If you’re building a Node.js application with Mongoose, you’ve probably felt
the pain of database performance at scale. The go-to solution? Add
Redis. Set up a caching layer,
wire it into your queries, and hope the invalidation logic doesn’t become a
maintenance nightmare.
But what if we told you there’s a simpler way – one that
uses the database you already have, requires zero additional
infrastructure, and handles cache invalidation automatically?
Meet
@sitelintpackages/mongoose-cache: a MongoDB-based caching solution for Mongoose queries with TTL and
automatic invalidation support.
Sometimes the database might work slowly and one of the reasons is a large log file. Tracking database activity is crucial for performance and issues monitoring. However, the log file may grow and therefore may cause the performance issue because of more and more writing and reading on a larger and larger log file. We may avoid such problems by scheduling regular log rotation and keeping the log file size below a defined threshold. Let’s get started on figuring out how to address this issue.
