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![Comparison
Hypervisor (VM) Containers (CT)
One real HW, many virtual One real HW (no virtual
HWs, many OSs HW), one kernel, many
High versatility – can run userspace instances
different OSs Higher density,
Lower density, natural page sharing
performance, scalability Dynamic resource
«Lowers» are mitigated by allocation
new hardware features
(such as VT-D)
Native performance:
[almost] no overhead](https://image.slidesharecdn.com/2012-04-openstack-openvz-linux-containers-120416140246-phpapp01/75/OpenVZ-Linux-Containers-7-2048.jpg)
![Comparison
Hypervisor (VM) Containers (CT)
One real HW, many virtual One real HW (no virtual
HWs, many OSs HW), one kernel, many
High versatility – can run userspace instances
different OSs Higher density,
Lower density, natural page sharing
performance, scalability Dynamic resource
«Lowers» are mitigated by allocation
new hardware features
(such as VT-D)
Native performance:
[almost] no overhead](https://crownmelresort.com/image.slidesharecdn.com/2012-04-openstack-openvz-linux-containers-120416140246-phpapp01/75/OpenVZ-Linux-Containers-7-2048.jpg)
Uploaded byKirill Kolyshkin
OpenVZ Linux Containers
The document presents an overview of OpenVZ and Linux container virtualization, comparing it to hypervisors. It discusses various virtualization techniques, the architecture of OpenVZ, and its components, including kernel features for resource management and migration. Additionally, it highlights the advantages of container-based virtualization in terms of performance, scalability, and density, and mentions ongoing efforts to integrate OpenVZ into the Linux kernel.
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OpenVZ Linux Containers
- 1. OpenVZ Linux Containers Kir Kolyshkin <kir@openvz.org> OpenStack Design Summit 16 April 2012, San Francisco
- 2. Agenda ● Virtualization approaches ● Containers versus hypervisors: ● OpenVZ internals ● New features
- 3. What is virtualization? Virtualizationis a technique for deploying technologies. Virtualization creates a level of indirection or an abstraction layer between a physical object and the managing or using application. http://www.aarohi.net/info/glossary.html Virtualization is a framework or methodology of dividing the resources of a computer into multiple execution environments... http://www.kernelthread.com/publications/virtualization/ A key benefit of the virtualization is the ability to run multiple operating systems on a single physical server and share the underlying hardware resources – known as partitioning. http://www.vmware.com/pdf/virtualization.pdf 3
- 4. Ways to Virtualize ● Hardware Emulation ● Para-Virtualization ● Containers-type Virtualization (a.k.a. OS-level Virtualization) ● Multi-server virtualization 4
- 5. Emulation/Paravirtualization ● VMware ● Xen ● Parallels ● KVM ● QEmu ● Bochs 5
- 6. Containers ● OpenVZ / Parallels Containers ● LXC ● FreeBSD jails ● Solaris Containers/Zones ● IBM AIX6 WPARs (Workload Partitions) 6
- 7. Comparison Hypervisor (VM) Containers (CT) One real HW, many virtual One real HW (no virtual HWs, many OSs HW), one kernel, many High versatility – can run userspace instances different OSs Higher density, Lower density, natural page sharing performance, scalability Dynamic resource «Lowers» are mitigated by allocation new hardware features (such as VT-D) Native performance: [almost] no overhead
- 8. Containers are thinnerand more performant than hypervisors ● Containers – Share host OS and Drivers – Have small virtualization layer – Naturally share pages ● Hypervisors – Have separate OS plus virtual Hardware – Hardware emulation requires VMM state – Have trouble sharing Guest OS pages ● Containers are more elastic than hypervisors ● Container slicing of the OS is ideally suited to cloud slicing ● Hypervisors’ only advantage in IaaS is support for different OS families on one server
- 9. Density Hypervisor 41 VMs Containers with page sharing 112 CTs Containers without page sharing 57 CTs Admin CP time > 4 sec
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- 13. OpenVZ vs. Xenfrom HP labs ● For all the configuration and workloads we have tested, Xen incurs higher virtualization overhead than OpenVZ does ● For all the cases tested, the virtualization overhead observed in OpenVZ is limited, and can be neglected in many scenarios ● Xen systems becomes overloaded when hosting four instances of RUBiS, while the OpenVZ system should be able to host at least six without being overloaded
- 14. Evolution of OperatingSystems ● Multitask many processes ● Multiuser many users ● Multicontainer many containers (CTs, VEs, VPSs, guests, partitions...) 14
- 15. OpenVZ: components Kernel – Namespaces: virtualization and Isolation – CGroups: Resource Management – Checkpoint/restart (live migration) Tools – vzctl: containers control utility Templates – precreated images for fast container creation 15
- 16. Kernel: Virtualization &Isolation Each container has its own ● Files: chroot() System libraries, applications, virtualized /proc and /sys, virtualized locks etc. ● Process tree (PID namespace) Featuring virtualized PIDs, so that the init PID is 1 ● Network (net namespace) Virtual network device, its own IP addresses, set of netfilter and routing rules ● Devices Plus if needed, any VE can be granted access to real devices like network interfaces, serial ports, disk partitions, etc. ● IPC objects (IPC namespace) shared memory, semaphores, messages ● … 16
- 17. Kernel: Resource Management Managedresource sharing and limiting. ● User Beancounters per-CT resource counters, limits, and guarantees (kernel memory, network buffers, phys pages, etc.) ● Fair CPU scheduler (with shares and hard limits) ● Two-level disk quota (first-level: per-CT quota; second-level: ordinary user/group quota inside a CT) ● Disk I/O priority (also per-CT) 17
- 18. Kernel: Checkpointing/Migration ● Complete CT state can be saved in a file – running processes – opened files – network connections, buffers, backlogs, etc. – memory segments ● CT state can be restored later ● CT can be restored on a different server
- 19. Tools: CT control # vzctl create 101 --ostemplate fedora-15 # vzctl set 101 --ipadd 20.21.22.23/24 --save # vzctl start 101 # vzctl exec 101 ps ax PID TTY STAT TIME COMMAND 1 ? Ss 0:00 init 11830 ? Ss 0:00 syslogd -m 0 11897 ? Ss 0:00 /usr/sbin/sshd 11943 ? Ss 0:00 xinetd -stayalive -pidfile ... 12218 ? Ss 0:00 sendmail: accepting connections 12265 ? Ss 0:00 sendmail: Queue runner@01:00:00 13362 ? Ss 0:00 /usr/sbin/httpd 13363 ? S 0:00 _ /usr/sbin/httpd .............................................. 13373 ? S 0:00 _ /usr/sbin/httpd 6416 ? Rs 0:00 ps axf # vzctl enter 101 bash# logout # vzctl stop 101 # vzctl destroy 101 19
- 20. Feature: VSwap ● A new approach to memory management, only two parameters to configure: RAM, swap ● Appeared in RHEL6-based OpenVZ kernel ● Swap is virtual, no actual I/O is performed ● Slow down to emulate real swap ● Only when actual global RAM shortage occurs, virtual swap goes into the real swap
- 21. Feature: ploop ● Reimplementation of Linux loop device ● Modular architecture ● Support for different file formats (“plain”, QCOW2, etc) ● Network storage is supported (NFS) ● Snapshots and fast provisioning via stacked images ● Write tracker for faster live migration
- 22. Feature: CRIU ● Checkpoint/Restore (mostly) In Userspace ● Kernel manage processes, knows everything ● All efforts to merge CPT to Linux kernel failed ● Solution: let's do it in userpace! ● Minimal kernel intervention ● First set of patches was recently accepted ● See http://criu.org/
- 23. CRIU merge commentfrom akpm Checkpoint/restart feature work. A note on this: this is a project by various mad Russians to perform c/r mainly from userspace, with various oddball helper code added into the kernel where the need is demonstrated. So rather than some large central lump of code, what we have is little bits and pieces popping up in various places which either expose something new or which permit something which is normally kernel-private to be modified. The overall project is an ongoing thing. I've judged that the size and scope of the thing means that we're more likely to be successful with it if we integrate the support into mainline piecemeal rather than allowing it all to develop out-of-tree.
- 24. Development ● Most of the magic is in the kernel ● Use RHEL kernels as a base ● Support it for many years (RHEL4 kernels from 2006 are still supported) ● Merge bits and pieces upstream, then reuse ● Plans to include most of the kernel stuff till RHEL7
- 25. LXC vs OpenVZ ● OpenVZ was off-the-mainline historically – developing since 2000 ● We are working on merging bits and pieces, with more than 1500 patches in mainline ● Code in mainline is used by OpenVZ ● OpenVZ is production ready and stable ● LXC is a work-in-progress – not a ready replacement for OpenVZ ● We will keep maintaining OpenVZ for a while
- 26. To mainline wego ● II Parallels is the driving force behind Linux containers ● Collaborating with the Linux community to move OpenVZ upstream into the Linux kernel ● Ensures that Linux delivers a single consistent container technology ● vzctl will support mainline containers ● No rerun of Xen/KVM wars!
- 27. To sum itup ● Platform-independent – as long as Linux supports it, we support it ● No problems with scalability or disk I/O – lots of memory, lots of CPUs no prob – native I/O speed ● Unbeatable density and performance ● Reliable, supported, free ● Plays well with others
- 28.
Editor's Notes
- #2 The goal of Intel vConsolidate benchmark is to measure aggregated server performance in consolidation scenario: when different (and non-related unlike to LAMP benchmark) applications are running on the same box each in its own virtual environment (virtual machine or container). vConsolidate benchmark was developed by Intel in cooperation with other vendors. It runs separate workloads with Java (SPECjbb test), Mail, Web and Database VMs running concurrently. Each set of such VMs is called CSU - Consolidation Stack Unit. Performance metric is a geomean from throughput of each workload type: transactions/sec for Db, requests/sec for Web and java operations/sec for Java. The same type of metric is commonly used in other benchmarks like those from SPEC. vConsolidate benchmark is very similar to other virtualization specific benchmarks like VMMark from VMWare and SPECvirt, but the latter are more enterprise oriented and generate the load requiring a fast SAN storage and high end hardware. Since we believe containers benefits are even more prominent on commodity hardware we use vConsolidate benchmark to demonstrate that. OpenVZ demonstrates outstanding performance benefits over hypervisors in case of multi-processor environments and multi-threaded workloads: Almost 3x times better overall performance in case of single set of workloads (1 CSU). 2.1-2.2x times better overall performance on 5 and 10 CSU.
- #5 multi-server virtualization is actually not about virtualization; it's rather more about grid and clustering, so I'm not going to cover that.
- #6 Low manageability: many os to manage, must login to each, mass management is equally difficult to multiple physical. Low performance is/will be mitigated by Intel VT and AMD V, so it's not really an issue. After all, emulation approach looks strange: why do we run OS on top of another OS? OS is designed to be run on hardware, not something virtual.
- #11 LAMP (acronym for Linux, Apache, MySQL, PHP) software stack is widely used for building modern web sites on Linux. So it's quite natural that there is a need to understand how well such type of workloads run in virtualized environment and how many LAMPs virtualization can bare on a single piece of hardware. 2 important metrics are presented in this report: total number of serviced requests/sec and average response time. To measure LAMP software stack performance and density we use DVD-Store E-Commerce benchmark developed by Dell. OpenVZ shows the best performance over solutions tested: OpenVZ 38% faster than XenServer and more than x2 times faster than HyperV and ESXi under high load.
- #12 OpenVZ shows the best response time over solutions tested: 33% better response time compared to ESXi and x2 times better response time than XenServer and HyperV
- #13 The goal of Intel vConsolidate benchmark is to measure aggregated server performance in consolidation scenario: when different (and non-related unlike to LAMP benchmark) applications are running on the same box each in its own virtual environment (virtual machine or container). vConsolidate benchmark was developed by Intel in cooperation with other vendors. It runs separate workloads with Java (SPECjbb test), Mail, Web and Database VMs running concurrently. Each set of such VMs is called CSU - Consolidation Stack Unit. Performance metric is a geomean from throughput of each workload type: transactions/sec for Db, requests/sec for Web and java operations/sec for Java. The same type of metric is commonly used in other benchmarks like those from SPEC. vConsolidate benchmark is very similar to other virtualization specific benchmarks like VMMark from VMWare and SPECvirt, but the latter are more enterprise oriented and generate the load requiring a fast SAN storage and high end hardware. Since we believe containers benefits are even more prominent on commodity hardware we use vConsolidate benchmark to demonstrate that. OpenVZ demonstrates outstanding performance benefits over hypervisors in case of multi-processor environments and multi-threaded workloads: Almost 3x times better overall performance in case of single set of workloads (1 CSU). 2.1-2.2x times better overall performance on 5 and 10 CSU.
- #15 This is a natural step in evolution of the Operating Systems, and Linux is the first one. Virtualization is really needed by everyone, and will be a part of any OS kernel.
- #18 Resource management is a very important and very complex thing. Consider the story of CPU scheduler development: (1) Need for CPU shares – to balance CPU power between CTs. So every CT have a guaranteed minimum share but can use up to all CPU power if available. (1a) BUT as number of CTs per server grow, guaranteed minimum remains but power decreases, thus ppl complain, thus (2) Need for upper CPU limit. Hard limits the max CPU power, even if it's available. It solves 1a problem, but introduces another problem – power is not used even if available. Thus (3) Need for burstable CPU limit (not yet implemented). CT can have up to all CPU power but not always – say, limited per month or so.
- #20 I will actually show a two-minute live demo in a green-on-black terminal instead of this page.