In Chapter 6, Solution Architecture Design Patterns, you learned about various design patterns, including microservice, event-driven, cached-based, and stateless. An organization may choose a combination of these design patterns depending on their solution's design needs. You can have multiple approaches to architecture design depending on your workload. Once you finalize your strategy and start solution implementation, the next step is to optimize your application. To optimize your application, you need to collect data by performing load testing and defining benchmarking as per your application's performance requirements.

Performance optimization is a continuous improvement process, one in which you need to take cognizance of optimal resource utilization from the beginning of solution design to after the application's launch. You need to choose the right resources as per the workload or tweak the application and infrastructure configuration—for example, you may want to select a NoSQL database to store the session state for your application and store transactions in the relational database.

For analytics and reporting purposes, you can offload your production database by loading data from the application database to data warehousing solutions and create reports from there. In the case of servers, you may want to choose a virtual machine or containers. You can take an entirely serverless approach to build and deploy your application code. Regardless of your approach and application workload, you need to choose the primary resource type, which includes computing, storage, database, and network. Let's look at more details on how to select these resources type for performance optimization.