def send_manager(output):
# recipient's email
toEmail1 = "*****@*****.**"
toEmail2 = "*****@*****.**"
msg1 = Message(subject="Health Recording System: Manager Report",
sender='*****@*****.**',
recipients=[toEmail1])
msg1.body = "Good Morning, Qixuan \n" + output
with webapp.app_context():
mail.send(msg1)
print("SendToQixuan")
msg2 = Message(subject="Health Recording System: Manager Report",
sender='*****@*****.**',
recipients=[toEmail2])
msg2.body = "Good Morning, Shixiong \n" + output
with webapp.app_context():
mail.send(msg2)
print("SendToShixiong!!!")
return True
def welcomeMailer(user):
name = Utils.getUserName(user)
with webapp.app_context():
email = Message('Welcome to Ostrich!', recipients=[user.email])
email.html = transform(
render_template('mailers/welcome.html', name=name))
mail.send(email)
return True
def delete_outdated(delete):
with webapp.app_context():
query = "DELETE FROM requests WHERE id = %s"
cnx = get_db()
cursor = cnx.cursor()
for id in delete:
# print("deleting HTTP request rate id: "+str(id))
cursor.execute(query, (id, ))
cnx.commit()
def sendUpsellEmail(data):
name = Utils.getUserName(data['user'])
with webapp.app_context():
consumer_mail = render_template(
'mailers/extend_order.html',
name=name,
book_name=data['book_name'],
order_id=data['order_id'],
items=data['items'],
curated_items=data['curated_items'],
quote=data['quote'],
quote_author=data['quote_author'])
pre = Premailer(consumer_mail,
remove_classes=False,
strip_important=False)
consumer_mail = pre.transform()
email = Message('Enjoying the book?',
recipients=[data['user'].email])
email.html = consumer_mail
mail.send(email)
return True
def cpuUtilHelper(id):
'''
request boto3 cloudwatch service and get the average CPU usage of the specific instance during the past 2 minuets
:param id:
:return: average CPU rate
'''
with webapp.app_context():
client = boto3.client('cloudwatch')
metric_name = 'CPUUtilization'
namespace = 'AWS/EC2'
statistic = 'Average' # could be Sum,Maximum,Minimum,SampleCount,Average
cpu = client.get_metric_statistics(
Period=1 * 60,
StartTime=datetime.datetime.utcnow() - timedelta(seconds=2 * 60),
EndTime=datetime.datetime.utcnow() - timedelta(seconds=0 * 60),
MetricName=metric_name,
Namespace=namespace, # Unit='Percent',
Statistics=[statistic],
Dimensions=[{
'Name': 'InstanceId',
'Value': id
}])
return cpu
def start_auto_scalling():
'''
Perform a continues loop and keeps checking if the average CPU meet the criteria of increasing/shrinking the instance
:return:
'''
with webapp.app_context():
write_log("Start Auto Scaling:")
while True:
if isAutoScaling:
delete_log()
write_log("=== === ===" + str(datetime.datetime.now()) +
"=== === ===")
cnx = get_database()
cnx.connect()
cursor = cnx.cursor()
query = "SELECT * FROM autoscaler_config"
cursor.execute(query)
results = cursor.fetchall()
cpu_threshold_grow = results[0][1]
cpu_threshold_shrinking = results[0][2]
ratio_grow = results[0][3]
ratio_shrink = results[0][4]
write_log("---> CPU Threshold grow: " +
str(cpu_threshold_grow))
write_log("---> CPU Threshold shrinking: " +
str(cpu_threshold_shrinking))
write_log("---> CPU ratio grow: " + str(ratio_grow))
write_log("---> CPU ratio shrink: " + str(ratio_shrink))
try:
auto_scaling(cpu_threshold_grow, cpu_threshold_shrinking,
ratio_grow, ratio_shrink)
except Exception as e:
write_log(e)
write_log("=== === === === === === === === ===")
sleep(time_interval)
cnx.close()
def increaseHelper():
with webapp.app_context():
ec2 = boto3.resource('ec2')
instances = ec2.instances.all()
workingWorkerCounter = 0
cmd = '''
#!/bin/bash
kill -9 $(lsof -t -i:5000)
source /var/lib/jenkins/workspace/flaskvenv/bin/activate
gunicorn -b 0.0.0.0:5000 --chdir /var/lib/jenkins/workspace/ece1779-image-processing/ app:webapp
'''
for instance in instances:
if instance.id != "i-0a4596b36ad81d462" and \
(instance.state['Name'] == "running" or instance.state['Name'] == "pending"):
workingWorkerCounter += 1
# if still have avaliable slots for new workers
if workingWorkerCounter < 10:
newInstance = ec2.create_instances(
ImageId=config.ami_id,
MinCount=1,
MaxCount=1,
InstanceType='t2.small',
KeyName="ECE1779_NEW",
)
newInstance[0].wait_until_running(
Filters=[{
'Name': 'instance-id',
'Values': [str(newInstance[0].id)]
}])
registerInstanceToLB(newInstance[0].id)
result = boto3.client('ec2').monitor_instances(
InstanceIds=[str(newInstance[0].id)])
return True
else:
return False
def auto_scaling(cpu_threshold_grow, cpu_threshold_shrinking, ratio_grow,
ratio_shrink):
'''
check if the average CPU of the instances in the past 2 minuets meet the criteria of increasing/shrinking the instance, if so, the function will excute the corresponding operation
:param cpu_threshold_grow: cpu_threshold_grow rate
:param cpu_threshold_shrinking: cpu_threshold_shrinking rate
:param ratio_grow: ratio_grow rate
:param ratio_shrink: ratio_shrink rate
:return:
'''
with webapp.app_context():
# getting average cpu utils
ec2 = boto3.resource('ec2')
# instances = ec2.instances.filter(
# Filters=[{'Name': 'instance-state-name', 'Values': ['running']}])
instances = ec2.instances.all()
instances = instance_filter(instances)
instancesCumCpuUtilData = 0
write_log(
"---> Currently: " + str(len(instances)) +
" instance(s) are registered under the load balancer and are running or pending"
)
if len(instances) == 0:
write_log("---> Currently no instance available, add one!")
increase()
instances = ec2.instances.all()
instances = instance_filter(instances)
for instance in instances:
cpuData = cpuUtilHelper(instance.id)
if len(cpuData['Datapoints']) != 0:
write_log("---> Average for instance: " +
str(cpuData['Datapoints'][0]['Average']))
if instance.launch_time.replace(tzinfo=None) <= (
datetime.datetime.utcnow() -
timedelta(seconds=5 * 60)).replace(tzinfo=None):
instancesCumCpuUtilData += cpuData['Datapoints'][0][
'Average']
else:
cnx = get_database()
cnx.connect()
cursor = cnx.cursor()
query = "SELECT * FROM autoscaler_config"
cursor.execute(query)
results = cursor.fetchall()
adjustment = results[0][2]
write_log(
"---> The instance: " + str(instance.id) +
" is just created. To avoid unusual high CPU util at the beginning of the boot, the current CPU util will be counted as "
+ str(adjustment) +
" at this time. This instance's real CPU util will be counted and be used for auto-scaling after: "
+
str(instance.launch_time + timedelta(seconds=5 * 60)) +
"!")
instancesCumCpuUtilData += adjustment
else:
write_log("---> Instance: " + str(instance.id) +
"'s monitoring data is still under preparation.")
average = instancesCumCpuUtilData / len(instances)
write_log("---> Current average of all instances: " + str(average))
# Enforcement
# if average > 90 and len(instances) < 10:
# increase()
# if average < 10 and len(instances) > 1:
# decrease()
# User customizable cases:
if average > cpu_threshold_grow:
write_log("---> Start to increase instance: ")
ctr = 0
for i in range(len(instances),
math.ceil(len(instances) * (ratio_grow))):
ctr = ctr + 1
write_log("------> Start to increase instance: " + str(ctr))
increase()
write_log("------> Completed the increment")
elif average < cpu_threshold_shrinking:
write_log("---> Start to decrease instance: ")
ctr = 0
lenth = len(instances)
for i in range(len(instances),
math.ceil(len(instances) * (ratio_shrink))):
if lenth > 1:
ctr = ctr + 1
write_log("------> Start to decrease instance: " +
str(ctr))
decrease()
lenth = lenth - 1
write_log("------> Completed the decrement")
elif lenth == 0:
write_log("Oops, all the instances deleted :( ")
increase()
write_log("Reopened a new one :) ")
else:
write_log(
"------> Oops, failed to delete the instance as there is only one instance left :( "
)
return average
import os
from app import webapp
from orm import DB, Session
import models
webapp.config.update({
'SQLALCHEMY_DATABASE_URI': os.environ['UQFINAL_DB_URI'],
'SQLALCHEMY_TRACK_MODIFICATIONS': False,
'SQLALCHEMY_POOL_SIZE': 0,
'SQLALCHEMY_POOL_RECYCLE': 500,
})
DB.init_app(webapp)
if __name__ == "__main__":
import sys
args = sys.argv
if len(args) > 1 and args[1] == "generatedb":
with webapp.app_context():
s = Session()
models.ORMBase.metadata.create_all(s.connection())
s.commit()
else:
webapp.run(port=8080)
def genericMailer(mail_obj, recipients=['*****@*****.**']):
with webapp.app_context():
email = Message(mail_obj['subject'], recipients=recipients)
email.body = mail_obj['body']
mail.send(email)
return True
def send_async_mail(webapp, email):
with webapp.app_context():
mail.send(email)
