The growth of companies puts increasing amounts of data and traffic on their systems, which can lead to slower response times, downtime, and server crashes. To ease this strain, companies need strategies in place to handle large datasets, user requests, and traffic spikes. Improving application performance is crucial for delivering better user experiences and unlocking more responsive, real-time experiences. A cloud data platform with features such as all-in-one caching, low latency, high read/write availability, and the ability to process large datasets in real time can help. Hyperscaling data architectures using a cloud data platform can also improve speeds and app performance. Dynamic caching reduces load on primary databases by storing frequently requested data closer to the app, while in-memory caching speeds up data processing by keeping "hot" data in RAM for fast access. Redis is designed for caching at scale and provides enterprise-grade functionality, integrations, and cost savings. By using a new approach like Redis Flex, which balances DRAM and SSDs for hot data, caching can be faster and cheaper than other approaches. A modern caching strategy simplifies app codebase by serving the right data to the right user at the right time, reducing manual labor and saving time. The Redis Query Engine handles high query volumes and delivers data quickly even under heavy traffic loads, while dumb data stores only let you retrieve data using exact keys or names. AI-powered coding assistants like Redis Copilot can speed up development by helping engineers write code faster. Improving app performance is an ongoing process that requires considering the application environment and leveraging solutions such as AWS Lambda and Amazon SageMaker to support modern, high-performing apps.