When you run Plastic in centralized mode, especially on wide area networks or across VPNs, you’ll be hit by network issues: latency, slow down, connection problems… Then you have two options: you can use the distributed system to avoid being hit by the network (setting up a local server at your office to communicate with the central one, then avoiding a huge number of roundtrips), or you can set up a proxy server to greatly reduce network traffic and improve performance.
Depending on your own circumstances, preferences, network resources and so on, you can go from one or the other. At the end of the day what we try to come up with is a good set of options so you can choose.
How the proxy server works
The proxy server works in a pretty straightforward way: it simply caches revision data (file data actually) to make it available to clients so that they don’t have to go and query the central server. It greatly reduces network usage since normally data transfers (more than metadata) generate most of the daily traffic.
In order to use the proxy server the clients need to be specifically configured (a detailed explanation later), so every time they need to request data, they’ll ask the proxy server, which will make the call on their behalf, handle concurrent requests of the same revision so the data is retrieved only once (reducing data traffic) and store the data locally (using a pre-configured cache directory) before returning it to the client.
The proxy doesn’t need any configuration since:
Data is stored by server and repository (a different directory for each server and then a directory for each repository).
The following figure shows how the basic communication flow works and how data is arranged inside the proxy server data location.
The next graphic explains how the individual calls requesting data for revisions are handled by the proxy server which will cache the received data after calling the repository server.
And the same principle will apply when scenarios get more complicated and instead of a single server and repository there are several servers and repositories involved.
What happens if the proxy server goes down?
Currently the mechanism we’ve implemented is also pretty transparent: if the proxy server goes down (or you shut it down), the client will detect it (network connection will fail) and will directly contact the real repository server. It will log it for diagnostic purposes. A client won’t use again the proxy server once it detects it is down until the client itself gets restarted.
Installing a proxy server
Installing a proxy server is pretty straightforward on Windows, Linux and Mac OS X. You just have to get the installer and follow the steps. In fact, it will only ask you for a directory to locate the cached data, and that’s all.
The configuration will be saved on a plasticcached.conf file with a single entry for the directory mentioned above.
Configuring a proxy server on the client side
There’s only a simple change to perform on the clients: run the configuration wizard (from the GUI preferences option or running plastic - -configure) and set the right proxy server.
How a typical proxy server set up looks like
The initial situation before you set up a proxy server will be something like the following.
The network traffic (in red) is too high and clients are slowed down. In order to solve it you can set up a couple of proxy servers, one at each LAN.
Now the data traffic will be local and performance will get much better.
Ok, so far I’ve been telling that performance gets better on centralized setups when you introduce a proxy server, but I didn’t share any data about how better does it actually get.
We run load tests on a cluster to check and improve Plastic SCM performance, and this time we focused on finding out how to reduce network traffic by using proxy servers.
We use the following configuration: 4 different networks where computers are connected through a gigabit connection and then one central server connected to the different sub-networks with a 100Mbps connection (which is the actual limiting factor). In total we will use 71 concurrent clients.
We use a very simple repository were a simple copy consist on 25k files and about 3k directories and a total of 300Mb.
The test itself is very simple:
The following figure depicts the network layout and the machines at each lab (CPU, total bogomips of each node and RAM).
Then we run the test with and without proxy servers and compare the results.
Linux 64bits + proxy servers
As you can see, in this very simple example, we can multiply overall performance by a factor of 3 by introducing proxy servers. The actual number of proxy servers and configuration will vary depending on your layout, we tested with 4 proxy servers because we’re using 4 networks, but it would vary depending on the topology.