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WP/Containers density

4 bytes added, 14:30, 15 March 2011
multiple wording fixes
== What is density? ==
Density is a characteristics characteristic which tells one how many containers (CTs) or Virtual Machines (VMs) virtualization technology can run successfully on the a given hardware. Typically users also care for quality of service of their software, i.e. how well their services are working on utilized node and how fast they respond to external requests. Average Typical metrics of quality of service are average response time, 99.9% requests response time , and max response time are typical metrics of quality of service. When a hardware node is capable to bear handle the load , these metrics either do not grow much with bigger number of containers , or grow linearly. When a hardware node becomes over utilized , these metrics typically start to degrade exponentially (e.g. due to memory swap out).
== What makes containers to be perfectly suitable for high density? ==
* Containers do not reserve memory assigned to itthem. They exhibit real-time elastic behavior, : if applications a container do not use memory, then it is free for use by other containers usage. i.e. overcommit In other words, overcommitment is as natural and easy like as on a standalone Linux box , when multiple applications compete for memory resources. As a result , a simple container running ssh, apache, init and cron takes only 10-20Mb of physical RAM. Sure, for efficient caching of apache pages more RAM is needed.
* Containers memory management is system-wide wise. If one container needs more physical RAM (e.g. for apache pages caching) and hardware node have no more memory available, kernel will automatically reclaim last recently used caches of other containers.
* Parallels Virtuozzo containers Containers product does goes a step further and introduces containers by introducing container templates, which are used as a basis for all containers , and a special Copycopy-on-Write write filesystem , which makes sure that original template is kept untouched and container gets its own private copy of template file when it tries to modify it. As a result all common files are shared across the containers and present on disk and in memory caches in a single instance. This saves memory, reduces I/O and makes L2/L3 caches work more effective.
== Why Virtual Machines are not that good? ==
Hypervisors (Xen, ESX, KVM) are not that good on high density scenarios. There are multiple reasons for that:
* Memory is basically reserved on the host on VM start. e.g. KVM and XEN by default reserve the whole memory by default and do not allow memory overcommitment. As a result you can't run more then 15 VMs with 1GB RAM on 16Gb box. ESX as , being the most advanced hypervisor , uses page sharing and ballooning technologies to introduce memory overcommitment. However, on practice it allows to get only about 2x times overcommitment on the guests of the same type. From our Our experiments tell that half of this the improvement is due to page sharing , and half is due to ballooning.
* Multiple kernels and their system data structures in memory. There are some technologies like RAM pages sharing and ballooning which help a bithere, too.
* what happens when CT is above it's limit
* what happens when node RAM is exhausted
* plots and examples. Kir had http_load plot in the past. We will have LAMP results as well.

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