Three-Hot Technologies and Their Usages at Huawei's Public Cloud

In this proposal, Liu Jinsong introduces Huawei's three-hot technologies: hot-fix, hot-replacement, and hot-migration (live migration). It firstly analyses the online-update needs coming from Huawei's cloud infrastructure, then discusses the different usage models of three-hot technologies. It then introduces some key technical points of three-hot technologies, for example, how to hot-replace qemu/network/storage components of Huawei's public cloud, how to reduce CPU downtime (under big memory pressure) and network breaktime (reduce VPC breaktime from several minutes to less then 100ms) of live migration, and how to ensure 100% VM alive when live migration fails.
展开查看详情

1.Three-hot Technologies a nd Their U sages at Huawei’s Public Cloud Liu Jinsong , Huang Zhichao Huawei

2.Agenda Online update requirements @ cloud Huawei’s 3-hot technologies Hot patch Hot replacement Hot migration (live migration ) 3-hot usages @ Huawei Cloud

3.Online update requirements @ cloud Cloud is complicated, need fix/update frequently Bugs & security holes Hundreds of CVE reports per year High risk security holes XSA-108 Intel security hole: spectre , meltdown, and … (it’s just 1 hole but …) Components upgrade Openstack components: nova , neutron, etc. VM related components: libvirt , qemu , ovs , vims, etc. Fast upgrade support newly-add features, say, once per month Hostos upgrade New CPU / C hipset support, i.e , Skylake adds ~40 hardware features New kernel support, w/ better performance and newly-add features CPU microcode upgrade, hardware broken Microcode for Intel security hole Memory error: UCNA, SRAO, SRAR Other unbelievable hardware broken: i.e., CPU crazy fans 

4.Online update requirements @ cloud We have to fix/upgrade the SPEED car !!!

5.Huawei’s 3-hot technologies Advantages Disadvantages hot patch Bug fix and security holes Light-weight operation Usually for small but critical fix Do not support newly-add functions/features Some bugs/security holes are hard to fix via hot patch Troublesome for SRE to manage and verify patch branches hot replacement Component replaced entirely Support newly-add features Medium-weight operation Not good at kernel fix/update hot migration (= live migration in Chinese ) Kernel upgrade Not only for upgrade Solve problems what hot patch or hot replacement cannot handle Cannot migrate vm w/ sr-iov Heavy-weight operation

6.Hot patch H ot-patch for Xen xSplice -like solution (thanks Konrad @ Oracle) Trampoline jump at the head of old func Wait for all pCPUs to stop and apply together clean stack ensure not running at any CPU Idle Before vmentry cpuid serializing Enhancement Auto build from a patch and auto test A framework to hot-patch a POD Retry, revert, and reboot handler Support hot-patching assembly code Hot-patch for KVM & Linux livepatch combine consistency model of kGraft + kPatch https:// www.slideshare.net/GlobalLogicUkraine/linux-kernel-live-patching Hot-patch for usrspace processes Huawei’s Dopra , a framework Patching qemu , ovs , vims, …

7.Hot patch use case @ Huawei cloud Fix CVE-2017-5715 (Intel Spectre ) at Xen hypervisor xSplice fix C function but cannot fix assembly code xpatch /tools/create-diff- object.c Define and handle special symbol (w/ prefix ‘_fix_’) Find correct assembly address to replace Fix vmx_asm_vmexit_handler --- arch/x86/ hvm / vmx / entry.S +++ arch/x86/ hvm / vmx / entry.S @@ -116,6 +116,81 @@ vmx_asm_vmexit_handler : + ALIGN + . globl _ fix_vmx_asm_vmexit_handler + _ fix_vmx_asm_vmexit_handler :  // special symbol w/ prefix ‘_fix_’ push % rdi         push % rsi ……         push % r15 + xor   % e di ,% edi              // fix assembly +         xor   % esi ,% esi + …… + xor   %r15,% r15 get_current ( bx ) ……

8.Advantages and disadvantages of hot patch Hot patch Light-weight operation for cloud SRE But t roublesome for SRE to manage baseline branches Some fix are hard to be hot-patched data structure (shadow variable after kernel 4.15) . rodata cannot change function api and semantic u nsafe to fix ftrace handler w/ infinite loop risk unsafe to fix NMI handler booting stage bugfix inline function s hould be very careful about deadlock do not support newly-add functions ……

9.Hot replacement Components entirely upgrade Reboot-able components: VM runtime-unrelated nova, neutron, libvirt , etc. Non reboot-able components: VM runtime-related compute ( qemu ), storage (vims), network ( ovs ), etc.

10.Hot replacement framework Unified replacement framework for OVS (network) and VIMS (storage) Preload and lazy-offload, fast switching (less than 100ms) State vs. stateless design Add component agent connecting qemu (if possible) so that no disconnect and no re-connect Qemu is another story R unning Pause U npause Old component New component Qemu Virtio BE VM Virtio FE VM Virtio FE 1 disconnect re-connect 2 States copy if need 3 VM unpause 4 Host components at backend VM at frontend Preload Lazy_offload VM pause

11.Hot replacement - qemu Qemu hot replacement Way 1: migrate vm locally may fail since insufficient memory may fail for VM under high dirty page speed Way 2: share page Zero copy Performance impact by transparent huge pages Way 3: share page table, cover old qemu VMAs except that of VM Zero copy keep pid unchange Much bigger switch downtime, kill old qemu then covered by new qemu VMAs Cannot revert if new qemu fail Way 4: share page table, but exec new qemu process Zero copy Preload new qemu sharing VM PUD with old qemu Pause old qemu and unpause new qemu Lazy-offload old qemu if new qemu success, or, revert old qemu if new qemu fail Different pid but acceptable

12.Hot migration -- challenges Live migration @ virtualization Xen live migration PV is unfriendly to live migration Buggy PV disconnect and re-connect Ecosystem issue, work around by guest whitelist but >15% guest cannot migrate Support migration among different CPUs via emulated tsc but w/ performance issue KVM live migration Not support migration among different CPUs because of native tsc (until Skylake tsc scaling) SR-IOV migration Giant VM migration under huge memory dirty ratio

13.Hot migration -- challenges Live migration @ cloud Cloud environment challenges Cloud environment is very complicated and unfriendly to live migration Different software version and configuration Different hardware types: CPU, MSRs Even buggy network switch may result in migration error !! different storage/network types Performance challenges Network breaktime , growing w/ VPC scale (10S->10 minutes) Communication among cloud components Nova, neutron, libvirt , etc. Reliability challenges Migrating VM may dead or brain-split Ensure vm 100% survive when migrate fail Large scale parallel migration challenges Server congestion, network congestion, etc. Gratuitous ARP may not accepted by parallel migrating vms Malfunction server isolation Blablabla ……

14.Hot migration design @ Huawei cloud De-couple Event mechanism and publisher-subscriber model Support different storage/network types Reliability Shakehands and roll-back when anything wrong ( vm will survive) How about shakehands broken (say, network issue)? image lock: who get the image lock will survive ( vm will not brain-split) Performance Fast event channel for performance-critical ops Network trampoline when VPC path not ready Giant vm migration Support any giant vm migration under any dirty page ratio If only transfer ratio > dirty page ratio

15.Hot migration result @ Huawei cloud Live migration for OS upgrade at all Huawei cloud sites Reliability 99.99% migration success 100% vm survive when migration fail for whatever reason Performance CPU downtime: ~25ms VPC network breaktime : 82% breaktime < 50ms 99% breaktime < 200ms 100% breaktime < 500ms Degree of parallelism Upgrade > 2000 servers per night Technically support much higher parallelism but no enough free servers Support all giant vm live migration

16.Hot migration use case @ Huawei cloud MCE/ Disk error/ Filesystem readonly …… ~1%% server crash per day, while ~48% hardware issue Dynamic resource scheduling Distributed power management Fix CVE-2017-5715 (Intel Spectre ) at KVM Better performance than upstream: 30% -> 10%- Retpolin e optimization: remove uneccessary retpoline (no vcpus ) IBPB/IBRS optimization: remove uneccessary IBPB/IBRS ( novcpus , A->Idle->A) Microcode update, so that guest upgrade by itself

17.“Quote Placeholder”

18.