On Thu, Aug 28, 2014 at 04:38:09PM +0200, Benoît Canet wrote: > I collected some items of a cloud provider wishlist regarding I/O accouting. > > In a cloud I/O accouting can have 3 purpose: billing, helping the customers > and doing metrology to help the cloud provider seeks hidden costs. > > I'll cover the two former topic in this mail because they are the most important > business wize. > > 1) prefered place to collect billing IO accounting data: > -------------------------------------------------------- > For billing purpose the collected data must be as close as possible to what the > customer would see by using iostats in his vm. > > The first conclusion we can draw is that the choice of collecting IO accouting > data used for billing in the block devices models is right. I agree. When statistics are collected at lower layers it becomes are for the end user to understand numbers that include hidden costs for image formats, network protocols, etc. > 2) what to do with occurences of rare events: > --------------------------------------------- > > Another point is that QEMU developpers agree that they don't know which policy > to apply to some I/O accounting events. > Must QEMU discard invalid I/O write IO or account them as done ? > Must QEMU count a failed read I/O as done ? > > When discusting this with a cloud provider the following appears: these decisions > are really specific to each cloud provider and QEMU should not implement them. > The right thing to do is to add accouting counters to collect these events. > > Moreover these rare events are precious troubleshooting data so it's an additional > reason not to toss them. Sounds good, network interface statistics also include error counters. > 3) list of block I/O accouting metrics wished for billing and helping the customers > ----------------------------------------------------------------------------------- > > Basic I/O accouting data will end up making the customers bills. > Extra I/O accouting informations would be a precious help for the cloud provider > to implement a monitoring panel like Amazon Cloudwatch. One thing to be aware of is that counters inside QEMU cannot be trusted. If a malicious guest can overwrite memory in QEMU then the counters can be manipulated. For most purposes this should be okay. Just be aware that evil guests could manipulate their counters if a security hole is found in QEMU. > Here is the list of counters and statitics I would like to help implement in QEMU. > > This is the most important part of the mail and the one I would like the community > review the most. > > Once this list is settled I would proceed to implement the required infrastructure > in QEMU before using it in the device models. > > /* volume of data transfered by the IOs */ > read_bytes > write_bytes > > /* operation count */ > read_ios > write_ios > flush_ios > > /* how many invalid IOs the guest submit */ > invalid_read_ios > invalid_write_ios > invalid_flush_ios > > /* how many io error happened */ > read_ios_error > write_ios_error > flush_ios_error > > /* account the time passed doing IOs */ > total_read_time > total_write_time > total_flush_time > > /* since when the volume is iddle */ > qvolume_iddleness_time ? > > /* the following would compute latecies for slices of 1 seconds then toss the > * result and start a new slice. A weighted sumation of the instant latencies > * could help to implement this. > */ > 1s_read_average_latency > 1s_write_average_latency > 1s_flush_average_latency > > /* the former three numbers could be used to further compute a 1 minute slice value */ > 1m_read_average_latency > 1m_write_average_latency > 1m_flush_average_latency > > /* the former three numbers could be used to further compute a 1 hours slice value */ > 1h_read_average_latency > 1h_write_average_latency > 1h_flush_average_latency > > /* 1 second average number of requests in flight */ > 1s_read_queue_depth > 1s_write_queue_depth > > /* 1 minute average number of requests in flight */ > 1m_read_queue_depth > 1m_write_queue_depth > > /* 1 hours average number of requests in flight */ > 1h_read_queue_depth > 1h_write_queue_depth I think libvirt captures similar data. At least virt-manager displays graphs with similar data (maybe for CPU, memory, or network instead of disk). > 4) Making this happen > ------------------------- > > Outscale want to make these IO stat happen and gave me the go to do whatever > grunt is required to do so. > That said we could collaborate on some part of the work. Seems like a nice improvement to the query-blockstats available today. CCing libvirt for management stack ideas. Stefan
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