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Currently scx_layered outputs statistics periodically as info! logs. The format of this is largely unstructured and mostly suitable for running scx_layered interactively (e.g. observing its behavior on the command line or via logs after the fact). In order to run scx_layered at larger scale, it's desireable to have statistics output in some format that is amenable to being ingested into monitoring databases (e.g. Prometheseus). This allows collection of stats across many machines. This commit adds a command line flag (-o) that outputs statistics to stdout in OpenMetrics format instead of the normal log mechanism. OpenMetrics has a public format specification (https://github.com/OpenObservability/OpenMetrics) and is in use by many projects. The library for producing OpenMetrics metrics is lightweight but does induce some changes. Primarily, metrics need to be pre-registered (see OpenMetricsStats::new()). Without -o, the output looks as before, for example: ``` 19:39:54 [INFO] CPUs: online/possible=52/52 nr_cores=26 19:39:54 [INFO] Layered Scheduler Attached 19:39:56 [INFO] tot= 9912 local=76.71 open_idle= 0.00 affn_viol= 2.63 tctx_err=0 proc=21ms 19:39:56 [INFO] busy= 1.3 util= 65.2 load= 263.4 fallback_cpu= 1 19:39:56 [INFO] batch : util/frac= 49.7/ 76.3 load/frac= 252.0: 95.7 tasks= 458 19:39:56 [INFO] tot= 2842 local=45.04 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00 19:39:56 [INFO] cpus= 2 [ 0, 2] 04000001 00000000 19:39:56 [INFO] immediate: util/frac= 0.0/ 0.0 load/frac= 0.0: 0.0 tasks= 0 19:39:56 [INFO] tot= 0 local= 0.00 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00 19:39:56 [INFO] cpus= 50 [ 0, 50] fbfffffe 000fffff 19:39:56 [INFO] normal : util/frac= 15.4/ 23.7 load/frac= 11.4: 4.3 tasks= 556 19:39:56 [INFO] tot= 7070 local=89.43 open_idle= 0.00 preempt= 0.00 affn_viol= 3.69 19:39:56 [INFO] cpus= 50 [ 0, 50] fbfffffe 000fffff 19:39:58 [INFO] tot= 7091 local=84.91 open_idle= 0.00 affn_viol= 2.64 tctx_err=0 proc=21ms 19:39:58 [INFO] busy= 0.6 util= 31.2 load= 107.1 fallback_cpu= 1 19:39:58 [INFO] batch : util/frac= 18.3/ 58.5 load/frac= 93.9: 87.7 tasks= 589 19:39:58 [INFO] tot= 2011 local=60.67 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00 19:39:58 [INFO] cpus= 2 [ 2, 2] 04000001 00000000 19:39:58 [INFO] immediate: util/frac= 0.0/ 0.0 load/frac= 0.0: 0.0 tasks= 0 19:39:58 [INFO] tot= 0 local= 0.00 open_idle= 0.00 preempt= 0.00 affn_viol= 0.00 19:39:58 [INFO] cpus= 50 [ 50, 50] fbfffffe 000fffff 19:39:58 [INFO] normal : util/frac= 13.0/ 41.5 load/frac= 13.2: 12.3 tasks= 650 19:39:58 [INFO] tot= 5080 local=94.51 open_idle= 0.00 preempt= 0.00 affn_viol= 3.68 19:39:58 [INFO] cpus= 50 [ 50, 50] fbfffffe 000fffff ^C19:39:59 [INFO] EXIT: BPF scheduler unregistered ``` With -o passed, the output is in OpenMetrics format: ``` 19:40:08 [INFO] CPUs: online/possible=52/52 nr_cores=26 19:40:08 [INFO] Layered Scheduler Attached # HELP total Total scheduling events in the period. # TYPE total gauge total 8489 # HELP local % that got scheduled directly into an idle CPU. # TYPE local gauge local 86.45305689716104 # HELP open_idle % of open layer tasks scheduled into occupied idle CPUs. # TYPE open_idle gauge open_idle 0.0 # HELP affn_viol % which violated configured policies due to CPU affinity restrictions. # TYPE affn_viol gauge affn_viol 2.332430203793144 # HELP tctx_err Failures to free task contexts. # TYPE tctx_err gauge tctx_err 0 # HELP proc_ms CPU time this binary has consumed during the period. # TYPE proc_ms gauge proc_ms 20 # HELP busy CPU busy % (100% means all CPUs were fully occupied). # TYPE busy gauge busy 0.5294061026085283 # HELP util CPU utilization % (100% means one CPU was fully occupied). # TYPE util gauge util 27.37195512782239 # HELP load Sum of weight * duty_cycle for all tasks. # TYPE load gauge load 81.55024768702126 # HELP layer_util CPU utilization of the layer (100% means one CPU was fully occupied). # TYPE layer_util gauge layer_util{layer_name="immediate"} 0.0 layer_util{layer_name="normal"} 19.340849995024997 layer_util{layer_name="batch"} 8.031105132797393 # HELP layer_util_frac Fraction of total CPU utilization consumed by the layer. # TYPE layer_util_frac gauge layer_util_frac{layer_name="batch"} 29.34063385422595 layer_util_frac{layer_name="immediate"} 0.0 layer_util_frac{layer_name="normal"} 70.65936614577405 # HELP layer_load Sum of weight * duty_cycle for tasks in the layer. # TYPE layer_load gauge layer_load{layer_name="immediate"} 0.0 layer_load{layer_name="normal"} 11.14363313258934 layer_load{layer_name="batch"} 70.40661455443191 # HELP layer_load_frac Fraction of total load consumed by the layer. # TYPE layer_load_frac gauge layer_load_frac{layer_name="normal"} 13.664744680306903 layer_load_frac{layer_name="immediate"} 0.0 layer_load_frac{layer_name="batch"} 86.33525531969309 # HELP layer_tasks Number of tasks in the layer. # TYPE layer_tasks gauge layer_tasks{layer_name="immediate"} 0 layer_tasks{layer_name="normal"} 490 layer_tasks{layer_name="batch"} 343 # HELP layer_total Number of scheduling events in the layer. # TYPE layer_total gauge layer_total{layer_name="normal"} 6711 layer_total{layer_name="batch"} 1778 layer_total{layer_name="immediate"} 0 # HELP layer_local % of scheduling events directly into an idle CPU. # TYPE layer_local gauge layer_local{layer_name="batch"} 69.79752530933632 layer_local{layer_name="immediate"} 0.0 layer_local{layer_name="normal"} 90.86574281031143 # HELP layer_open_idle % of scheduling events into idle CPUs occupied by other layers. # TYPE layer_open_idle gauge layer_open_idle{layer_name="immediate"} 0.0 layer_open_idle{layer_name="batch"} 0.0 layer_open_idle{layer_name="normal"} 0.0 # HELP layer_preempt % of scheduling events that preempted other tasks. # # TYPE layer_preempt gauge layer_preempt{layer_name="normal"} 0.0 layer_preempt{layer_name="batch"} 0.0 layer_preempt{layer_name="immediate"} 0.0 # HELP layer_affn_viol % of scheduling events that violated configured policies due to CPU affinity restrictions. # TYPE layer_affn_viol gauge layer_affn_viol{layer_name="normal"} 2.950379973178364 layer_affn_viol{layer_name="batch"} 0.0 layer_affn_viol{layer_name="immediate"} 0.0 # HELP layer_cur_nr_cpus Current # of CPUs assigned to the layer. # TYPE layer_cur_nr_cpus gauge layer_cur_nr_cpus{layer_name="normal"} 50 layer_cur_nr_cpus{layer_name="batch"} 2 layer_cur_nr_cpus{layer_name="immediate"} 50 # HELP layer_min_nr_cpus Minimum # of CPUs assigned to the layer. # TYPE layer_min_nr_cpus gauge layer_min_nr_cpus{layer_name="normal"} 0 layer_min_nr_cpus{layer_name="batch"} 0 layer_min_nr_cpus{layer_name="immediate"} 0 # HELP layer_max_nr_cpus Maximum # of CPUs assigned to the layer. # TYPE layer_max_nr_cpus gauge layer_max_nr_cpus{layer_name="immediate"} 50 layer_max_nr_cpus{layer_name="normal"} 50 layer_max_nr_cpus{layer_name="batch"} 2 # EOF ^C19:40:11 [INFO] EXIT: BPF scheduler unregistered ``` Signed-off-by: Dan Schatzberg <schatzberg.dan@gmail.com> |
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| .. | ||
| c | ||
| include | ||
| rust | ||
| meson.build | ||
| README.md | ||
| sync-to-kernel.sh | ||
SCHED_EXT SCHEDULERS
Introduction
This directory contains the repo's schedulers.
Some of these schedulers are simply examples of different types of schedulers that can be built using sched_ext. They can be loaded and used to schedule on your system, but their primary purpose is to illustrate how various features of sched_ext can be used.
Other schedulers are actually performant, production-ready schedulers. That is, for the correct workload and with the correct tuning, they may be deployed in a production environment with acceptable or possibly even improved performance. Some of the examples could be improved to become production schedulers.
Please see the following README files for details on each of the various types of schedulers:
- rust describes all of the schedulers with rust user space components. All of these schedulers are production ready.
- c describes all of the schedulers with C user space components. All of these schedulers are production ready.
Note on syncing
Note that there is a sync-to-kernel.sh script in this directory. This is used to sync any changes to the specific schedulers with the Linux kernel tree. If you've made any changes to a scheduler in please use the script to synchronize with the sched_ext Linux kernel tree:
$ ./sync-to-kernel.sh /path/to/kernel/tree