In today's distributed systems, many database systems were developed with a single database serving the entire enterprise, whereas Redis evolved differently, designed to store active data that will change often, with an indefinite structure and minimal resources required for massive throughput. A microservices architecture is characterized by individual services designed to fit specific use cases, each concerning themselves only with input/output and private data, allowing Redis databases to back a wide range of different microservices. Each service must perform as fast as possible due to inter-service communication overhead, making state maintenance crucial and isolating service data from other data layers for uncoupled scaling and cross-service contention. Services are designed to fill single roles in business processes, with non-relational state well-suited to NoSQL data models like Redis. Once built, services communicate through private HTTP endpoints or log-like structures, such as Redis Streams, allowing for asynchronous event announcements and bidirectional communication. Even without using Redis for storage or communication, it can play a vital role by caching frequently accessed data, preventing unneeded API calls from impacting performance.