This is a stellar breakdown of Redis in action clear, pragmatic, and rooted in real-world scale. The IPL use case hits home: caching hot data with TTLs that match user expectations is one of the simplest yet most effective ways to protect your DB and deliver snappy UX. The Pub/Sub pattern is especially elegant here. Too often, teams reach for heavyweight brokers when Redis can handle real-time fanout with minimal latency and operational overhead. And BullMQ for background jobs? That’s the kind of architectural clarity that keeps APIs responsive under pressure. Appreciate the emphasis on best practices especially hit ratio monitoring and failover planning. Redis may be simple, but scaling it well takes intention. Posts like this help bridge the gap between “it works” and “it works reliably at scale.”