The Scalable Test Platform

Testing may not be fun, but it's important; Open SourceDevelopment Lab and Scalable Test Platform want to help.

The Open Source Development Lab (OSDL) is a nonprofit company working to enhance Linux scalability and telco capabilities. OSDL sponsors ( have financed a full-scale test and development lab, complete with terabytes of storage and an array of SMP servers with anywhere from 2 to 16 CPUs. At the lab we provide developers with full access to enterprise-class machines via remote login.

We have been working with developers on the creation and execution of their tests. During this process, we have noticed a number of things that have to be done again and again for each test that comes through the lab. We listed the tasks that went into running an average test sequence and found a great deal of the process involved human interaction that could be automated. The Scalable Test Platform (STP) is the result of our attempt to automate the testing process from request to report.

Problems with Testing Methods

Benchmarking itself has inherent concept problems that are outside both the scope of this article and the scope of the Scalable Test Platform effort. There are, however, solvable problems with current testing practices, and that is what the STP attempts to address. Please keep in mind, the benchmarking we focus on is completely different from methods used to get marketable benchmark numbers.

The configuration of a testing environment is rarely as well documented as it should be. Documentation on the setup of systems used in tests is usually limited to what the tester believes is relevant to their specific research goals. This lack of detail will cause problems later on, when other analysts are examining the report. It is not uncommon for an analyst to have to duplicate an entire test sequence to get the data required to answer questions that come up later. It is also common practice for a testing setup to be only partially automated. The resulting human interaction at undocumented moments will also affect the repeatability of the results.

Performance testing can require massive resources, both in the form of time and hardware. How many open-source developers can get access to 50 two-way client servers on a gigabit network in order to test a server farm made up of multiple 8-CPU servers and a 16-CPU server? Few companies would stretch to provide access to hardware like that and then only with a full entourage of managers and the potential revenue return to justify the expense. A good idea conceived by a developer without access to hardware like this is likely to remain unexplored.

Currently no central archive exists of well-documented results for performance, stability and standard compliance tests. Researchers are forced to run their own tests or pick and choose from mediocre results to come up with a less-than-accurate guess. System administrators have no central place to look for starter information on what combination of kernel, distribution and hardware tends to work well for a workload similar to what they anticipate. This lack of available research leads to confusion regarding the performance and reliability among the myriad of Linux choices.

Linux Kernel Development

Linux kernel developers cannot spend the time and effort required to run long performance and stability tests on their patches. Even if a developer is willing to spend the time testing a patch, testing software often requires a great deal of knowledge and specialized hardware just to install and configure. Occasionally this situation leads to problems being introduced into both the stable and development kernel trees. It also can allow problems solved previously to recur in future development but go unnoticed because of a lack of regression testing.

A number of developers have spoken up on the Linux kernel mailing list requesting a standard testing procedure for new patches. Many users and developers agree that a simple procedure, including performance, stability, standards compliance and regression testing, would benefit Linux kernel development.

While you can't test for every bug out there, you can check for common types of problems. It's generally not too difficult to add a regression test case to your testing suite after a bug is found and fixed. The problem is not in the creation of these tests. Most developers realize that it's a good idea to have a few synthetic tests available and very often do so. The problem is that most developers can't or won't take the time to configure a full range of verification tests. While coding can be fun, testing is often quite boring. If a developer could easily request a full test of their code and then continue working while someone else does the dirty work, we think they would be more inclined to attempt verification runs on their patches.