This article is cross-posted on make.rafflecopter.com.
The core of any distributed system is the Enterprise Service Bus (ESB). Its how the disparate, coupled components communicate, either through request/reply semantics or asynchronous messaging. Whether your building a web app, a SAAS, a PAAS, or a radar, distributed systems are the right way to go.
First, a moment on why distributed systems are so popular. Distributing your system (as opposed to a monolithic application) will decrease performance due increased overhead (i.e. time on the ESB versus a simple function call). But it will allow increased concurrency, easier development (like functional programming, composing smaller parts is easier), better management (individual services can be updated without taking down the system), and the ability to scale (buzz word!). Scaling does not just mean in users, but also in developers, as multiple composed services will be easier for larger teams to develop on (see: Amazon).
Distributing your system has benefits, but the key for success is making the tradeoff decisions to maximize the benefits you care about. There are primary tradeoffs to think about when choosing an ESB: communication pattern and broker.
Communication Pattern: Remote Procedure Call (RPC) vs Publish/Subscribe (Pub/Sub)
In RPC, each communication requires a response which may be waited for in a synchronous or asynchronous way. The pub/sub pattern is a system where messages are sent (published) asynchronously on channels which are subscribed to by other applications on the network. There are other minutia to consider, but these are the primary two patterns. RPC implies your communications need responses from specific endpoints, whereas pub/sub implies that communication is undirected, that is, messages are not sent to direct places, only on channels where others may be listening.
The biggest problem in managing and monitoring a distributed system is a constantly changing topology, or map of how applications communicate. Whether your running 5 services with 2 instances each, or 1000 services with 10,000 nodes, topology will change. In order to manage the topology as it changes, a broker is very useful. A broker is a central place(es) where all nodes connect to in order to communicate. Brokers can be proxies for messages or can be discovery services that allow nodes to connect to each other. Brokers help improve topology management by reducing the work that users have to do. Proxy brokers can help monitoring by having a central place to keep track of traffic and usage of the ESB. Proxy brokers are the most popular of brokered systems because of the great tooling and monitoring it provides (see: RabbitMQ and Redis). Unbrokered systems such as CORBA and OSGi have increased wire performance, but use discovery services to find other endpoints, which can increase wire traffic.
Every system has different requirements, and different tradeoff decisions are made. As we at Rafflecopter expand our system, we want to nail down our ESB. We’re building and expanding a web application with a scaling number of users and backend systems such as analytics, recommendations, and social connections. For a system like this, we chose the pub/sub pattern because asynchronous communcation will be the core unit of communication in the system. If request/reply semantics are needed in the rare case, we’ll use http. Additionally, we don’t fall into the “needing extreme performance” group, so we decided to stick wth a brokered system.
Back when I used to work for the government doing embedded computing, we made different choices, going with a brokerless sysytem and a binary protocol for the bare-bones speed requirements and giving both RPC and Pub/Sub patterns available. But in today’s world of big servers and complicated applications running in the milliseconds (not microseconds), the advantages of a brokered system weigh heavily in the tradeoff decision.