Applies to openSUSE Leap 42.1

Part IV Resource Management

8 General System Resource Management

Tuning the system is not only about optimizing the kernel or getting the most out of your application, it begins with setting up a lean and fast system. The way you set up your partitions and file systems can influence the server's speed. The number of active services and the way routine tasks are scheduled also affects performance.

9 Kernel Control Groups

Kernel Control Groups (abbreviated known as cgroups) are a kernel feature that allows aggregating or partitioning tasks (processes) and all their children into hierarchical organized groups. These hierarchical groups can be configured to show a specialized behavior that helps with tuning the system to make best use of available hardware and network resources.

In the following sections, we often reference kernel documentation such as /usr/src/linux/Documentation/cgroups/. These files are part of the kernel-source package.

This chapter is just an overview. To use cgroups properly and to avoid performance implications, you must study the provided references.

10 Automatic Non-Uniform Memory Access (NUMA) Balancing

There are physical limitations to hardware that are encountered when large numbers of CPU and memory are required. For the purposes of this chapter, the important limitation is that there is limited communication bandwidth between the CPUs and the memory. One architecture modification that was introduced to address this is Non-Uniform Memory Access (NUMA).

In this configuration, there are multiple nodes. Each of the nodes contains a subset of all CPUs and memory. The access speed to main memory is determined by the location of the memory relative to the CPU. The performance of a workload depends on the application threads accessing data that is local to the CPU the thread is executing on. Automatic NUMA Balancing is a new feature of SLE 12. Automatic NUMA Balancing migrates data on demand to memory nodes that are local to the CPU accessing that data. Depending on the workload, this can dramatically boost performance when using NUMA hardware.

11 Power Management

Power management aims at reducing operating costs for energy and cooling systems while at the same time keeping the performance of a system at a level that matches the current requirements. Thus, power management is always a matter of balancing the actual performance needs and power saving options for a system. Power management can be implemented and used at different levels of the system. A set of specifications for power management functions of devices and the operating system interface to them has been defined in the Advanced Configuration and Power Interface (ACPI). As power savings in server environments can primarily be achieved at the processor level, this chapter introduces some main concepts and highlights some tools for analyzing and influencing relevant parameters.

Print this page