Large-Scale Linux Configuration Management
The difficulty of installing and setting up Linux is often mentioned as one of the reasons it is not more widely used. People usually assume that editing the traditional UNIX configuration files is more difficult than using the graphical interfaces provided by operating systems like Microsoft Windows. For a novice user with a single machine, this may be true, and most commercial UNIX vendors now supply GUI-based tools for at least some aspects of system configuration. Under Linux, projects like COAS (see Resources 1) and the Red Hat distribution are starting to cater to this need.
For a large installation with tens or hundreds of machines, the GUI approach does not work—entering individual configuration data for 200 machines is simply not practical. As well as the ability to install large numbers of machines, big sites usually need more control over the configuration; for example, they might need to install new machines with a configuration which is guaranteed to be identical to an existing one. Machines are also likely to need periodical reconfiguring as their use changes, or simply to keep up to date with the latest software and patches.
To do this effectively requires a good deal of automation, and large UNIX sites have been developing their own tools for many years (see Resources 2). The flexibility and accessibility of UNIX configuration files makes Linux particularly suitable for automation, and those sites attempting to install and manage large numbers of NT systems are often likely to find the process more difficult (see Resources 3).
The Division of Informatics at Edinburgh University has over 500 UNIX machines, with a wide variety of different configurations. Most of them are installed and maintained automatically using the LCFG (Local ConFiGuration) system, originally developed several years ago (see Resources 4). Both client and server configurations can be easily reproduced to replace failed machines or to create tens of identical systems for a new laboratory. Reconfiguration is thus a continuous process; for example, machines adjust every night to ensure they are carrying the latest versions of the required software. Linux (we use a version of the Red Hat distribution) has proven itself well-suited to this environment, and it has recently overtaken Solaris to become the most popular desktop system, both for staff use and student laboratories.
An automatic configuration system should be able to build working machines from scratch with no manual intervention. This includes configuration of the basic operating system (disk partitions, network adaptors), loading of required software, and configuration of application-specific services such as web servers. This allows failed machines to be recreated quickly, using replacement hardware, and new machines to be installed efficiently, even by junior staff. As a side effect, it also avoids the need for backups of any system partition.
The set of configuration information that drives this build process defines the personality of an individual machine, and it is extremely useful if this specification is available in an explicit form (such as a plaintext file or a database). Machines can then be cloned simply by copying their specification and applying the automatic build. This is important for installing multiple similar machines, such as in a student laboratory. The master copy of the specification should be held remotely from the machine, so that it is available even when the machine is down. This allows programs to automatically verify individual configurations and even the relationships between machines, such as ensuring every client's specified DNS server is actually configured to run a name daemon. The specification can also be generated from higher-level descriptions of a machine's function. An inheritance model is very useful, since many machine configurations can be conveniently described as small variations of a generic configuration for a particular class.
Traditional configuration systems are often static, in the sense that the configuration is applied only at the time the machine is installed. Most vendor-supplied installation processes fall into this category, as do systems based on cloning by copying disk images. If subsequent changes to the configuration have to be applied manually, the configuration is almost certain to “rot”, and it is impossible to be confident that all machines are correctly configured. Obvious misconfigurations simply result in users having malfunctioning machines. More subtle misconfigurations may go unnoticed and pose serious security problems, for example. Even though a fully dynamic system is not practical, an ideal system will continually adjust the configuration to conform to the specification. Some parameters can be changed immediately to track a change in the specification; some, such as a network address, may be changed only when the machine reboots; and others, such as a disk partitioning, may require a complete rebuild.
If a configuration system is incomplete and manual intervention is necessary, many of the benefits are lost. However, constructing a comprehensive system to cover every conceivable parameter is clearly impractical. The key problem is trying to create an extensible framework flexible enough to allow new parameters and components to be incorporated with little effort. An individual instance of the system can then evolve at a particular site to suit the local requirements. If it is going to be extended on demand by working administrators, the framework needs to be extremely lightweight and comprehensible in a short amount of time. It must be easy to create components in a familiar language, and to interface them to new subsystems which require configuration. Open-source software is an advantage, since it is often easy to base a new extension on one that already exists.
|Updates from LinuxCon and ContainerCon, Toronto, August 2016||Aug 23, 2016|
|NVMe over Fabrics Support Coming to the Linux 4.8 Kernel||Aug 22, 2016|
|What I Wish I’d Known When I Was an Embedded Linux Newbie||Aug 18, 2016|
|Pandas||Aug 17, 2016|
|Juniper Systems' Geode||Aug 16, 2016|
|Analyzing Data||Aug 15, 2016|
- Updates from LinuxCon and ContainerCon, Toronto, August 2016
- NVMe over Fabrics Support Coming to the Linux 4.8 Kernel
- What I Wish I’d Known When I Was an Embedded Linux Newbie
- New Version of GParted
- All about printf
- Analyzing Data
- Tor 0.2.8.6 Is Released
- Blender for Visual Effects
- Tech Tip: Really Simple HTTP Server with Python
With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide