To be clear, I’m suspecting explicit throttling as described here: https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux/7/html/virtualization_tuning_and_optimization_guide/sect-virtualization_tuning_optimization_guide-blockio-techniques not impact from virtualization as such, though depending on the versions of software involved, the device emulation chosen can make a big difference, eg. virtio-scsi vs virtio-blk vs IDE. If one has Prometheus / Grafana set up to track throughput and iops per volume / attachment / VM, or enables the client-side admin socket, that sort of throttling can be very visually apparent. > On Oct 5, 2021, at 8:35 PM, Zakhar Kirpichenko <zakhar@xxxxxxxxx> wrote: > > Hi! > > The clients are KVM VMs, there's QEMU/libvirt impact for sure. I will test > with a baremetal client and see whether it performs much better. > > /Z > > > On Wed, 6 Oct 2021, 01:29 Anthony D'Atri, <anthony.datri@xxxxxxxxx> wrote: > >> The lead PG handling ops isn’t a factor, with RBD your volumes touch >> dozens / hundreds of PGs. But QD=1 and small block sizes are going to >> limit your throughput. >> >> What are your clients? Are they bare metal? Are they VMs? If they’re >> VMs, do you have QEMU/libvirt throttling in play? I see that a lot. >> >>> On Oct 5, 2021, at 2:06 PM, Zakhar Kirpichenko <zakhar@xxxxxxxxx> wrote: >>> >>> I'm not sure, fio might be showing some bogus values in the summary, I'll >>> check the readings again tomorrow. >>> >>> Another thing I noticed is that writes seem bandwidth-limited and don't >>> scale well with block size and/or number of threads. I.e. one clients >>> writes at about the same speed regardless of the benchmark settings. A >>> person on reddit, where I asked this question as well, suggested that in >> a >>> replicated pool writes and reads are handled by the primary PG, which >> would >>> explain this write bandwidth limit. >>> >>> /Z >>> >>> On Tue, 5 Oct 2021, 22:31 Christian Wuerdig, < >> christian.wuerdig@xxxxxxxxx> >>> wrote: >>> >>>> Maybe some info is missing but 7k write IOPs at 4k block size seem >> fairly >>>> decent (as you also state) - the bandwidth automatically follows from >> that >>>> so not sure what you're expecting? >>>> I am a bit puzzled though - by my math 7k IOPS at 4k should only be >>>> 27MiB/sec - not sure how the 120MiB/sec was achieved >>>> The read benchmark seems in line with 13k IOPS at 4k making around >>>> 52MiB/sec bandwidth which again is expected. >>>> >>>> >>>> On Wed, 6 Oct 2021 at 04:08, Zakhar Kirpichenko <zakhar@xxxxxxxxx> >> wrote: >>>> >>>>> Hi, >>>>> >>>>> I built a CEPH 16.2.x cluster with relatively fast and modern hardware, >>>>> and >>>>> its performance is kind of disappointing. I would very much appreciate >> an >>>>> advice and/or pointers :-) >>>>> >>>>> The hardware is 3 x Supermicro SSG-6029P nodes, each equipped with: >>>>> >>>>> 2 x Intel(R) Xeon(R) Gold 5220R CPUs >>>>> 384 GB RAM >>>>> 2 x boot drives >>>>> 2 x 1.6 TB Micron 7300 MTFDHBE1T6TDG drives (DB/WAL) >>>>> 2 x 6.4 TB Micron 7300 MTFDHBE6T4TDG drives (storage tier) >>>>> 9 x Toshiba MG06SCA10TE 9TB HDDs, write cache off (storage tier) >>>>> 2 x Intel XL710 NICs connected to a pair of 40/100GE switches >>>>> >>>>> All 3 nodes are running Ubuntu 20.04 LTS with the latest 5.4 kernel, >>>>> apparmor is disabled, energy-saving features are disabled. The network >>>>> between the CEPH nodes is 40G, CEPH access network is 40G, the average >>>>> latencies are < 0.15 ms. I've personally tested the network for >>>>> throughput, >>>>> latency and loss, and can tell that it's operating as expected and >> doesn't >>>>> exhibit any issues at idle or under load. >>>>> >>>>> The CEPH cluster is set up with 2 storage classes, NVME and HDD, with 2 >>>>> smaller NVME drives in each node used as DB/WAL and each HDD allocated >> . >>>>> ceph osd tree output: >>>>> >>>>> ID CLASS WEIGHT TYPE NAME STATUS REWEIGHT >> PRI-AFF >>>>> -1 288.37488 root default >>>>> -13 288.37488 datacenter ste >>>>> -14 288.37488 rack rack01 >>>>> -7 96.12495 host ceph01 >>>>> 0 hdd 9.38680 osd.0 up 1.00000 >> 1.00000 >>>>> 1 hdd 9.38680 osd.1 up 1.00000 >> 1.00000 >>>>> 2 hdd 9.38680 osd.2 up 1.00000 >> 1.00000 >>>>> 3 hdd 9.38680 osd.3 up 1.00000 >> 1.00000 >>>>> 4 hdd 9.38680 osd.4 up 1.00000 >> 1.00000 >>>>> 5 hdd 9.38680 osd.5 up 1.00000 >> 1.00000 >>>>> 6 hdd 9.38680 osd.6 up 1.00000 >> 1.00000 >>>>> 7 hdd 9.38680 osd.7 up 1.00000 >> 1.00000 >>>>> 8 hdd 9.38680 osd.8 up 1.00000 >> 1.00000 >>>>> 9 nvme 5.82190 osd.9 up 1.00000 >> 1.00000 >>>>> 10 nvme 5.82190 osd.10 up 1.00000 >> 1.00000 >>>>> -10 96.12495 host ceph02 >>>>> 11 hdd 9.38680 osd.11 up 1.00000 >> 1.00000 >>>>> 12 hdd 9.38680 osd.12 up 1.00000 >> 1.00000 >>>>> 13 hdd 9.38680 osd.13 up 1.00000 >> 1.00000 >>>>> 14 hdd 9.38680 osd.14 up 1.00000 >> 1.00000 >>>>> 15 hdd 9.38680 osd.15 up 1.00000 >> 1.00000 >>>>> 16 hdd 9.38680 osd.16 up 1.00000 >> 1.00000 >>>>> 17 hdd 9.38680 osd.17 up 1.00000 >> 1.00000 >>>>> 18 hdd 9.38680 osd.18 up 1.00000 >> 1.00000 >>>>> 19 hdd 9.38680 osd.19 up 1.00000 >> 1.00000 >>>>> 20 nvme 5.82190 osd.20 up 1.00000 >> 1.00000 >>>>> 21 nvme 5.82190 osd.21 up 1.00000 >> 1.00000 >>>>> -3 96.12495 host ceph03 >>>>> 22 hdd 9.38680 osd.22 up 1.00000 >> 1.00000 >>>>> 23 hdd 9.38680 osd.23 up 1.00000 >> 1.00000 >>>>> 24 hdd 9.38680 osd.24 up 1.00000 >> 1.00000 >>>>> 25 hdd 9.38680 osd.25 up 1.00000 >> 1.00000 >>>>> 26 hdd 9.38680 osd.26 up 1.00000 >> 1.00000 >>>>> 27 hdd 9.38680 osd.27 up 1.00000 >> 1.00000 >>>>> 28 hdd 9.38680 osd.28 up 1.00000 >> 1.00000 >>>>> 29 hdd 9.38680 osd.29 up 1.00000 >> 1.00000 >>>>> 30 hdd 9.38680 osd.30 up 1.00000 >> 1.00000 >>>>> 31 nvme 5.82190 osd.31 up 1.00000 >> 1.00000 >>>>> 32 nvme 5.82190 osd.32 up 1.00000 >> 1.00000 >>>>> >>>>> ceph df: >>>>> >>>>> --- RAW STORAGE --- >>>>> CLASS SIZE AVAIL USED RAW USED %RAW USED >>>>> hdd 253 TiB 241 TiB 13 TiB 13 TiB 5.00 >>>>> nvme 35 TiB 35 TiB 82 GiB 82 GiB 0.23 >>>>> TOTAL 288 TiB 276 TiB 13 TiB 13 TiB 4.42 >>>>> >>>>> --- POOLS --- >>>>> POOL ID PGS STORED OBJECTS USED %USED MAX >>>>> AVAIL >>>>> images 12 256 24 GiB 3.15k 73 GiB 0.03 76 >>>>> TiB >>>>> volumes 13 256 839 GiB 232.16k 2.5 TiB 1.07 76 >>>>> TiB >>>>> backups 14 256 31 GiB 8.56k 94 GiB 0.04 76 >>>>> TiB >>>>> vms 15 256 752 GiB 198.80k 2.2 TiB 0.96 76 >>>>> TiB >>>>> device_health_metrics 16 32 35 MiB 39 106 MiB 0 76 >>>>> TiB >>>>> volumes-nvme 17 256 28 GiB 7.21k 81 GiB 0.24 11 >>>>> TiB >>>>> ec-volumes-meta 18 256 27 KiB 4 92 KiB 0 76 >>>>> TiB >>>>> ec-volumes-data 19 256 8 KiB 1 12 KiB 0 152 >>>>> TiB >>>>> >>>>> Please disregard the ec-pools, as they're not currently in use. All >> other >>>>> pools are configured with min_size=2, size=3. All pools are bound to >> HDD >>>>> storage except for 'volumes-nvme', which is bound to NVME. The number >> of >>>>> PGs was increased recently, as with autoscaler I was getting a very >> uneven >>>>> PG distribution on devices and we're expecting to add 3 more nodes of >>>>> exactly the same configuration in the coming weeks. I have to emphasize >>>>> that I tested different PG numbers and they didn't have a noticeable >>>>> impact >>>>> on the cluster performance. >>>>> >>>>> The main issue is that this beautiful cluster isn't very fast. When I >> test >>>>> against the 'volumes' pool, residing on HDD storage class (HDDs with >>>>> DB/WAL >>>>> on NVME), I get unexpectedly low throughput numbers: >>>>> >>>>>> rados -p volumes bench 30 write --no-cleanup >>>>> ... >>>>> Total time run: 30.3078 >>>>> Total writes made: 3731 >>>>> Write size: 4194304 >>>>> Object size: 4194304 >>>>> Bandwidth (MB/sec): 492.415 >>>>> Stddev Bandwidth: 161.777 >>>>> Max bandwidth (MB/sec): 820 >>>>> Min bandwidth (MB/sec): 204 >>>>> Average IOPS: 123 >>>>> Stddev IOPS: 40.4442 >>>>> Max IOPS: 205 >>>>> Min IOPS: 51 >>>>> Average Latency(s): 0.129115 >>>>> Stddev Latency(s): 0.143881 >>>>> Max latency(s): 1.35669 >>>>> Min latency(s): 0.0228179 >>>>> >>>>>> rados -p volumes bench 30 seq --no-cleanup >>>>> ... >>>>> Total time run: 14.7272 >>>>> Total reads made: 3731 >>>>> Read size: 4194304 >>>>> Object size: 4194304 >>>>> Bandwidth (MB/sec): 1013.36 >>>>> Average IOPS: 253 >>>>> Stddev IOPS: 63.8709 >>>>> Max IOPS: 323 >>>>> Min IOPS: 91 >>>>> Average Latency(s): 0.0625202 >>>>> Max latency(s): 0.551629 >>>>> Min latency(s): 0.010683 >>>>> >>>>> On average, I get around 550 MB/s writes and 800 MB/s reads with 16 >>>>> threads >>>>> and 4MB blocks. The numbers don't look fantastic for this hardware, I >> can >>>>> actually push over 8 GB/s of throughput with fio, 16 threads and 4MB >>>>> blocks >>>>> from an RBD client (KVM Linux VM) connected over a low-latency 40G >>>>> network, >>>>> probably hitting some OSD caches there: >>>>> >>>>> READ: bw=8525MiB/s (8939MB/s), 58.8MiB/s-1009MiB/s >> (61.7MB/s-1058MB/s), >>>>> io=501GiB (538GB), run=60001-60153msec >>>>> Disk stats (read/write): >>>>> vdc: ios=48163/0, merge=6027/0, ticks=1400509/0, in_queue=1305092, >>>>> util=99.48% >>>>> >>>>> The issue manifests when the same client does something closer to >>>>> real-life >>>>> usage, like a single-thread write or read with 4KB blocks, as if using >> for >>>>> example ext4 file system: >>>>> >>>>>> fio --name=ttt --ioengine=posixaio --rw=write --bs=4k --numjobs=1 >>>>> --size=4g --iodepth=1 --runtime=60 --time_based --end_fsync=1 >>>>> ... >>>>> Run status group 0 (all jobs): >>>>> WRITE: bw=120MiB/s (126MB/s), 120MiB/s-120MiB/s (126MB/s-126MB/s), >>>>> io=7694MiB (8067MB), run=64079-64079msec >>>>> Disk stats (read/write): >>>>> vdc: ios=0/6985, merge=0/406, ticks=0/3062535, in_queue=3048216, >>>>> util=77.31% >>>>> >>>>>> fio --name=ttt --ioengine=posixaio --rw=read --bs=4k --numjobs=1 >>>>> --size=4g --iodepth=1 --runtime=60 --time_based --end_fsync=1 >>>>> ... >>>>> Run status group 0 (all jobs): >>>>> READ: bw=54.0MiB/s (56.7MB/s), 54.0MiB/s-54.0MiB/s >> (56.7MB/s-56.7MB/s), >>>>> io=3242MiB (3399MB), run=60001-60001msec >>>>> Disk stats (read/write): >>>>> vdc: ios=12952/3, merge=0/1, ticks=81706/1, in_queue=56336, >> util=99.13% >>>>> >>>>> And this is a total disaster: the IOPS look decent, but the bandwidth >> is >>>>> unexpectedly very very low. I just don't understand why a single RBD >>>>> client >>>>> writes at 120 MB/s (sometimes slower), and 50 MB/s reads look like a >> bad >>>>> joke ¯\_(ツ)_/¯ >>>>> >>>>> When I run these benchmarks, nothing seems to be overloaded, things >> like >>>>> CPU and network are barely utilized, OSD latencies don't show anything >>>>> unusual. Thus I am puzzled with these results, as in my opinion SAS >> HDDs >>>>> with DB/WAL on NVME drives should produce better I/O bandwidth, both >> for >>>>> writes and reads. I mean, I can easily get much better performance >> from a >>>>> single HDD shared over network via NFS or iSCSI. >>>>> >>>>> I am open to suggestions and would very much appreciate comments >> and/or an >>>>> advice on how to improve the cluster performance. >>>>> >>>>> Best regards, >>>>> Zakhar >>>>> _______________________________________________ >>>>> ceph-users mailing list -- ceph-users@xxxxxxx >>>>> To unsubscribe send an email to ceph-users-leave@xxxxxxx >>>>> >>>> >>> _______________________________________________ >>> ceph-users mailing list -- ceph-users@xxxxxxx >>> To unsubscribe send an email to ceph-users-leave@xxxxxxx >> >> > _______________________________________________ > ceph-users mailing list -- ceph-users@xxxxxxx > To unsubscribe send an email to ceph-users-leave@xxxxxxx _______________________________________________ ceph-users mailing list -- ceph-users@xxxxxxx To unsubscribe send an email to ceph-users-leave@xxxxxxx
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