In this blog post I will show you how you can measure the usage of host resources by Hyper-V virtual machines. This is yet another feature that was introduced in Windows Server 2012 Hyper-V that isn’t immediately obvious and is driven by using Windows PowerShell. So why should you use resource metering in Hyper-V? Read on to see why this feature is so important.
Why is Hyper-V Resource Metering Important?
The American National Institute of Standards and Technology gives us one of the best definitions of a cloud in their Special Publication 800-145, entitled “The NIST Definition of Cloud Computing.” In this document they describe a cloud as having five essential characteristics. One of the traits that they describe as being necessary to have a cloud is a measured service:
Cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service [e.g., storage, processing, bandwidth, and active user accounts]. Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service.
What does this mean? A cloud enables a tenant to consume just what they need and pay for what they use. The cloud must be able to measure that usage. Using this information, a cloud vendor can charge the tenant for their resource usage.
perf [Linux] to record, benchmark, or trace CPU events running kernels and applications.
Virtual CPUs[edit]
Cloud computing can involve subdividing CPU operation into virtual central processing units[78] [vCPUs[79]].
A host is the virtual equivalent of a physical machine, on which a virtual system is operating.[80] When there are several physical machines operating in tandem and managed as a whole, the grouped computing and memory resources form a cluster. In some systems, it is possible to dynamically add and remove from a cluster. Resources available at a host and cluster level can be partitioned out into resources pools with fine granularity.
Performance[edit]
The performance or speed of a processor depends on, among many other factors, the clock rate [generally given in multiples of hertz] and the instructions per clock [IPC], which together are the factors for the instructions per second [IPS] that the CPU can perform.[81] Many reported IPS values have represented "peak" execution rates on artificial instruction sequences with few branches, whereas realistic workloads consist of a mix of instructions and applications, some of which take longer to execute than others. The performance of the memory hierarchy also greatly affects processor performance, an issue barely considered in MIPS calculations. Because of these problems, various standardized tests, often called "benchmarks" for this purpose—such as SPECint—have been developed to attempt to measure the real effective performance in commonly used applications.
Processing performance of computers is increased by using multi-core processors, which essentially is plugging two or more individual processors [called cores in this sense] into one integrated circuit.[82] Ideally, a dual core processor would be nearly twice as powerful as a single core processor. In practice, the performance gain is far smaller, only about 50%, due to imperfect software algorithms and implementation.[83] Increasing the number of cores in a processor [i.e. dual-core, quad-core, etc.] increases the workload that can be handled. This means that the processor can now handle numerous asynchronous events, interrupts, etc. which can take a toll on the CPU when overwhelmed. These cores can be thought of as different floors in a processing plant, with each floor handling a different task. Sometimes, these cores will handle the same tasks as cores adjacent to them if a single core is not enough to handle the information.
Due to specific capabilities of modern CPUs, such as simultaneous multithreading and uncore, which involve sharing of actual CPU resources while aiming at increased utilization, monitoring performance levels and hardware use gradually became a more complex task.[84] As a response, some CPUs implement additional hardware logic that monitors actual use of various parts of a CPU and provides various counters accessible to software; an example is Intel's Performance Counter Monitor technology.[2]