In the client/server architecture, a relatively small server farm manages the cached data of and access to the same data for many client applications. Clients can update and access data efficiently, leaving the servers to manage data distribution to other clients and any synchronization with outside data stores.
Standard Client/Server Deployment
In the most common client/server topology, a farm of cache servers provides caching services to many clients. Cache servers have a homogeneous data store in data regions that are replicated or partitioned across the server farm.
VMware GemFire locators provide reliable and flexible server discovery services for your clients. You can use all servers for all client requests, or group servers according to function, with the locators directing each client request to the right group of servers.
How Client/Server Connections Work
The server pools in your VMware GemFire client processes manage all client connection requests to the server tier. To make the best use of the pool functionality, you should understand how the pool manages the server connections.
Configuring a Client/Server System
Configure your server and client processes and data regions to run your client/server system.
Organizing Servers Into Logical Member Groups
In a client/server configuration, by putting servers into logical member groups, you can control which servers your clients use and target specific servers for specific data or tasks. You can configure servers to manage different data sets or to direct specific client traffic to a subset of servers, such as those directly connected to a back-end database.
Client/Server Example Configurations
For easy configuration, you can start with these example client/server configurations and modify for your systems.
Fine-Tuning Your Client/Server Configuration
You can fine-tune your client/server system with server load-balancing. For example, you can configure how often the servers check their load with the cache server
load-poll-interval property, or configure your own server load metrics by implementing the