies like Q2BSTUDIO can support the design and implementation of custom software solutions that integrate artificial intelligence, cybersecurity, and cloud services.
