Hi, 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. 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. 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. 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 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. Best regards Benoît
