This series of best practices for performance is suitable for anyone, regardless of whether you are a beginner or an experienced MongoDB developer. The series will cover practical advice that can be applied to various scenarios, including using fully managed cloud database services or self-managing MongoDB. The series will start by discussing two key factors: pattern design and the key resources to consider. It will then delve into data modeling, which is crucial for performance optimization. Data modeling involves understanding application query patterns, designing a data model that corresponds to these patterns, and adjusting data models to optimize queries, insert, and update operations. The series will also cover how to apply data modeling best practices in MongoDB, including using JSON documents, arrays, subdocuments, and referencing other collections. It will discuss the key considerations when designing a data model, such as embedding versus referencing, and provide resources for further learning. Finally, it will cover how to review and refine a data model using tools like MongoDB Compass and how to optimize the work set size by adjusting RAM size.