Amazon's Dynamo serves as a foundational real-world example of a distributed key-value store whose architecture parallels the parameter synchronization mechanisms used in deep learning. Because neural networks have many different layers, their respective sets of gradients must be indexed using a key $i$. This indexing strategy intentionally mirrors systems like Dynamo, which also utilize key-based structures to efficiently distribute and manage parameters across multiple servers.