Neo4j can be used as an embedded library within your Java application, or it can be run in a separate server process. The server version is more common and provides a richer set of APIs for interacting with the graph database. The server can also be extended using unmanaged extensions to add custom functionality. When deploying Neo4j to production, it's essential to consider hardware and software requirements, such as choosing machines with multiple cores, sufficient RAM, and specialized SSDs. A good configuration includes assigning a significant amount of RAM to the page cache and configuring the garbage collector for optimal performance. Neo4j supports clustering for high availability and high read throughput, which involves configuring instances in a cluster to work together seamlessly. Clustering can be configured using HA endpoints, load balancers, and caching strategies like cache sharding. Backups are crucial for data protection, and Neo4j provides online backup capabilities that allow for non-disruptive backups of running instances. Monitoring the production environment is also vital, and Neo4j exposes various metrics and counters to help with this task. Testing at scale is essential before deploying an app into production, and Neo4j has been extensively tested in real-world scenarios to ensure its stability and performance.