The Philosophy Behind unicorn
Being a server that only runs on Unix-like platforms, unicorn is strongly tied to the Unix philosophy of doing one thing and (hopefully) doing it well. Despite using HTTP, unicorn is strictly a backend application server for running Rack-based Ruby applications.
Avoid Complexity
Instead of attempting to be efficient at serving slow clients, unicorn relies on a buffering reverse proxy to efficiently deal with slow clients.
unicorn uses an old-fashioned preforking worker model with blocking I/O. Our processing model is the antithesis of more modern (and theoretically more efficient) server processing models using threads or non-blocking I/O with events.
Threads and Events Are Hard
…to many developers. Reasons for this is beyond the scope of this document. unicorn avoids concurrency within each worker process so you have fewer things to worry about when developing your application. Of course unicorn can use multiple worker processes to utilize multiple CPUs or spindles. Applications can still use threads internally, however.
Slow Clients Are Problematic
Most benchmarks we’ve seen don’t tell you this, and unicorn doesn’t care about slow clients… but you should.
A “slow client” can be any client outside of your datacenter. Network traffic within a local network is always faster than traffic that crosses outside of it. The laws of physics do not allow otherwise.
Persistent connections were introduced in HTTP/1.1 reduce latency from connection establishment and TCP slow start. They also waste server resources when clients are idle.
Persistent connections mean one of the unicorn worker processes (depending on your application, it can be very memory hungry) would spend a significant amount of its time idle keeping the connection alive and not doing anything else. Being single-threaded and using blocking I/O, a worker cannot serve other clients while keeping a connection alive. Thus unicorn does not implement persistent connections.
If your application responses are larger than the socket buffer or if you’re handling large requests (uploads), worker processes will also be bottlenecked by the speed of the client connection. You should not allow unicorn to serve clients outside of your local network.
Application Concurrency != Network Concurrency
Performance is asymmetric across the different subsystems of the machine and parts of the network. CPUs and main memory can process gigabytes of data in a second; clients on the Internet are usually only capable of a tiny fraction of that. unicorn deployments should avoid dealing with slow clients directly and instead rely on a reverse proxy to shield it from the effects of slow I/O.
Improved Performance Through Reverse Proxying
By acting as a buffer to shield unicorn from slow I/O, a reverse proxy will inevitably incur overhead in the form of extra data copies. However, as I/O within a local network is fast (and faster still with local sockets), this overhead is negligible for the vast majority of HTTP requests and responses.
The ideal reverse proxy complements the weaknesses of unicorn. A reverse proxy for unicorn should meet the following requirements:
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It should fully buffer all HTTP requests (and large responses). Each request should be “corked” in the reverse proxy and sent as fast as possible to the backend unicorn processes. This is the most important feature to look for when choosing a reverse proxy for unicorn.
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It should spend minimal time in userspace. Network (and disk) I/O are system-level tasks and usually managed by the kernel. This may change if userspace TCP stacks become more popular in the future; but the reverse proxy should not waste time with application-level logic. These concerns should be separated
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It should avoid context switches and CPU scheduling overhead. In many (most?) cases, network devices and their interrupts are only be handled by one CPU at a time. It should avoid contention within the system by serializing all network I/O into one (or few) userspace processes. Network I/O is not a CPU-intensive task and it is not helpful to use multiple CPU cores (at least not for GigE).
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It should efficiently manage persistent connections (and pipelining) to slow clients. If you care to serve slow clients outside your network, then these features of HTTP/1.1 will help.
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It should (optionally) serve static files. If you have static files on your site (especially large ones), they are far more efficiently served with as few data copies as possible (e.g. with sendfile() to completely avoid copying the data to userspace).
nginx is the only (Free) solution we know of that meets the above requirements.
Indeed, the folks behind unicorn have deployed nginx as a reverse-proxy not only for Ruby applications, but also for production applications running Apache/mod_perl, Apache/mod_php and Apache Tomcat. In every single case, performance improved because application servers were able to use backend resources more efficiently and spend less time waiting on slow I/O.
Worse Is Better
Requirements and scope for applications change frequently and drastically. Thus languages like Ruby and frameworks like Rails were built to give developers fewer things to worry about in the face of rapid change.
On the other hand, stable protocols which host your applications (HTTP and TCP) only change rarely. This is why we recommend you NOT tie your rapidly-changing application logic directly into the processes that deal with the stable outside world. Instead, use HTTP as a common RPC protocol to communicate between your frontend and backend.
In short: separate your concerns.
Of course a theoretical “perfect” solution would combine the pieces and maybe give you better performance at the end of the day, but that is not the Unix way.
Just Worse in Some Cases
unicorn is not suited for all applications. unicorn is optimized for applications that are CPU/memory/disk intensive and spend little time waiting on external resources (e.g. a database server or external API).
unicorn is highly inefficient for Comet/reverse-HTTP/push applications where the HTTP connection spends a large amount of time idle. Nevertheless, the ease of troubleshooting, debugging, and management of unicorn may still outweigh the drawbacks for these applications.