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No commits in common. "41cd34ba4de367d591f09146cfd49cfc12203a4f" and "73c0834f85ad9ef2a17b99643b8c83c3915d1bd3" have entirely different histories.

8 changed files with 270 additions and 540 deletions

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@ -19,13 +19,6 @@
#
###############################################################################
import sys
from os import path
# Ensure current directory (/usr/share/pvc) is in the system path for Gunicorn
current_dir = path.dirname(path.abspath(__file__))
sys.path.append(current_dir)
import pvcapid.Daemon # noqa: F401, E402
import pvcapid.Daemon # noqa: F401
pvcapid.Daemon.entrypoint()

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@ -19,13 +19,15 @@
#
###############################################################################
import subprocess
from ssl import SSLContext, TLSVersion
from distutils.util import strtobool as dustrtobool
import daemon_lib.config as cfg
# Daemon version
version = "0.9.100~git-73c0834f"
version = "0.9.100"
# API version
API_VERSION = 1.0
@ -51,6 +53,7 @@ def strtobool(stringv):
# Configuration Parsing
##########################################################
# Get our configuration
config = cfg.get_configuration()
config["daemon_name"] = "pvcapid"
@ -58,16 +61,22 @@ config["daemon_version"] = version
##########################################################
# Flask App Creation for Gunicorn
# Entrypoint
##########################################################
def create_app():
"""
Create and return the Flask app and SSL context if necessary.
"""
# Import the Flask app from pvcapid.flaskapi after adjusting the path
import pvcapid.flaskapi as pvc_api
def entrypoint():
import pvcapid.flaskapi as pvc_api # noqa: E402
if config["api_ssl_enabled"]:
context = SSLContext()
context.minimum_version = TLSVersion.TLSv1
context.get_ca_certs()
context.load_cert_chain(
config["api_ssl_cert_file"], keyfile=config["api_ssl_key_file"]
)
else:
context = None
# Print our startup messages
print("")
@ -93,69 +102,9 @@ def create_app():
print("")
pvc_api.celery_startup()
return pvc_api.app
##########################################################
# Entrypoint
##########################################################
def entrypoint():
if config["debug"]:
app = create_app()
if config["api_ssl_enabled"]:
ssl_context = SSLContext()
ssl_context.minimum_version = TLSVersion.TLSv1
ssl_context.get_ca_certs()
ssl_context.load_cert_chain(
config["api_ssl_cert_file"], keyfile=config["api_ssl_key_file"]
)
else:
ssl_context = None
app.run(
pvc_api.app.run(
config["api_listen_address"],
config["api_listen_port"],
threaded=True,
ssl_context=ssl_context,
ssl_context=context,
)
else:
# Build the command to run Gunicorn
gunicorn_cmd = [
"gunicorn",
"--workers",
"1",
"--threads",
"8",
"--timeout",
"86400",
"--bind",
"{}:{}".format(config["api_listen_address"], config["api_listen_port"]),
"pvcapid.Daemon:create_app()",
"--log-level",
"info",
"--access-logfile",
"-",
"--error-logfile",
"-",
]
if config["api_ssl_enabled"]:
gunicorn_cmd += [
"--certfile",
config["api_ssl_cert_file"],
"--keyfile",
config["api_ssl_key_file"],
]
# Run Gunicorn
try:
subprocess.run(gunicorn_cmd)
except KeyboardInterrupt:
exit(0)
except Exception as e:
print(e)
exit(1)

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@ -5058,7 +5058,95 @@ class API_Storage_Ceph_Benchmark(Resource):
description: The PVC benchmark format of the results
benchmark_result:
type: object
description: A benchmark test result; format not documented due to complexity
description: A format 0 test result
properties:
test_name:
type: object
properties:
overall:
type: object
properties:
iosize:
type: string (integer)
description: The total size of the benchmark data
bandwidth:
type: string (integer)
description: The average bandwidth (KiB/s)
iops:
type: string (integer)
description: The average IOPS
runtime:
type: string (integer)
description: The total test time in milliseconds
latency:
type: object
properties:
min:
type: string (integer)
description: The minimum latency measurement
max:
type: string (integer)
description: The maximum latency measurement
mean:
type: string (float)
description: The mean latency measurement
stdev:
type: string (float)
description: The standard deviation of latency
bandwidth:
type: object
properties:
min:
type: string (integer)
description: The minimum bandwidth (KiB/s) measurement
max:
type: string (integer)
description: The maximum bandwidth (KiB/s) measurement
mean:
type: string (float)
description: The mean bandwidth (KiB/s) measurement
stdev:
type: string (float)
description: The standard deviation of bandwidth
numsamples:
type: string (integer)
description: The number of samples taken during the test
iops:
type: object
properties:
min:
type: string (integer)
description: The minimum IOPS measurement
max:
type: string (integer)
description: The maximum IOPS measurement
mean:
type: string (float)
description: The mean IOPS measurement
stdev:
type: string (float)
description: The standard deviation of IOPS
numsamples:
type: string (integer)
description: The number of samples taken during the test
cpu:
type: object
properties:
user:
type: string (float percentage)
description: The percentage of test time spent in user space
system:
type: string (float percentage)
description: The percentage of test time spent in system (kernel) space
ctxsw:
type: string (integer)
description: The number of context switches during the test
majfault:
type: string (integer)
description: The number of major page faults during the test
minfault:
type: string (integer)
description: The number of minor page faults during the test
"""
return list_benchmarks(config, reqargs.get("job", None))
@ -5069,10 +5157,6 @@ class API_Storage_Ceph_Benchmark(Resource):
"required": True,
"helptext": "A valid pool must be specified.",
},
{
"name": "name",
"required": False,
},
]
)
@Authenticator
@ -5088,11 +5172,6 @@ class API_Storage_Ceph_Benchmark(Resource):
type: string
required: true
description: The PVC storage pool to benchmark
- in: query
name: name
type: string
required: false
description: An optional override name for the job
responses:
200:
description: OK
@ -5110,10 +5189,7 @@ class API_Storage_Ceph_Benchmark(Resource):
}, 400
task = run_celery_task(
"storage.benchmark",
pool=reqargs.get("pool", None),
name=reqargs.get("name", None),
run_on="primary",
"storage.benchmark", pool=reqargs.get("pool", None), run_on="primary"
)
return (
{

View File

@ -3755,13 +3755,6 @@ def cli_storage_benchmark():
@click.command(name="run", short_help="Run a storage benchmark.")
@connection_req
@click.argument("pool")
@click.option(
"--name",
"name",
default=None,
show_default=False,
help="Use a custom name for the job",
)
@click.option(
"--wait/--no-wait",
"wait_flag",
@ -3773,14 +3766,12 @@ def cli_storage_benchmark():
@confirm_opt(
"Storage benchmarks take approximately 10 minutes to run and generate significant load on the cluster; they should be run sparingly. Continue"
)
def cli_storage_benchmark_run(pool, name, wait_flag):
def cli_storage_benchmark_run(pool, wait_flag):
"""
Run a storage benchmark on POOL in the background.
"""
retcode, retmsg = pvc.lib.storage.ceph_benchmark_run(
CLI_CONFIG, pool, name, wait_flag
)
retcode, retmsg = pvc.lib.storage.ceph_benchmark_run(CLI_CONFIG, pool, wait_flag)
if retcode and wait_flag:
retmsg = wait_for_celery_task(CLI_CONFIG, retmsg)

View File

@ -30,7 +30,6 @@ from requests_toolbelt.multipart.encoder import (
import pvc.lib.ansiprint as ansiprint
from pvc.lib.common import UploadProgressBar, call_api, get_wait_retdata
from pvc.cli.helpers import MAX_CONTENT_WIDTH
#
# Supplemental functions
@ -1725,17 +1724,15 @@ def format_list_snapshot(config, snapshot_list):
#
# Benchmark functions
#
def ceph_benchmark_run(config, pool, name, wait_flag):
def ceph_benchmark_run(config, pool, wait_flag):
"""
Run a storage benchmark against {pool}
API endpoint: POST /api/v1/storage/ceph/benchmark
API arguments: pool={pool}, name={name}
API arguments: pool={pool}
API schema: {message}
"""
params = {"pool": pool}
if name:
params["name"] = name
response = call_api(config, "post", "/storage/ceph/benchmark", params=params)
return get_wait_retdata(response, wait_flag)
@ -1807,7 +1804,7 @@ def get_benchmark_list_results(benchmark_format, benchmark_data):
benchmark_bandwidth, benchmark_iops = get_benchmark_list_results_legacy(
benchmark_data
)
elif benchmark_format == 1 or benchmark_format == 2:
elif benchmark_format == 1:
benchmark_bandwidth, benchmark_iops = get_benchmark_list_results_json(
benchmark_data
)
@ -2009,7 +2006,6 @@ def format_info_benchmark(config, benchmark_information):
benchmark_matrix = {
0: format_info_benchmark_legacy,
1: format_info_benchmark_json,
2: format_info_benchmark_json,
}
benchmark_version = benchmark_information[0]["test_format"]
@ -2344,15 +2340,12 @@ def format_info_benchmark_json(config, benchmark_information):
if benchmark_information["benchmark_result"] == "Running":
return "Benchmark test is still running."
benchmark_format = benchmark_information["test_format"]
benchmark_details = benchmark_information["benchmark_result"]
# Format a nice output; do this line-by-line then concat the elements at the end
ainformation = []
ainformation.append(
"{}Storage Benchmark details (format {}):{}".format(
ansiprint.bold(), benchmark_format, ansiprint.end()
)
"{}Storage Benchmark details:{}".format(ansiprint.bold(), ansiprint.end())
)
nice_test_name_map = {
@ -2400,7 +2393,7 @@ def format_info_benchmark_json(config, benchmark_information):
if element[1] != 0:
useful_latency_tree.append(element)
max_rows = 5
max_rows = 9
if len(useful_latency_tree) > 9:
max_rows = len(useful_latency_tree)
elif len(useful_latency_tree) < 9:
@ -2409,10 +2402,15 @@ def format_info_benchmark_json(config, benchmark_information):
# Format the static data
overall_label = [
"BW/s:",
"IOPS:",
"I/O:",
"Time:",
"Overall BW/s:",
"Overall IOPS:",
"Total I/O:",
"Runtime (s):",
"User CPU %:",
"System CPU %:",
"Ctx Switches:",
"Major Faults:",
"Minor Faults:",
]
while len(overall_label) < max_rows:
overall_label.append("")
@ -2421,149 +2419,68 @@ def format_info_benchmark_json(config, benchmark_information):
format_bytes_tohuman(int(job_details[io_class]["bw_bytes"])),
format_ops_tohuman(int(job_details[io_class]["iops"])),
format_bytes_tohuman(int(job_details[io_class]["io_bytes"])),
str(job_details["job_runtime"] / 1000) + "s",
job_details["job_runtime"] / 1000,
job_details["usr_cpu"],
job_details["sys_cpu"],
job_details["ctx"],
job_details["majf"],
job_details["minf"],
]
while len(overall_data) < max_rows:
overall_data.append("")
cpu_label = [
"Total:",
"User:",
"Sys:",
"OSD:",
"MON:",
]
while len(cpu_label) < max_rows:
cpu_label.append("")
cpu_data = [
(
benchmark_details[test]["avg_cpu_util_percent"]["total"]
if benchmark_format > 1
else "N/A"
),
round(job_details["usr_cpu"], 2),
round(job_details["sys_cpu"], 2),
(
benchmark_details[test]["avg_cpu_util_percent"]["ceph-osd"]
if benchmark_format > 1
else "N/A"
),
(
benchmark_details[test]["avg_cpu_util_percent"]["ceph-mon"]
if benchmark_format > 1
else "N/A"
),
]
while len(cpu_data) < max_rows:
cpu_data.append("")
memory_label = [
"Total:",
"OSD:",
"MON:",
]
while len(memory_label) < max_rows:
memory_label.append("")
memory_data = [
(
benchmark_details[test]["avg_memory_util_percent"]["total"]
if benchmark_format > 1
else "N/A"
),
(
benchmark_details[test]["avg_memory_util_percent"]["ceph-osd"]
if benchmark_format > 1
else "N/A"
),
(
benchmark_details[test]["avg_memory_util_percent"]["ceph-mon"]
if benchmark_format > 1
else "N/A"
),
]
while len(memory_data) < max_rows:
memory_data.append("")
network_label = [
"Total:",
"Sent:",
"Recv:",
]
while len(network_label) < max_rows:
network_label.append("")
network_data = [
(
format_bytes_tohuman(
int(benchmark_details[test]["avg_network_util_bps"]["total"])
)
if benchmark_format > 1
else "N/A"
),
(
format_bytes_tohuman(
int(benchmark_details[test]["avg_network_util_bps"]["sent"])
)
if benchmark_format > 1
else "N/A"
),
(
format_bytes_tohuman(
int(benchmark_details[test]["avg_network_util_bps"]["recv"])
)
if benchmark_format > 1
else "N/A"
),
]
while len(network_data) < max_rows:
network_data.append("")
bandwidth_label = [
"Min:",
"Max:",
"Mean:",
"StdDev:",
"Samples:",
"",
"",
"",
"",
]
while len(bandwidth_label) < max_rows:
bandwidth_label.append("")
bandwidth_data = [
format_bytes_tohuman(int(job_details[io_class]["bw_min"]) * 1024)
+ " / "
+ format_ops_tohuman(int(job_details[io_class]["iops_min"])),
format_bytes_tohuman(int(job_details[io_class]["bw_max"]) * 1024)
+ " / "
+ format_ops_tohuman(int(job_details[io_class]["iops_max"])),
format_bytes_tohuman(int(job_details[io_class]["bw_mean"]) * 1024)
+ " / "
+ format_ops_tohuman(int(job_details[io_class]["iops_mean"])),
format_bytes_tohuman(int(job_details[io_class]["bw_dev"]) * 1024)
+ " / "
+ format_ops_tohuman(int(job_details[io_class]["iops_stddev"])),
str(job_details[io_class]["bw_samples"])
+ " / "
+ str(job_details[io_class]["iops_samples"]),
format_bytes_tohuman(int(job_details[io_class]["bw_min"]) * 1024),
format_bytes_tohuman(int(job_details[io_class]["bw_max"]) * 1024),
format_bytes_tohuman(int(job_details[io_class]["bw_mean"]) * 1024),
format_bytes_tohuman(int(job_details[io_class]["bw_dev"]) * 1024),
job_details[io_class]["bw_samples"],
"",
"",
"",
"",
]
while len(bandwidth_data) < max_rows:
bandwidth_data.append("")
lat_label = [
"Min:",
"Max:",
"Mean:",
"StdDev:",
iops_data = [
format_ops_tohuman(int(job_details[io_class]["iops_min"])),
format_ops_tohuman(int(job_details[io_class]["iops_max"])),
format_ops_tohuman(int(job_details[io_class]["iops_mean"])),
format_ops_tohuman(int(job_details[io_class]["iops_stddev"])),
job_details[io_class]["iops_samples"],
"",
"",
"",
"",
]
while len(lat_label) < max_rows:
lat_label.append("")
while len(iops_data) < max_rows:
iops_data.append("")
lat_data = [
int(job_details[io_class]["lat_ns"]["min"]) / 1000,
int(job_details[io_class]["lat_ns"]["max"]) / 1000,
int(job_details[io_class]["lat_ns"]["mean"]) / 1000,
int(job_details[io_class]["lat_ns"]["stddev"]) / 1000,
"",
"",
"",
"",
"",
]
while len(lat_data) < max_rows:
lat_data.append("")
@ -2572,119 +2489,98 @@ def format_info_benchmark_json(config, benchmark_information):
lat_bucket_label = list()
lat_bucket_data = list()
for element in useful_latency_tree:
lat_bucket_label.append(element[0] + ":" if element[0] else "")
lat_bucket_data.append(round(float(element[1]), 2) if element[1] else "")
while len(lat_bucket_label) < max_rows:
lat_bucket_label.append("")
while len(lat_bucket_data) < max_rows:
lat_bucket_label.append("")
lat_bucket_label.append(element[0])
lat_bucket_data.append(element[1])
# Column default widths
overall_label_length = 5
overall_label_length = 0
overall_column_length = 0
cpu_label_length = 6
cpu_column_length = 0
memory_label_length = 6
memory_column_length = 0
network_label_length = 6
network_column_length = 6
bandwidth_label_length = 8
bandwidth_column_length = 0
latency_label_length = 7
latency_column_length = 0
bandwidth_label_length = 0
bandwidth_column_length = 11
iops_column_length = 4
latency_column_length = 12
latency_bucket_label_length = 0
latency_bucket_column_length = 0
# Column layout:
# Overall CPU Memory Network Bandwidth/IOPS Latency Percentiles
# --------- ----- ------- -------- -------------- -------- ---------------
# BW Total Total Total Min Min A
# IOPS Usr OSD Send Max Max B
# Time Sys MON Recv Mean Mean ...
# Size OSD StdDev StdDev Z
# MON Samples
# General Bandwidth IOPS Latency Percentiles
# --------- ---------- -------- -------- ---------------
# Size Min Min Min A
# BW Max Max Max B
# IOPS Mean Mean Mean ...
# Runtime StdDev StdDev StdDev Z
# UsrCPU Samples Samples
# SysCPU
# CtxSw
# MajFault
# MinFault
# Set column widths
for item in overall_label:
_item_length = len(str(item))
if _item_length > overall_label_length:
overall_label_length = _item_length
for item in overall_data:
_item_length = len(str(item))
if _item_length > overall_column_length:
overall_column_length = _item_length
for item in cpu_data:
_item_length = len(str(item))
if _item_length > cpu_column_length:
cpu_column_length = _item_length
test_name_length = len(nice_test_name_map[test])
if test_name_length > overall_label_length + overall_column_length:
_diff = test_name_length - (overall_label_length + overall_column_length)
overall_column_length += _diff
for item in memory_data:
for item in bandwidth_label:
_item_length = len(str(item))
if _item_length > memory_column_length:
memory_column_length = _item_length
for item in network_data:
_item_length = len(str(item))
if _item_length > network_column_length:
network_column_length = _item_length
if _item_length > bandwidth_label_length:
bandwidth_label_length = _item_length
for item in bandwidth_data:
_item_length = len(str(item))
if _item_length > bandwidth_column_length:
bandwidth_column_length = _item_length
for item in iops_data:
_item_length = len(str(item))
if _item_length > iops_column_length:
iops_column_length = _item_length
for item in lat_data:
_item_length = len(str(item))
if _item_length > latency_column_length:
latency_column_length = _item_length
for item in lat_bucket_data:
for item in lat_bucket_label:
_item_length = len(str(item))
if _item_length > latency_bucket_column_length:
latency_bucket_column_length = _item_length
if _item_length > latency_bucket_label_length:
latency_bucket_label_length = _item_length
# Top row (Headers)
ainformation.append(
"{bold}{overall_label: <{overall_label_length}} {header_fill}{end_bold}".format(
"{bold}\
{overall_label: <{overall_label_length}} \
{bandwidth_label: <{bandwidth_label_length}} \
{bandwidth: <{bandwidth_length}} \
{iops: <{iops_length}} \
{latency: <{latency_length}} \
{latency_bucket_label: <{latency_bucket_label_length}} \
{latency_bucket} \
{end_bold}".format(
bold=ansiprint.bold(),
end_bold=ansiprint.end(),
overall_label=nice_test_name_map[test],
overall_label_length=overall_label_length,
header_fill="-"
* (
(MAX_CONTENT_WIDTH if MAX_CONTENT_WIDTH <= 120 else 120)
- len(nice_test_name_map[test])
- 4
),
)
)
ainformation.append(
"{bold}\
{overall_label: <{overall_label_length}} \
{cpu_label: <{cpu_label_length}} \
{memory_label: <{memory_label_length}} \
{network_label: <{network_label_length}} \
{bandwidth_label: <{bandwidth_label_length}} \
{latency_label: <{latency_label_length}} \
{latency_bucket_label: <{latency_bucket_label_length}}\
{end_bold}".format(
bold=ansiprint.bold(),
end_bold=ansiprint.end(),
overall_label="Overall",
overall_label_length=overall_label_length + overall_column_length + 1,
cpu_label="CPU (%)",
cpu_label_length=cpu_label_length + cpu_column_length + 1,
memory_label="Memory (%)",
memory_label_length=memory_label_length + memory_column_length + 1,
network_label="Network (bps)",
network_label_length=network_label_length + network_column_length + 1,
bandwidth_label="Bandwidth / IOPS",
bandwidth_label_length=bandwidth_label_length
+ bandwidth_column_length
+ 1,
latency_label="Latency (μs)",
latency_label_length=latency_label_length + latency_column_length + 1,
latency_bucket_label="Buckets (μs/%)",
latency_bucket_label_length=latency_bucket_label_length
+ latency_bucket_column_length,
bandwidth_label="",
bandwidth_label_length=bandwidth_label_length,
bandwidth="Bandwidth/s",
bandwidth_length=bandwidth_column_length,
iops="IOPS",
iops_length=iops_column_length,
latency="Latency (μs)",
latency_length=latency_column_length,
latency_bucket_label="Latency Buckets (μs/%)",
latency_bucket_label_length=latency_bucket_label_length,
latency_bucket="",
)
)
@ -2692,19 +2588,13 @@ def format_info_benchmark_json(config, benchmark_information):
# Top row (Headers)
ainformation.append(
"{bold}\
{overall_label: <{overall_label_length}} \
{overall_label: >{overall_label_length}} \
{overall: <{overall_length}} \
{cpu_label: <{cpu_label_length}} \
{cpu: <{cpu_length}} \
{memory_label: <{memory_label_length}} \
{memory: <{memory_length}} \
{network_label: <{network_label_length}} \
{network: <{network_length}} \
{bandwidth_label: <{bandwidth_label_length}} \
{bandwidth_label: >{bandwidth_label_length}} \
{bandwidth: <{bandwidth_length}} \
{latency_label: <{latency_label_length}} \
{iops: <{iops_length}} \
{latency: <{latency_length}} \
{latency_bucket_label: <{latency_bucket_label_length}} \
{latency_bucket_label: >{latency_bucket_label_length}} \
{latency_bucket} \
{end_bold}".format(
bold="",
@ -2713,24 +2603,12 @@ def format_info_benchmark_json(config, benchmark_information):
overall_label_length=overall_label_length,
overall=overall_data[idx],
overall_length=overall_column_length,
cpu_label=cpu_label[idx],
cpu_label_length=cpu_label_length,
cpu=cpu_data[idx],
cpu_length=cpu_column_length,
memory_label=memory_label[idx],
memory_label_length=memory_label_length,
memory=memory_data[idx],
memory_length=memory_column_length,
network_label=network_label[idx],
network_label_length=network_label_length,
network=network_data[idx],
network_length=network_column_length,
bandwidth_label=bandwidth_label[idx],
bandwidth_label_length=bandwidth_label_length,
bandwidth=bandwidth_data[idx],
bandwidth_length=bandwidth_column_length,
latency_label=lat_label[idx],
latency_label_length=latency_label_length,
iops=iops_data[idx],
iops_length=iops_column_length,
latency=lat_data[idx],
latency_length=latency_column_length,
latency_bucket_label=lat_bucket_label[idx],
@ -2739,4 +2617,4 @@ def format_info_benchmark_json(config, benchmark_information):
)
)
return "\n".join(ainformation) + "\n"
return "\n".join(ainformation)

View File

@ -19,34 +19,31 @@
#
###############################################################################
import os
import psutil
import psycopg2
import psycopg2.extras
import subprocess
from datetime import datetime
from json import loads, dumps
from time import sleep
from daemon_lib.celery import start, fail, log_info, update, finish
import daemon_lib.common as pvc_common
import daemon_lib.ceph as pvc_ceph
# Define the current test format
TEST_FORMAT = 2
TEST_FORMAT = 1
# We run a total of 8 tests, to give a generalized idea of performance on the cluster:
# 1. A sequential read test of 64GB with a 4M block size
# 2. A sequential write test of 64GB with a 4M block size
# 3. A random read test of 64GB with a 4M block size
# 4. A random write test of 64GB with a 4M block size
# 5. A random read test of 64GB with a 256k block size
# 6. A random write test of 64GB with a 256k block size
# 7. A random read test of 64GB with a 4k block size
# 8. A random write test of 64GB with a 4k block size
# 1. A sequential read test of 8GB with a 4M block size
# 2. A sequential write test of 8GB with a 4M block size
# 3. A random read test of 8GB with a 4M block size
# 4. A random write test of 8GB with a 4M block size
# 5. A random read test of 8GB with a 256k block size
# 6. A random write test of 8GB with a 256k block size
# 7. A random read test of 8GB with a 4k block size
# 8. A random write test of 8GB with a 4k block size
# Taken together, these 8 results should give a very good indication of the overall storage performance
# for a variety of workloads.
test_matrix = {
@ -103,7 +100,7 @@ test_matrix = {
# Specify the benchmark volume name and size
benchmark_volume_name = "pvcbenchmark"
benchmark_volume_size = "64G"
benchmark_volume_size = "8G"
#
@ -229,7 +226,7 @@ def cleanup_benchmark_volume(
def run_benchmark_job(
config, test, pool, job_name=None, db_conn=None, db_cur=None, zkhandler=None
test, pool, job_name=None, db_conn=None, db_cur=None, zkhandler=None
):
test_spec = test_matrix[test]
log_info(None, f"Running test '{test}'")
@ -259,165 +256,31 @@ def run_benchmark_job(
)
log_info(None, "Running fio job: {}".format(" ".join(fio_cmd.split())))
# Run the fio command manually instead of using our run_os_command wrapper
# This will help us gather statistics about this node while it's running
process = subprocess.Popen(
fio_cmd.split(),
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
)
# Wait 15 seconds for the test to start
log_info(None, "Waiting 15 seconds for test resource stabilization")
sleep(15)
# Set up function to get process CPU utilization by name
def get_cpu_utilization_by_name(process_name):
cpu_usage = 0
for proc in psutil.process_iter(["name", "cpu_percent"]):
if proc.info["name"] == process_name:
cpu_usage += proc.info["cpu_percent"]
return cpu_usage
# Set up function to get process memory utilization by name
def get_memory_utilization_by_name(process_name):
memory_usage = 0
for proc in psutil.process_iter(["name", "memory_percent"]):
if proc.info["name"] == process_name:
memory_usage += proc.info["memory_percent"]
return memory_usage
# Set up function to get network traffic utilization in bps
def get_network_traffic_bps(interface, duration=1):
# Get initial network counters
net_io_start = psutil.net_io_counters(pernic=True)
if interface not in net_io_start:
return None, None
stats_start = net_io_start[interface]
bytes_sent_start = stats_start.bytes_sent
bytes_recv_start = stats_start.bytes_recv
# Wait for the specified duration
sleep(duration)
# Get final network counters
net_io_end = psutil.net_io_counters(pernic=True)
stats_end = net_io_end[interface]
bytes_sent_end = stats_end.bytes_sent
bytes_recv_end = stats_end.bytes_recv
# Calculate bytes per second
bytes_sent_per_sec = (bytes_sent_end - bytes_sent_start) / duration
bytes_recv_per_sec = (bytes_recv_end - bytes_recv_start) / duration
# Convert to bits per second (bps)
bits_sent_per_sec = bytes_sent_per_sec * 8
bits_recv_per_sec = bytes_recv_per_sec * 8
bits_total_per_sec = bits_sent_per_sec + bits_recv_per_sec
return bits_sent_per_sec, bits_recv_per_sec, bits_total_per_sec
log_info(None, f"Starting system resource polling for test '{test}'")
storage_interface = config["storage_dev"]
total_cpus = psutil.cpu_count(logical=True)
ticks = 1
osd_cpu_utilization = 0
osd_memory_utilization = 0
mon_cpu_utilization = 0
mon_memory_utilization = 0
total_cpu_utilization = 0
total_memory_utilization = 0
storage_sent_bps = 0
storage_recv_bps = 0
storage_total_bps = 0
while process.poll() is None:
# Do collection of statistics like network bandwidth and cpu utilization
current_osd_cpu_utilization = get_cpu_utilization_by_name("ceph-osd")
current_osd_memory_utilization = get_memory_utilization_by_name("ceph-osd")
current_mon_cpu_utilization = get_cpu_utilization_by_name("ceph-mon")
current_mon_memory_utilization = get_memory_utilization_by_name("ceph-mon")
current_total_cpu_utilization = psutil.cpu_percent(interval=1)
current_total_memory_utilization = psutil.virtual_memory().percent
(
current_storage_sent_bps,
current_storage_recv_bps,
current_storage_total_bps,
) = get_network_traffic_bps(storage_interface)
# Recheck if the process is done yet; if it's not, we add the values and increase the ticks
# This helps ensure that if the process finishes earlier than the longer polls above,
# this particular tick isn't counted which can skew the average
if process.poll() is None:
osd_cpu_utilization += current_osd_cpu_utilization
osd_memory_utilization += current_osd_memory_utilization
mon_cpu_utilization += current_mon_cpu_utilization
mon_memory_utilization += current_mon_memory_utilization
total_cpu_utilization += current_total_cpu_utilization
total_memory_utilization += current_total_memory_utilization
storage_sent_bps += current_storage_sent_bps
storage_recv_bps += current_storage_recv_bps
storage_total_bps += current_storage_total_bps
ticks += 1
# Get the 1-minute load average and CPU utilization, which covers the test duration
load1, _, _ = os.getloadavg()
load1 = round(load1, 2)
# Calculate the average CPU utilization values over the runtime
# Divide the OSD and MON CPU utilization by the total number of CPU cores, because
# the total is divided this way
avg_osd_cpu_utilization = round(osd_cpu_utilization / ticks / total_cpus, 2)
avg_osd_memory_utilization = round(osd_memory_utilization / ticks, 2)
avg_mon_cpu_utilization = round(mon_cpu_utilization / ticks / total_cpus, 2)
avg_mon_memory_utilization = round(mon_memory_utilization / ticks, 2)
avg_total_cpu_utilization = round(total_cpu_utilization / ticks, 2)
avg_total_memory_utilization = round(total_memory_utilization / ticks, 2)
avg_storage_sent_bps = round(storage_sent_bps / ticks, 2)
avg_storage_recv_bps = round(storage_recv_bps / ticks, 2)
avg_storage_total_bps = round(storage_total_bps / ticks, 2)
stdout, stderr = process.communicate()
retcode = process.returncode
resource_data = {
"avg_cpu_util_percent": {
"total": avg_total_cpu_utilization,
"ceph-mon": avg_mon_cpu_utilization,
"ceph-osd": avg_osd_cpu_utilization,
},
"avg_memory_util_percent": {
"total": avg_total_memory_utilization,
"ceph-mon": avg_mon_memory_utilization,
"ceph-osd": avg_osd_memory_utilization,
},
"avg_network_util_bps": {
"sent": avg_storage_sent_bps,
"recv": avg_storage_recv_bps,
"total": avg_storage_total_bps,
},
}
retcode, stdout, stderr = pvc_common.run_os_command(fio_cmd)
try:
jstdout = loads(stdout)
if retcode:
raise
except Exception:
return None, None
cleanup(
job_name,
db_conn=db_conn,
db_cur=db_cur,
zkhandler=zkhandler,
)
fail(
None,
f"Failed to run fio test '{test}': {stderr}",
)
return resource_data, jstdout
return jstdout
def worker_run_benchmark(zkhandler, celery, config, pool, name):
def worker_run_benchmark(zkhandler, celery, config, pool):
# Phase 0 - connect to databases
if not name:
cur_time = datetime.now().isoformat(timespec="seconds")
cur_primary = zkhandler.read("base.config.primary_node")
job_name = f"{cur_time}_{cur_primary}"
else:
job_name = name
current_stage = 0
total_stages = 13
@ -495,8 +358,7 @@ def worker_run_benchmark(zkhandler, celery, config, pool, name):
total=total_stages,
)
resource_data, fio_data = run_benchmark_job(
config,
results[test] = run_benchmark_job(
test,
pool,
job_name=job_name,
@ -504,25 +366,6 @@ def worker_run_benchmark(zkhandler, celery, config, pool, name):
db_cur=db_cur,
zkhandler=zkhandler,
)
if resource_data is None or fio_data is None:
cleanup_benchmark_volume(
pool,
job_name=job_name,
db_conn=db_conn,
db_cur=db_cur,
zkhandler=zkhandler,
)
cleanup(
job_name,
db_conn=db_conn,
db_cur=db_cur,
zkhandler=zkhandler,
)
fail(
None,
f"Failed to run fio test '{test}'",
)
results[test] = {**resource_data, **fio_data}
# Phase 3 - cleanup
current_stage += 1

2
debian/control vendored
View File

@ -32,7 +32,7 @@ Description: Parallel Virtual Cluster worker daemon
Package: pvc-daemon-api
Architecture: all
Depends: systemd, pvc-daemon-common, gunicorn, python3-gunicorn, python3-yaml, python3-flask, python3-flask-restful, python3-celery, python3-distutils, python3-redis, python3-lxml, python3-flask-migrate
Depends: systemd, pvc-daemon-common, python3-yaml, python3-flask, python3-flask-restful, python3-celery, python3-distutils, python3-redis, python3-lxml, python3-flask-migrate
Description: Parallel Virtual Cluster API daemon
A KVM/Zookeeper/Ceph-based VM and private cloud manager
.

View File

@ -96,12 +96,12 @@ def create_vm(
@celery.task(name="storage.benchmark", bind=True, routing_key="run_on")
def storage_benchmark(self, pool=None, name=None, run_on="primary"):
def storage_benchmark(self, pool=None, run_on="primary"):
@ZKConnection(config)
def run_storage_benchmark(zkhandler, self, pool, name):
return worker_run_benchmark(zkhandler, self, config, pool, name)
def run_storage_benchmark(zkhandler, self, pool):
return worker_run_benchmark(zkhandler, self, config, pool)
return run_storage_benchmark(self, pool, name)
return run_storage_benchmark(self, pool)
@celery.task(name="cluster.autobackup", bind=True, routing_key="run_on")