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Commit 2992c78d authored by Anas Mokhtari's avatar Anas Mokhtari
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Some experimental results from months 2 and 3/2024

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%% Cell type:markdown id:6475cecd-382c-4741-abc1-83e6aab9a174 tags:
# (3) Analysis of the calibration results
%% Cell type:code id:f8fae69d-11f4-4ac7-8c77-ed85399053fb tags:
``` python
%load_ext autoreload
%autoreload 2
```
%% Cell type:code id:bfe02192-3f93-46f1-b65d-8b7b5011fd34 tags:
``` python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
```
%% Cell type:markdown id:bfabd98a-5bd6-4c51-ae47-cad9686ce949 tags:
# Import experience results from csv file
%% Cell type:code id:754cd2f0-0911-4d6a-9d7a-ed71142b0b22 tags:
``` python
datetime = '2024-02-07_22-29-18'#'2024-01-31_01-20-41' #'2024-02-01_11-25-06'#'2024-01-29_11-03-35' #'2024-01-20_11-39-36'
datetime = '2024-02-19_15-06-41' #'2024-02-07_22-29-18'#'2024-01-31_01-20-41' #'2024-02-01_11-25-06'#'2024-01-29_11-03-35' #'2024-01-20_11-39-36'
# SUPPRIMER high après avoir résolu le prb de séparation entre les charges hautes et faibles.
results_file = 'Results/' + datetime + '_calibration.csv'#'_high.csv'#2024-01-20_11-39-36.csv')#sample.csv')#2024-01-17_00-26-18.csv')
results = pd.read_csv(results_file)
results
```
%% Cell type:markdown id:86b82186-557d-4968-a923-db898d54ab11 tags:
# Analyze energy consumption of all scenarios
## Processing
%% Cell type:code id:0fa22347-a75f-47ea-b4ce-502ab0376937 tags:
``` python
#print(results[results['Run number'] == max(results['Run number'])])
#image_sizes = results['Image size (px)'].unique()
#filters = results['Filter'].unique()
#rates = results['Req/s'].unique()
loader = results.loc[0, 'Load generator']
load_controller = 'Load type' if loader == 'LOCUST' else 'Req/s' if loader == 'LIMBO' else None
neutral_to_load = 'Req/s' if loader == 'LOCUST' else 'Users' if loader == 'LIMBO' else None
percentile = 1
experience = pd.DataFrame()
#experience = experience[experience['Dyn. Energy/Req'] <= experience['Dyn. Energy/Req'].quantile(0.95)]
#experience.columns = ['Image size (px)', 'Filter', 'Req/s', 'hhh', 'Dyn. Energy/Req']
#experience = results.drop_duplicates(subset=['Image size (px)', 'Filter', 'Req/s'], keep='first')[['Image size (px)', 'Filter', 'Req/s']]
experience = results.groupby(['Image size (px)', 'Filter', load_controller], group_keys=False).apply(lambda x : x[x['Dyn. Energy/Req']<=x['Dyn. Energy/Req'].quantile(percentile)]).reset_index()
#print(experience['Dyn. Energy/Req'].describe())
#print(experience.loc[:, experience.columns != 'command'].to_string())
experience = experience.groupby(['Image size (px)', 'Filter', load_controller]).agg({neutral_to_load: 'mean', 'Users': 'mean', 'Run number': 'count', 'Dyn. Energy/Req': ['min', 'max', 'mean', 'median']}).reset_index()# if loader == 'LOCUST' else experience.groupby(['Image size (px)', 'Filter', load_controller]).agg({'Users': 'mean', 'Run number': 'count', 'Dyn. Energy/Req': ['min', 'max', 'mean', 'median']}).reset_index() if loader == 'LIMBO' else None
experience.columns = ['Image size (px)', 'Filter', load_controller, neutral_to_load, 'Users', 'Tot. runs', 'Min J/Req', 'Max J/Req', 'Mean J/Req', 'Median J/Req'] if loader == 'LOCUST' else ['Image size (px)', 'Filter', load_controller, 'Users', 'Users', 'Tot. runs', 'Min J/Req', 'Max J/Req', 'Mean J/Req', 'Median J/Req'] if loader == 'LIMBO' else None
experience.insert(0, 'Load generator', [loader for x in range(len(experience))])
print(experience)
#print(experience.drop_duplicates(subset=['Image size (px)', 'Filter'], keep='first'))
```
%% Cell type:markdown id:10a386d8-7f54-4559-870a-e72c3388a653 tags:
## Saving results
%% Cell type:code id:914a8d89-c436-433a-8b9f-996bc3f21261 tags:
``` python
import utils as utils
# Save experience variable:
utils.save_variable(experience, 'experience', datetime)
#print(experience)
#test = utils.load_variable('experience', datetime)
#print(test)
```
%% Cell type:markdown id:93e34b6b-3471-4630-b19e-0c9e4ca16f84 tags:
# (4) Go to "energy_scheduler.ipynb" to find the configuration for the next period !
%% Cell type:markdown id:55aae441-9d85-4fdf-930e-218863b942d9 tags:
# Plotting
%% Cell type:code id:de6a57ec-9fa9-4790-96f7-57eddf62edde tags:
``` python
#plot_data = experience.drop_duplicates(subset=['Image size (px)', 'Filter'], keep='last')
plot_data = experience
#print(plot_data)#['Max J/Req'])
loads = plot_data[load_controller].unique()
#print(loads)
for i in loads:
data = plot_data[plot_data[load_controller] == i].reset_index(drop=True)
#print(data.index.to_list())
plt.figure(figsize=(8, 6))
#plt.errorbar(data.index.to_list(), data['Median J/Req'], [data['Median J/Req'] - data['Min J/Req'], data['Max J/Req'] - data['Median J/Req']], fmt='.', label='Erreur', color='y')
plt.scatter(data.index.to_list(), data['Max J/Req'], label='Max', color='r', marker='^')
plt.scatter(data.index.to_list(), data['Min J/Req'], label='Min', color='g', marker='v')
plt.scatter(data.index.to_list(), data['Median J/Req'], label='Median', color='b', marker='x')#, s=100
#plt.yscale('log')
plt.xlabel('Configuration')
plt.ylabel('Energy/Req (J)')
plt.title('Energy consumption of $\\mathbf{' + str(i) + '}$ ' + load_controller)
plt.legend()
plt.show()
'''
plt.figure(figsize=(8, 6))
plot_title = 'Comparison between loads: | '
for i in range(len(loads)):
plt.scatter(plot_data[plot_data[load_controller] == loads[i]].reset_index(drop=True).index.to_list(), plot_data.loc[plot_data[load_controller] == loads[i], 'Median J/Req'], label=loads[i])#, color='r', marker='^')
plt.bar(plot_data[plot_data[load_controller] == loads[i]].reset_index(drop=True).index.to_list(), plot_data.loc[plot_data[load_controller] == loads[i], 'Median J/Req'], label=loads[i])#, color='r', marker='^')
parameter1 = plot_data.loc[plot_data[load_controller] == loads[i], 'Image size (px)']
parameter2 = plot_data.loc[plot_data[load_controller] == loads[i], 'Filter']
configs = []
for x, y in zip(parameter1, parameter2):
configs.append(str(x)+'px x '+str(y))
plt.xticks(plot_data[plot_data[load_controller] == loads[i]].reset_index(drop=True).index.to_list(), configs, rotation=90, fontsize=8)
plot_title = plot_title + loads[i] + ' | '
plt.xlabel('Configuration')
plt.xlabel('Configuration (Image size x Filter)')
plt.ylabel('Median Energy/Req (J)')
plt.title(plot_title)
plt.legend()
plt.show()
'''
# Show the impact of parameters on energy consumption:
plt.figure(figsize=(8, 6))
#plot_title = 'Comparison between loads: | '
for i in range(len(loads)):
plt.bar(plot_data[plot_data[load_controller] == loads[i]].reset_index(drop=True).index.to_list(), plot_data.loc[plot_data[load_controller] == loads[i], 'Median J/Req'], label='Energy (J)')#, color='r', marker='^')
parameter1 = plot_data.loc[plot_data[load_controller] == loads[i], 'Image size (px)']
parameter2 = plot_data.loc[plot_data[load_controller] == loads[i], 'Filter']
configs = []
for x, y in zip(parameter1, parameter2):
configs.append(str(x)+'px x '+str(y))
plt.xticks(plot_data[plot_data[load_controller] == loads[i]].reset_index(drop=True).index.to_list(), configs, rotation=90)#, fontsize=8)
#plot_title = plot_title + loads[i] + ' | '
parameter1 = plot_data[plot_data[load_controller] == loads[i]].reset_index(drop=True).index.to_list()
parameter2 = plot_data.loc[plot_data[load_controller] == loads[i], 'Median J/Req']
for x, y in zip(parameter1, parameter2):
plt.text(x, y+.005, f"{y:.3f}", ha='center', size=7, rotation=35)
plt.xlabel('Configuration (Image size x Filter)')
plt.ylabel('Median Energy/Req (J)')
#plt.title(plot_title)
plt.tight_layout()
plt.legend()
file_name = datetime + '_Energy_per_Request' + '.pdf'
print("Saving file", file_name)
plt.savefig('Results/'+file_name)
plt.show()
print(plot_data)
```
%% Cell type:markdown id:92f37c0a-6626-4cf8-980f-a24ad51e62e6 tags:
# (more analyzes) energy consumption evolution of each scenraio
## Processing
%% Cell type:code id:2e430a90-f25e-4be1-aee1-c0037e36b950 tags:
``` python
experience = pd.DataFrame()
#experience = results.drop_duplicates(subset=['Image size (px)', 'Filter', 'Req/s'], keep='first')[['Image size (px)', 'Filter', 'Req/s']]
experience = results.groupby(['Image size (px)', 'Filter', load_controller], group_keys=False).apply(lambda x : x[x['Dyn. Energy/Req']<=x['Dyn. Energy/Req'].quantile(percentile)]).reset_index()
experience = experience.sort_values(by=['Image size (px)', 'Filter', load_controller])
#pd.set_option('display.max_rows', None)
#pd.set_option('display.max_columns', None)
#pd.set_option('display.width', None)
scenarios = experience.groupby(['Image size (px)', 'Filter', load_controller])
#print(experience.loc[:, experience.columns != 'command'].to_string())
for name, data in scenarios:
#print(name)
plt.plot(data['Run number'], data['Dyn. Energy (Joules)'], label='Energy', color='b') #, marker='o')
plt.xlabel('Run number')
plt.ylabel('Energy consumption (J)')
plt.title('Energy consumption of ' + str(data['Image size (px)'].unique()) + ' px and Filter ' + str(data['Filter'].unique()) + ' for ' + str(data[load_controller].unique()) + ' ' + load_controller + ' (' + str("{:.2f}".format(plot_data[neutral_to_load].unique()[0])) + neutral_to_load + ')')
plt.legend()
plt.show()
#experience.columns = ['Image size (px)', 'Filter', 'Req/s', 'Tot. runs', 'Min J/Req', 'Max J/Req', 'Mean J/Req']
#print(experience)
```
%% Cell type:code id:d7d4e911-88e5-491a-9ae9-852f01a7ef19 tags:
``` python
```
......
%% Cell type:code id:21ac32e0-527f-44ec-8b59-392bbafec565 tags:
``` python
%load_ext autoreload
%autoreload 2
```
%% Cell type:markdown id:7adf7241-6f08-442d-b3f3-230e81f3dae2 tags:
# (1) K3s deployment on G5K
%% Cell type:markdown id:8b15377a-4eaf-4509-a4b2-5215b1e1d166 tags:
## G5K nodes reservation
%% Cell type:code id:6a98cea2-263e-49c6-82df-d489907b074e tags:
``` python
from modules.Platform import Platform
walltime = "06:00:00"
walltime = "05:30:00"
platform = Platform()
roles = platform.reserve("ecotype", walltime=walltime, nodes=2) #nodes=3 when using the HTTP-Load-Genertor
```
%% Cell type:markdown id:6c353d4b-9814-4bd5-b515-cd135ea4b306 tags:
## K3s deployment
%% Cell type:code id:4bd79e8f-bdb8-4e81-8cad-6ba354bd7b11 tags:
``` python
platform.deploy()
```
%% Cell type:markdown id:68e208b8-376e-4298-b6fc-33f824f990c4 tags:
# (2) Calibration
%% Cell type:code id:c8023b18-f9d6-4e90-b67f-6cbcce156648 tags:
``` python
from modules.Calibration import Calibration
calibrator = Calibration(roles)
loader = 'LOCUST'
image_sizes = [32, 128, 512, 1024]
image_sizes = [144, 360, 480, 720, 1080] # sizes = heights of the image
filters = [0, 1, 2, 3]
duration = 60
duration = 30
runs = 10
load_types_number = 1 # Choose between 1 (High) and 3 (High, Medium and Low) load(s).
load_types_number = 1 # Choose either 1 (High) or 3 (High, Medium and Low) load(s).
if calibrator.server_capacity(image_sizes, filters, force=False) == -1:
calibrator.read_capacity('ecotype-43.nantes.grid5000.fr') # A previous calibration on ecotype server
calibrator.read_capacity('ecotype-36.nantes.grid5000.fr') # A previous calibration on ecotype server
calibrator.configure("calibration", loader, runs, duration, load_types_number, image_sizes, filters)
```
%% Cell type:code id:8f76e833-7434-472e-a285-41682ca53915 tags:
``` python
datetime = calibrator.run()
print("Use\033[1m", datetime, "\033[0m as a datetime value for the other scripts.")
```
%% Cell type:markdown id:e2d766c7-a8a2-4959-9408-e3ea486675ad tags:
# (3) Go to "Analysis.ipynb" to analyze the calibration results !
%% Cell type:markdown id:c5c42325-3b30-4f24-98b3-be07c20bc291 tags:
# (5) Evaluation
%% Cell type:markdown id:b1073c81-57f6-4572-981e-a18703733443 tags:
## Fast (basic) evaluation
%% Cell type:code id:aab4f513-ca30-4531-95e0-e084ae2d6561 tags:
``` python
"""datetime = '2024-01-31_01-20-41'#'2024-02-01_11-25-06'#'2024-01-20_11-39-36'
evaluator = Calibration(roles)
loader = 'LOCUST'
# duration if defined in the "next_next_configuration" variable.
runs = 1
next_configuration = utils.load_variable('next_configuration', datetime)
print(next_configuration)
evaluator.configure("evaluation", loader, runs, next_configuration=next_configuration)
evaluator.run()"""
```
%% Cell type:markdown id:037326af-39c5-4aaf-bff8-945c1c86f0a7 tags:
## Creating scenarios
%% Cell type:code id:f3f6cc4e-180a-489a-8b8d-2852c3c03266 tags:
``` python
from modules.Scenarios import Scenarios
from modules.Scheduler import Scheduler
duration = 60
load_type = 'High'
max_power_green = 100
max_power_green = 20
datetime = '2024-02-07_22-29-18'#'2024-02-01_11-25-06'#'2024-01-31_01-20-41'
total_req_rate = 200
datetime = '2024-02-19_15-06-41'#'2024-02-01_11-25-06'#'2024-01-31_01-20-41'
total_req_rate = 120
sch = Scheduler()
sch.load(datetime)
sch.get_load_types()
percentages = [100, 50, 0] # Les pourcentages doivent être suffisamment (ex.) élevés pour que tous les scénarios soient présents. Sinon, le 0 est aussi possible.
percentages = [100, 50] # Les pourcentages doivent être suffisamment élevés (ex. > 25) pour que tous les scénarios soient présents. Le 0 est possible.
ratios = Scenarios.get_ratios(percentages)
scenarios = Scenarios(datetime)
scenarios.next_configurations(percentages, total_req_rate, max_power_green, duration, load_type)
#sch.next_step(duration, power_green[case][str(ratio)], 0, 0, total_req_rate)
#baseline = sch.get_next_configuration(load_type=load_type)
#rrr = scenarios.get_ratios(percentages)
#scenarios.get_best_green_powers(total_req_rate, rrr, max_power_green, duration, load_type="High")
scenarios.next_configurations_v2(percentages, total_req_rate, max_power_green, duration, load_type, green_power=13)
```
%% Cell type:code id:6c9042cf-37d6-4640-a065-8ca92218a97c tags:
``` python
scenarios.plot(percentages, duration, total_req_rate, load_type=load_type)
scenarios.plot_v2(percentages, duration, total_req_rate, load_type=load_type)
```
%% Cell type:markdown id:63fd43d7-5a59-4802-b5b0-b7d3fbc0cfcf tags:
## Evaluating
%% Cell type:code id:6d28225b-60d0-4e79-8c32-14c1feb15ba9 tags:
``` python
import utils as utils
from modules.Calibration import Calibration
import pandas as pd
runs = 1
loader = "LOCUST"
energy = {}
evaluator = Calibration(roles)
for case in range(1, 5):
'''for case in range(1, 5):
energy[case] = {}
for ratio in ratios:
next_configuration = scenarios.get_next_configurations()[case][str(ratio)]
if next_configuration['Tot. J (based on median)'][0] == 0:
energy[case][str(ratio)] = 0
print("Case", case, "not applicable for the", ratio, "ratio.")
continue
evaluator.configure("evaluation", loader, runs, next_configuration=next_configuration)
date = evaluator.run()
file = 'Results/' + date + '_evaluation.csv'
results = pd.read_csv(file)
energy[case][str(ratio)] = results['Energy (Joules)'][0]
'''
for ratio in ratios:
next_configuration = scenarios.get_next_configurations()[str(ratio)]
if next_configuration['Tot. J (based on median)'][0] == 0:
energy[str(ratio)] = 0
#print("Case", case, "not applicable for the", ratio, "ratio.")
continue
evaluator.configure("evaluation", loader, runs, next_configuration=next_configuration)
date = evaluator.run()
file = 'Results/' + date + '_evaluation.csv'
results = pd.read_csv(file)
energy[str(ratio)] = results['Energy (Joules)'][0]
```
%% Cell type:code id:d0bb82b2-7b15-4d53-90c3-642da8a28b69 tags:
``` python
scenarios.plot(percentages, duration, total_req_rate, load_type, energy, case_number=None)
scenarios.plot_v4(percentages, duration, total_req_rate, load_type, energy, date)
scenarios.plot_v4(percentages, duration, total_req_rate, load_type, energy, date, annotation=True)
```
%% Cell type:markdown id:61e25929-fef9-4d16-aef5-48212630f514 tags:
# K3s undeployment
%% Cell type:code id:9890c579-1e7f-41b7-84b5-3b5ba94bcd6c tags:
``` python
platform.undeploy()
```
%% Cell type:markdown id:bb29cea1-6957-4832-aab4-3ab1a9800c88 tags:
# Stop G5K nodes reservation
%% Cell type:code id:71336f78-7e6c-4ee9-98bf-8c3fda5d8147 tags:
``` python
platform.release()
```
%% Cell type:markdown id:5ed65fd0-39a6-4219-a5c0-a48e8ce4fdc5 tags:
# Notes (to ignore)
%% Cell type:code id:0b554bbc-a099-4f58-8800-dad448893181 tags:
``` python
'''
# Adresse du serveur Prometheus
prometheus_pod = en.run_command(command="kubectl get pods -n monitoring -o custom-columns=NAME:.metadata.name | grep prometheus-server", roles=roles["kube"])
prometheus_pod = prometheus_pod[0].stdout
prometheus_address=en.run_command(command="kubectl get pod " + prometheus_pod + " -n monitoring -o=jsonpath='{.status.podIP}'", roles=roles["kube"])
#print(prometheus_address[0].stdout)
prometheus_address = prometheus_address[0].stdout
prometheus_url = "http://" + prometheus_address + ":9090"
#response = en.run_command(command='curl ' + prometheus_url + '/api/v1/query --data-urlencode \'query=100 * (1 - avg(rate(node_cpu_seconds_total{mode="idle"}[15m])))\' | jq -r \'.data.result[].value[1]\'', roles=roles["kube"])
response = en.run_command(command='curl ' + prometheus_url + '"/api/v1/query_range" \
--data-urlencode \'query=sum(rate(node_cpu_seconds_total{mode="idle"}[2m])) by (instance)\' \
--data-urlencode \'start=\'"$(date -d \'2 minutes ago\' -u +%s)" \
--data-urlencode \'end=\'"$(date -u +%s)" \
--data-urlencode \'step=15s\' \
', roles=roles["kube"])
# Afficher le résultat
print('valeur: ', response[0].stdout)
'''
```
......
Load generator,Run number,Users,Total Req,runtime (s),Req/s,Energy (Joules),Power (W),Energy/Req,command
LOCUST,1,200,12000,60,200.6065484960735,3548.22,59.13699999999999,0.295685,locust --headless --processes -1 --run-time 60 --users 200 --spawn-rate 200 --host http://ecotype-6.nantes.grid5000.fr:80 --csv 2024-02-16_22-49-25_px_200rps_60s_1.csv
Count,Message,Traceback,Nodes
Method,Name,Error,Occurrences
Type,Name,Request Count,Failure Count,Median Response Time,Average Response Time,Min Response Time,Max Response Time,Average Content Size,Requests/s,Failures/s,50%,66%,75%,80%,90%,95%,98%,99%,99.9%,99.99%,100%
GET,/fibo/1024/2/jpeg,12000,0,420.0,396.07205495307153,105.46320499997819,670.7341589990392,77798.92758333334,200.6065484960735,0.0,420,490,530,550,570,590,600,610,660,670,670
,Aggregated,12000,0,420.0,396.07205495307153,105.46320499997819,670.7341589990392,77798.92758333334,200.6065484960735,0.0,420,490,530,550,570,590,600,610,660,670,670
Timestamp,User Count,Type,Name,Requests/s,Failures/s,50%,66%,75%,80%,90%,95%,98%,99%,99.9%,99.99%,100%,Total Request Count,Total Failure Count,Total Median Response Time,Total Average Response Time,Total Min Response Time,Total Max Response Time,Total Average Content Size
1708120173,0,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120174,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120175,5,,Aggregated,0.000000,0.000000,580,590,590,610,610,610,610,610,610,610,610,5,0,580.0,553.7707279996539,489.9666330002219,612.6897449994431,92428.4
1708120176,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120177,5,,Aggregated,0.000000,0.000000,560,570,570,600,600,600,600,600,600,600,600,5,0,560.0,568.5245509994274,538.8147869998647,604.5541989988124,57275.0
1708120178,5,,Aggregated,0.000000,0.000000,570,580,600,600,610,610,610,610,610,610,610,10,0,570.0,577.0329235996542,538.8147869998647,610.5997930008016,71218.4
1708120179,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120180,5,,Aggregated,0.000000,0.000000,570,590,590,590,590,590,590,590,590,590,590,5,0,570.0,576.2752742000885,563.0347930000426,592.031270998632,87212.2
1708120181,5,,Aggregated,0.000000,0.000000,570,570,580,590,590,590,590,590,590,590,590,10,0,570.0,567.0762212999762,518.3639650003897,592.031270998632,89345.2
1708120182,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120183,5,,Aggregated,0.000000,0.000000,570,590,590,600,600,600,600,600,600,600,600,5,0,570.0,576.335069599736,558.926376999807,596.0017279994645,88524.4 11708120184,5,,Aggregated,0.000000,0.000000,570,590,590,590,600,600,600,600,600,600,600,10,0,570.0,572.9255772997931,552.7465199993458,596.0017279994645,78320.7
1708120185,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120186,5,,Aggregated,0.000000,0.000000,570,590,590,590,590,590,590,590,590,590,590,5,0,570.0,567.7623334002419,541.8614570007776,591.9553570001881,73115.4
1708120187,5,,Aggregated,0.000000,0.000000,570,570,590,590,590,590,590,590,590,590,590,10,0,570.0,569.4803448002858,541.8614570007776,591.9553570001881,80605.5
1708120188,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120189,5,,Aggregated,0.000000,0.000000,580,590,590,600,600,600,600,600,600,600,600,5,0,580.0,579.0460668002197,563.4168180004053,602.5795780005865,79568.6
1708120190,5,,Aggregated,0.000000,0.000000,590,590,590,600,600,600,600,600,600,600,600,10,0,580.0,580.5009161000271,562.1372679997876,602.5795780005865,75775.7
1708120191,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120192,5,,Aggregated,0.000000,0.000000,560,560,560,580,580,580,580,580,580,580,580,5,0,560.0,563.7557549998746,558.6181069993472,576.4937429994461,62986.2
1708120193,5,,Aggregated,0.000000,0.000000,560,560,570,570,580,580,580,580,580,580,580,10,0,560.0,564.4926205997763,556.5589889993134,576.4937429994461,83443.1
1708120194,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120195,5,,Aggregated,0.000000,0.000000,560,560,560,570,570,570,570,570,570,570,570,5,0,560.0,559.8970454000664,554.032059999372,565.1744219994725,87907.6
1708120196,5,,Aggregated,0.000000,0.000000,560,560,570,570,570,570,570,570,570,570,570,10,0,560.0,562.2103204001178,554.032059999372,574.7719860009965,91180.8
1708120197,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120198,5,,Aggregated,0.000000,0.000000,570,570,570,570,570,570,570,570,570,570,570,5,0,570.0,563.7143579995609,553.583096998409,573.7170580014208,58589.2
1708120199,5,,Aggregated,0.000000,0.000000,570,570,570,570,580,580,580,580,580,580,580,10,0,560.0,565.0306048997663,553.583096998409,576.1521929998707,64574.2
1708120200,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120201,5,,Aggregated,0.000000,0.000000,580,580,580,590,590,590,590,590,590,590,590,5,0,580.0,572.373186600089,544.22822000015,588.6322909991577,106182.2
1708120202,5,,Aggregated,0.000000,0.000000,570,580,580,590,590,590,590,590,590,590,590,10,0,560.0,568.8287418000982,544.22822000015,588.6322909991577,92364.6
1708120203,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120204,5,,Aggregated,0.000000,0.000000,570,580,580,600,600,600,600,600,600,600,600,5,0,570.0,574.8827834002441,557.930077000492,596.4966030005598,48962.4
1708120205,5,,Aggregated,0.000000,0.000000,570,570,570,580,600,600,600,600,600,600,600,10,0,570.0,570.3227028001493,555.2512399990519,596.4966030005598,63220.3
1708120206,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120207,5,,Aggregated,0.000000,0.000000,570,580,580,600,600,600,600,600,600,600,600,5,0,570.0,576.0515198002395,560.0653519995831,603.1831229993259,96479.4
1708120208,5,,Aggregated,0.000000,0.000000,560,570,570,580,600,600,600,600,600,600,600,10,0,560.0,569.0959306997684,554.3402210005297,603.1831229993259,90004.5
1708120209,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120210,5,,Aggregated,0.000000,0.000000,560,560,560,580,580,580,580,580,580,580,580,5,0,560.0,560.8852048004337,551.1072230001446,576.9864809990395,77900.8
1708120211,5,,Aggregated,0.000000,0.000000,560,560,570,580,580,580,580,580,580,580,580,10,0,560.0,563.2472415003576,551.1072230001446,581.8822809997073,74581.1
1708120212,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120213,5,,Aggregated,0.000000,0.000000,590,590,590,590,590,590,590,590,590,590,590,5,0,590.0,582.7032922006765,569.4496930009336,594.2142310013878,86111.6
1708120214,5,,Aggregated,0.000000,0.000000,570,570,590,590,590,590,590,590,590,590,590,10,0,560.0,567.300522500409,549.3949550000252,594.2142310013878,71835.6
1708120215,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120216,5,,Aggregated,0.000000,0.000000,570,570,570,590,590,590,590,590,590,590,590,5,0,570.0,571.7755551999289,559.5650819996081,589.9269970013847,87989.8
1708120217,5,,Aggregated,0.000000,0.000000,570,570,580,590,590,590,590,590,590,590,590,10,0,570.0,570.839884599809,547.1039220010425,589.9269970013847,80748.5
1708120218,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120219,5,,Aggregated,0.000000,0.000000,570,580,580,580,580,580,580,580,580,580,580,5,0,570.0,572.9315515996859,553.2028369998443,584.6706339998491,54736.4
1708120220,5,,Aggregated,0.000000,0.000000,570,580,580,590,600,600,600,600,600,600,600,10,0,570.0,572.6651738996225,553.2028369998443,601.2834079992899,56520.2
1708120221,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120222,5,,Aggregated,0.000000,0.000000,560,570,570,570,570,570,570,570,570,570,570,5,0,560.0,560.8173879998503,548.0072399986966,572.2560350004642,61429.6
1708120223,5,,Aggregated,0.000000,0.000000,560,570,570,570,600,600,600,600,600,600,600,10,0,550.0,562.1945765000419,544.9035000001459,599.7300829985761,70606.4
1708120224,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120225,5,,Aggregated,0.000000,0.000000,560,570,570,580,580,580,580,580,580,580,580,5,0,560.0,562.634098199851,555.7404680002946,575.6650509993051,86790.4
1708120226,5,,Aggregated,0.000000,0.000000,570,570,570,580,580,580,580,580,580,580,580,10,0,570.0,566.4804902000469,555.7404680002946,582.1729529998265,72486.1
1708120227,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120228,5,,Aggregated,0.000000,0.000000,560,560,560,570,570,570,570,570,570,570,570,5,0,560.0,559.2471883999679,555.6741229993349,568.5172929988767,74986.6
1708120229,5,,Aggregated,0.000000,0.000000,560,570,570,570,580,580,580,580,580,580,580,10,0,560.0,562.9579559001286,555.6741229993349,575.9914990012476,79135.8
1708120230,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120231,5,,Aggregated,0.000000,0.000000,570,570,570,580,580,580,580,580,580,580,580,5,0,570.0,568.7462031997711,562.8860249998979,582.8558409994002,70920.2
1708120232,5,,Aggregated,0.000000,0.000000,570,570,580,580,610,610,610,610,610,610,610,10,0,570.0,572.3848313999042,555.3743780001241,605.8580460012308,76812.2
1708120233,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
,0.0,0,0,0
0,0
0,0,0,0.0,0,0,0
0,0,0,0.0,0,0,0
0,0.0,0,0,0
420.0,396.7630579789209,105.46320499997819,670.7341589990392,77839.66148936171
1708120224,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,9430,0,420.0,396.7830666517349,105.46320499997819,670.7341589990392,77829.80646871687
1708120225,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,10000,0,420.0,396.41873254838197,105.46320499997819,670.7341589990392,77831.1751
1708120226,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,10000,0,420.0,396.41873254838197,105.46320499997819,670.7341589990392,77831.1751
1708120227,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,10030,0,420.0,396.43693230616407,105.46320499997819,670.7341589990392,77819.059222333
1708120228,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,10600,0,420.0,396.34512886602346,105.46320499997819,670.7341589990392,77832.1637735849
1708120229,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,10600,0,420.0,396.34512886602346,105.46320499997819,670.7341589990392,77832.1637735849
1708120230,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,10630,0,420.0,396.3384418564296,105.46320499997819,670.7341589990392,77804.0619943556
1708120231,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,11200,0,420.0,396.18159305436285,105.46320499997819,670.7341589990392,77839.07419642857
1708120232,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,11200,0,420.0,396.18159305436285,105.46320499997819,670.7341589990392,77839.07419642857
1708120233,200,,Aggregated,200.000000,0.000000,420,490,530,550,570,590,600,610,660,670,670,11230,0,420.0,396.16620630586476,105.46320499997819,670.7341589990392,77809.5108637578
Load generator,Run number,Users,Total Req,runtime (s),Req/s,Energy (Joules),Power (W),Energy/Req,command
LOCUST,1,200,11989,60,199.82226770033975,4634.943000000001,77.24905000000003,0.3865996329969139,locust --headless --processes -1 --run-time 60 --users 200 --spawn-rate 200 --host http://ecotype-6.nantes.grid5000.fr:80 --csv 2024-02-16_22-50-59_px_200rps_60s_1.csv
Count,Message,Traceback,Nodes
Method,Name,Error,Occurrences
Type,Name,Request Count,Failure Count,Median Response Time,Average Response Time,Min Response Time,Max Response Time,Average Content Size,Requests/s,Failures/s,50%,66%,75%,80%,90%,95%,98%,99%,99.9%,99.99%,100%
GET,/fibo/1024/3/jpeg,11989,0,560.0,531.7639748755527,151.52441800091765,843.5607709998294,81205.74268079072,199.82226770033978,0.0,560,670,710,740,770,790,800,810,830,840,840
,Aggregated,11989,0,560.0,531.7639748755527,151.52441800091765,843.5607709998294,81205.74268079072,199.82226770033978,0.0,560,670,710,740,770,790,800,810,830,840,840
Timestamp,User Count,Type,Name,Requests/s,Failures/s,50%,66%,75%,80%,90%,95%,98%,99%,99.9%,99.99%,100%,Total Request Count,Total Failure Count,Total Median Response Time,Total Average Response Time,Total Min Response Time,Total Max Response Time,Total Average Content Size
1708120266,0,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120267,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120268,5,,Aggregated,0.000000,0.000000,760,790,790,800,800,800,800,800,800,800,800,5,0,760.0,762.4200059995928,729.7167249998893,800.626143000045,106494.2
1708120269,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120270,5,,Aggregated,0.000000,0.000000,770,790,790,810,810,810,810,810,810,810,810,5,0,770.0,778.7189204005699,760.4529020009068,806.3684700009617,77182.2
1708120271,5,,Aggregated,0.000000,0.000000,770,770,790,800,810,810,810,810,810,810,810,10,0,760.0,772.85310640018,747.849061001034,806.3684700009617,73085.8
1708120272,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120273,5,,Aggregated,0.000000,0.000000,770,810,810,810,810,810,810,810,810,810,810,5,0,770.0,778.3550896001543,746.279830000276,810.7725219997519,94575.8
1708120274,5,,Aggregated,0.000000,0.000000,770,770,790,810,810,810,810,810,810,810,810,10,0,760.0,764.6110652998686,716.9141519989353,810.7725219997519,87460.4
1708120275,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120276,5,,Aggregated,0.000000,0.000000,760,780,780,780,780,780,780,780,780,780,780,5,0,760.0,759.6908095998515,737.9965889995219,784.4656990000658,83914.2 1708120277,5,,Aggregated,0.000000,0.000000,770,770,770,780,780,780,780,780,780,780,780,10,0,770.0,766.462350999609,746.7662310009473,784.072856999046,76809.3
1708120278,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120279,5,,Aggregated,0.000000,0.000000,760,760,760,800,800,800,800,800,800,800,800,5,0,760.0,761.7374131994438,739.1939539993473,801.0725690000982,77453.6
1708120280,5,,Aggregated,0.000000,0.000000,780,780,780,790,800,800,800,800,800,800,800,10,0,760.0,768.5729844997695,739.1939539993473,801.0725690000982,67397.5
1708120281,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120282,5,,Aggregated,0.000000,0.000000,780,790,790,810,810,810,810,810,810,810,810,5,0,780.0,772.9030534006597,729.2536500008282,808.6974650013872,70946.2
1708120283,5,,Aggregated,0.000000,0.000000,790,790,790,800,810,810,810,810,810,810,810,10,0,780.0,776.780536800652,729.2536500008282,808.6974650013872,74357.8
1708120284,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120285,5,,Aggregated,0.000000,0.000000,760,790,790,810,810,810,810,810,810,810,810,5,0,760.0,766.8656226000166,739.9417039996479,808.1238649992883,112597.2
1708120286,5,,Aggregated,0.000000,0.000000,770,790,790,810,810,810,810,810,810,810,810,10,0,770.0,772.2130358999493,739.9417039996479,810.4625870000746,100155.2 11708120287,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120288,5,,Aggregated,0.000000,0.000000,750,790,790,800,800,800,800,800,800,800,800,5,0,750.0,769.4185964006465,748.8790659990627,803.4414130015648,83380.0
1708120289,5,,Aggregated,0.000000,0.000000,760,790,790,790,800,800,800,800,800,800,800,10,0,750.0,766.8473957004608,735.0468500007992,803.4414130015648,80938.1
1708120290,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120291,5,,Aggregated,0.000000,0.000000,770,790,790,800,800,800,800,800,800,800,800,5,0,770.0,777.8014348001307,753.5548569994717,796.277667999675,81174.4
1708120292,5,,Aggregated,0.000000,0.000000,790,790,800,800,800,800,800,800,800,800,800,10,0,780.0,780.7397893999223,751.0293370014551,798.0085099989083,78862.0
1708120293,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120294,5,,Aggregated,0.000000,0.000000,770,780,780,790,790,790,790,790,790,790,790,5,0,770.0,773.6631765998027,766.0003900000447,789.0164920008829,66962.6
1708120295,5,,Aggregated,0.000000,0.000000,780,790,790,790,800,800,800,800,800,800,800,10,0,770.0,774.3613966997145,747.1089509999729,796.8729549993441,73014.1
1708120296,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,01708121708120297,5,,Aggregated,0.000000,0.000000,750,760,760,780,780,780,780,780,780,780,780,5,0,750.0,754.7449921999942,735.4106349994254,784.463568999854,74520.0
1708120298,5,,Aggregated,0.000000,0.000000,760,770,770,780,790,790,790,790,790,790,790,10,0,750.0,759.355389600023,735.4106349994254,788.1290249988524,89134.0
1708120299,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120300,5,,Aggregated,0.000000,0.000000,760,780,780,800,800,800,800,800,800,800,800,5,0,760.0,768.2047425998462,733.6115340003744,796.9838690005417,81138.8
1708120301,5,,Aggregated,0.000000,0.000000,760,780,780,790,800,800,800,800,800,800,800,10,0,760.0,761.8415452998306,729.2013610003778,796.9838690005417,70626.6
1708120302,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120303,5,,Aggregated,0.000000,0.000000,760,770,770,770,770,770,770,770,770,770,770,5,0,760.0,760.0701720006327,749.7009590006201,765.3065320009773,59770.4
1708120304,5,,Aggregated,0.000000,0.000000,770,770,770,820,840,840,840,840,840,840,840,10,0,760.0,770.9050918003413,732.1205700009159,838.7217189992953,71508.0
1708120305,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120306,5,,Aggregated,0.000000,0.000000,790,790,790,800,800,800,800,800,800,800,800,5,0,790.0,781.94390299941,761.9448209989059,801.8397340001684,11818217081708120307,5,,Aggregated,0.000000,0.000000,780,790,790,790,800,800,800,800,800,800,800,10,0,780.0,778.0670066995299,759.1086890006409,801.8397340001684,91024.5
1708120308,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120309,5,,Aggregated,0.000000,0.000000,770,800,800,830,830,830,830,830,830,830,830,5,0,770.0,788.2040875996609,765.9989010007848,825.5261079993943,59421.6
1708120310,5,,Aggregated,0.000000,0.000000,770,780,800,800,830,830,830,830,830,830,830,10,0,770.0,770.9154035996107,714.7672320006677,825.5261079993943,62887.2
1708120311,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120312,5,,Aggregated,0.000000,0.000000,760,760,760,790,790,790,790,790,790,790,790,5,0,760.0,761.5312106001511,743.9974629996868,787.1899109995866,62589.8
1708120313,5,,Aggregated,0.000000,0.000000,750,760,760,760,790,790,790,790,790,790,790,10,0,750.0,755.8164174999547,741.9063769993954,787.1899109995866,57728.0
1708120314,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120315,5,,Aggregated,0.000000,0.000000,760,760,760,800,800,800,800,800,800,800,800,5,0,760.0,766.7834429998038,748.7704539998958,802.4864809995051,94574.8
1708120316,5,,Aggregated,0.000000,0.000000,760,760,770,790,800,800,800,800,800,800,800,10,0,760.0,763.1103706997237,732.9582829988794,802.4864809995051,93792.1171708120317,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120318,5,,Aggregated,0.000000,0.000000,750,760,760,790,790,790,790,790,790,790,790,5,0,750.0,754.4279632002144,738.3435550000286,786.7274879990873,75994.2
1708120319,5,,Aggregated,0.000000,0.000000,750,760,780,790,800,800,800,800,800,800,800,10,0,740.0,753.9272104000702,719.1268050009967,796.7480269999214,83471.6
1708120320,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120321,5,,Aggregated,0.000000,0.000000,780,780,780,790,790,790,790,790,790,790,790,5,0,780.0,770.4742760000954,723.2684850005171,790.7182470007683,115417.2
1708120322,5,,Aggregated,0.000000,0.000000,780,780,780,790,800,800,800,800,800,800,800,10,0,770.0,767.7272585000537,723.2684850005171,800.7560879996163,105214.9
1708120323,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120324,5,,Aggregated,0.000000,0.000000,760,760,760,770,770,770,770,770,770,770,770,5,0,760.0,754.2867003998253,736.1898290000681,767.3046889995021,87536.8
1708120325,5,,Aggregated,0.000000,0.000000,760,770,780,790,820,820,820,820,820,820,820,10,0,760.0,764.764476900018,736.1898290000681,815.9373260004941,88907.9
1708120326,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
/A,0,0,0,0.0,0,0,0
00000,690,690,700,770,780,780,780,780,780,780,780,10,0,610.0,657.5462337003046,560.5775940002786,783.0114600001252,85419.4
1708120326,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120317,200,,Aggregated,198.500000,0.000000,560,660,720,740,770,790,800,810,820,840,840,9430,0,560.0,532.4243413748623,151.52441800091765,843.5607709998294,80871.30296924709
1708120318,200,,Aggregated,199.900000,0.000000,560,660,720,740,770,790,800,810,820,840,840,10000,0,560.0,532.0657457829012,151.52441800091765,843.5607709998294,80924.869
1708120319,200,,Aggregated,199.900000,0.000000,560,660,720,740,770,790,800,810,820,840,840,10000,0,560.0,532.0657457829012,151.52441800091765,843.5607709998294,80924.869
1708120320,200,,Aggregated,198.700000,0.000000,560,660,720,740,770,790,800,810,820,840,840,10030,0,560.0,532.3277286419757,151.52441800091765,843.5607709998294,80890.13549351944
1708120321,200,,Aggregated,200.600000,0.000000,560,670,720,740,770,790,800,810,820,840,840,10600,0,560.0,532.0175906595315,151.52441800091765,843.5607709998294,80919.23009433963
1708120322,200,,Aggregated,200.600000,0.000000,560,670,720,740,770,790,800,810,820,840,840,10600,0,560.0,532.0175906595315,151.52441800091765,843.5607709998294,80919.23009433963
1708120323,200,,Aggregated,198.500000,0.000000,560,670,720,740,770,790,800,810,820,840,840,10630,0,560.0,532.2915265101637,151.52441800091765,843.5607709998294,80894.26274694262
1708120324,200,,Aggregated,200.000000,0.000000,560,670,720,740,770,790,800,810,830,840,840,11200,0,560.0,532.2438063676799,151.52441800091765,843.5607709998294,81009.42455357143
1708120325,200,,Aggregated,200.000000,0.000000,560,670,720,740,770,790,800,810,830,840,840,11200,0,560.0,532.2438063676799,151.52441800091765,843.5607709998294,81009.42455357143
1708120326,200,,Aggregated,198.100000,0.000000,560,670,720,740,770,790,800,810,830,840,840,11230,0,560.0,532.4219612337508,151.52441800091765,843.5607709998294,80993.50463045415
Load generator,Run number,Users,Total Req,runtime (s),Req/s,Energy (Joules),Power (W),Energy/Req,command
LOCUST,1,200,12000,60,200.0286222723644,4660.860000000001,77.68100000000001,0.38840500000000006,locust --headless --processes -1 --run-time 60 --users 200 --spawn-rate 200 --host http://ecotype-6.nantes.grid5000.fr:80 --csv 2024-02-16_22-52-31_px_200rps_60s_1.csv
Count,Message,Traceback,Nodes
Method,Name,Error,Occurrences
Type,Name,Request Count,Failure Count,Median Response Time,Average Response Time,Min Response Time,Max Response Time,Average Content Size,Requests/s,Failures/s,50%,66%,75%,80%,90%,95%,98%,99%,99.9%,99.99%,100%
GET,/fibo/1024/3/jpeg,12000,0,530.0,499.86161942807763,143.40982700014138,832.968623000852,81364.71491666666,200.0286222723644,0.0,530,630,680,710,740,760,780,790,820,830,830
,Aggregated,12000,0,530.0,499.86161942807763,143.40982700014138,832.968623000852,81364.71491666666,200.0286222723644,0.0,530,630,680,710,740,760,780,790,820,830,830
Timestamp,User Count,Type,Name,Requests/s,Failures/s,50%,66%,75%,80%,90%,95%,98%,99%,99.9%,99.99%,100%,Total Request Count,Total Failure Count,Total Median Response Time,Total Average Response Time,Total Min Response Time,Total Max Response Time,Total Average Content Size
1708120359,0,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120360,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120361,5,,Aggregated,0.000000,0.000000,710,720,720,740,740,740,740,740,740,740,740,5,0,710.0,711.2689170000522,688.9246400005504,740.9352680006123,104105.6
1708120362,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120363,5,,Aggregated,0.000000,0.000000,720,730,730,740,740,740,740,740,740,740,740,5,0,720.0,724.3270799997845,716.5075970006001,737.5516760002938,84000.2
1708120364,5,,Aggregated,0.000000,0.000000,730,740,740,740,760,760,760,760,760,760,760,10,0,730.0,730.2125815996988,716.5075970006001,755.230822998783,87825.1
1708120365,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120366,5,,Aggregated,0.000000,0.000000,760,760,760,760,760,760,760,760,760,760,760,5,0,759.3505530003313,741.9710579997627,718.0901979991177,759.3505530003313,79813.2
1708120367,5,,Aggregated,0.000000,0.000000,740,760,760,760,780,780,780,780,780,780,780,10,0,720.0,737.2860699997545,708.3954259996972,780.6009579999227,72885.0
1708120368,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120369,5,,Aggregated,0.000000,0.000000,730,730,730,750,750,750,750,750,750,750,750,5,0,730.0,731.8312479997985,718.0295039997873,746.37003001171708120370,5,1708120370,5,,Aggregated,0.000000,0.000000,730,730,740,750,750,750,750,750,750,750,750,10,0,730.0,731.9304990996898,716.3287269995635,748.7164270005451,63600.1
1708120371,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120372,5,,Aggregated,0.000000,0.000000,730,740,740,770,770,770,770,770,770,770,770,5,0,730.0,737.4666365998564,717.7591029994801,767.571238000528,119805.2
1708120373,5,,Aggregated,0.000000,0.000000,740,750,750,760,770,770,770,770,770,770,770,10,0,730.0,739.8223241001688,717.7591029994801,767.571238000528,104532.2
1708120374,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120375,5,,Aggregated,0.000000,0.000000,740,760,760,770,770,770,770,770,770,770,770,5,0,740.0,749.8985538000852,732.9352819997439,767.6736010016612,92767.6
1708120376,5,,Aggregated,0.000000,0.000000,730,740,740,760,770,770,770,770,770,770,770,10,0,730.0,738.5271997001837,721.5725830010342,767.6736010016612,83980.1
1708120377,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120378,5,,Aggregated,0.000000,0.000000,730,730,730,750,750,750,750,750,750,750,750,5,0,730.0,734.6614660000341,726.9369839996216,751.1003649997292,96143.8
1708120379,5,,Aggregated,0.000000,0.000000,730,730,730,730,750,750,750,750,750,750,750,10,0,700.0,715.1695791002567,687.5809730008768,751.10031708120380,5,,Aggre1708120380,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120381,5,,Aggregated,0.000000,0.000000,760,760,760,780,780,780,780,780,780,780,780,5,0,760.0,756.5476468003908,733.9129190004314,775.2746719997958,92206.4
1708120382,5,,Aggregated,0.000000,0.000000,740,750,760,760,780,780,780,780,780,780,780,10,0,740.0,743.0191588004163,710.3124690002005,775.2746719997958,86100.7
1708120383,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120384,5,,Aggregated,0.000000,0.000000,750,750,750,750,750,750,750,750,750,750,750,5,0,747.7295129992854,742.6832101995387,730.1436349989672,747.7295129992854,71840.6
1708120385,5,,Aggregated,0.000000,0.000000,740,740,750,750,750,750,750,750,750,750,750,10,0,730.0,730.9009574997617,695.5581140009599,747.7295129992854,70396.6
1708120386,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120387,5,,Aggregated,0.000000,0.000000,730,730,730,740,740,740,740,740,740,740,740,5,0,730.0,722.825044199999,711.5671550000116,735.3273650005576,89972.2
1708120388,5,,Aggregated,0.000000,0.000000,720,720,730,730,740,740,740,740,740,740,740,10,0,720.0,716.306634600005,694.1681770003925,735.3273650005576,96543.9
1708120389,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N171708120390,5,,Aggregated,0.0001708120390,5,,Aggregated,0.000000,0.000000,740,750,750,760,760,760,760,760,760,760,760,5,0,740.0,740.5801011995209,722.8595729993685,755.7917599988286,65926.8
1708120391,5,,Aggregated,0.000000,0.000000,730,730,740,750,760,760,760,760,760,760,760,10,0,720.0,729.7202344998368,713.2955710003444,755.7917599988286,65115.6
1708120392,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120393,5,,Aggregated,0.000000,0.000000,730,750,750,760,760,760,760,760,760,760,760,5,0,730.0,727.1969578003336,702.7590100005909,755.9151989989914,98852.2
1708120394,5,,Aggregated,0.000000,0.000000,720,730,750,750,760,760,760,760,760,760,760,10,0,720.0,724.7784118002528,702.7590100005909,755.9151989989914,90430.7
1708120395,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120396,5,,Aggregated,0.000000,0.000000,680,680,680,690,690,690,690,690,690,690,690,5,0,680.0,679.0921759999037,668.2387159999053,694.8989639986394,93303.2
1708120397,5,,Aggregated,0.000000,0.000000,720,720,720,720,770,770,770,770,770,770,770,10,0,690.0,703.3547114002431,668.2387159999053,768.7320430013642,85174.0
1708120398,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120399,5,,Aggregated,0.000000,0.000000,720,740,740,750,750,750,750,750,750,750,750,5,0,720.0,725.8290445995954,703.80410817081170811708120400,5,,Aggregated,0.000000,0.000000,730,730,740,740,770,770,770,770,770,770,770,10,0,720.0,720.8560740999019,656.7363410013058,768.5161409990542,78597.0
1708120401,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120402,5,,Aggregated,0.000000,0.000000,750,750,750,770,770,770,770,770,770,770,770,5,0,750.0,741.5529429999879,710.1428830010263,772.3765549999371,72513.2
1708120403,5,,Aggregated,0.000000,0.000000,750,750,760,760,770,770,770,770,770,770,770,10,0,730.0,737.0135957000457,703.1758399989485,772.3765549999371,77271.3
1708120404,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120406,5,,Aggregated,0.000000,0.000000,740,760,760,810,810,810,810,810,810,810,810,5,0,740.0,749.7532254001271,715.1455790008185,809.1936649998388,63486.6
1708120407,5,,Aggregated,0.000000,0.000000,730,740,760,760,810,810,810,810,810,810,810,10,0,730.0,735.272296200128,695.8362000004854,809.1936649998388,77146.2
1708120408,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120409,5,,Aggregated,0.000000,0.000000,710,720,720,750,750,750,750,750,750,750,750,5,0,710.0,712.1466145999875,689.5677030006482,745.0214979999146,52406.0
1708120410,5,,Aggregated,0.000000,0.000000,720,730,730,730,750,750,750,750,750,750,750,10,0,720.0,717.2620019000533,689.5677030006482,745.02149799991461708120411,170817081708120411,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120412,5,,Aggregated,0.000000,0.000000,660,670,670,690,690,690,690,690,690,690,690,5,0,660.0,628.1383389999974,554.6210430002247,686.4510409996001,90951.8
1708120413,5,,Aggregated,0.000000,0.000000,650,660,670,690,730,730,730,730,730,730,730,10,0,650.0,636.2599220999982,554.6210430002247,726.3209009997809,76056.6
1708120414,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120415,5,,Aggregated,0.000000,0.000000,620,630,630,650,650,650,650,650,650,650,650,5,0,620.0,610.5857758004277,558.330386000307,646.6108720014745,74358.6
1708120416,5,,Aggregated,0.000000,0.000000,620,630,650,650,740,740,740,740,740,740,740,10,0,620.0,609.9002802000541,472.21202199943946,740.2316989991959,85687.6
1708120417,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
1708120418,5,,Aggregated,0.000000,0.000000,550,570,570,580,580,580,580,580,580,580,580,5,0,550.0,536.1644461998367,473.30098299971723,584.6546789998683,67363.6
1708120419,5,,Aggregated,0.000000,0.000000,580,630,640,650,650,650,650,650,650,650,650,10,0,570.0,572.801589899791,473.30098299971723,650.14269600033,91156.6
1708120420,5,,Aggregated,0.000000,0.000000,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
A,0,0,0,0.0,0,0,0
,N/A,0,0,0,0.0,0,0,0
0.0,0,0,0
A,N/A,N/A,N/A,N/A,N/A,N/A,0,0,0,0.0,0,0,0
830,830,9400,0,530.0,500.2224912615936,143.40982700014138,832.968623000852,81366.96127659574
1708120410,200,,Aggregated,200.000000,0.000000,530,630,690,710,740,760,780,790,820,830,830,9430,0,530.0,500.04287013393224,143.40982700014138,832.968623000852,81343.52746553553
1708120411,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,10000,0,530.0,499.4760612498979,143.40982700014138,832.968623000852,81304.9748
1708120412,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,10000,0,530.0,499.4760612498979,143.40982700014138,832.968623000852,81304.9748
1708120413,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,10030,0,530.0,499.37318699222106,143.40982700014138,832.968623000852,81303.89601196411
1708120414,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,10600,0,530.0,499.636942289808,143.40982700014138,832.968623000852,81146.62764150943
1708120415,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,10600,0,530.0,499.636942289808,143.40982700014138,832.968623000852,81146.62764150943
1708120416,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,10630,0,530.0,499.3687772176827,143.40982700014138,832.968623000852,81184.77826904986
1708120417,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,11200,0,530.0,499.9805274437454,143.40982700014138,832.968623000852,81296.82258928572
1708120418,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,11200,0,530.0,499.9805274437454,143.40982700014138,832.968623000852,81296.82258928572
1708120419,200,,Aggregated,200.000000,0.000000,530,630,680,710,740,760,780,790,820,830,830,11230,0,530.0,499.6469262169143,143.40982700014138,832.968623000852,81296.8606411398
Load generator,Run number,Users,Total Req,runtime (s),Req/s,Energy (Joules),Power (W),Energy/Req,command
LOCUST,1,200,11976,60,200.03222316962103,3697.4670000000006,61.62445000000001,0.30873972945891787,locust --headless --processes -1 --run-time 60 --users 200 --spawn-rate 200 --host http://ecotype-6.nantes.grid5000.fr:80 --csv 2024-02-16_22-54-04_px_200rps_60s_1.csv
Count,Message,Traceback,Nodes
Method,Name,Error,Occurrences
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