def main(jsonDoc):
# Logger setup
try:
logging.basicConfig(filename='/var/log/boru.log',
level=logging.INFO,
format="%(asctime)s: %(levelname)s: %(message)s")
log = logging.getLogger('awsResume')
except Exception as e:
# Logging* just print, can't log
print("[awsResume] Critical Logger Setup Error: {}".format(str(e)))
# Exit
return
# Extracting the taskId and accountName for the DBConnect to start working from the next step
try:
taskId = jsonDoc['task_id']
accountName = jsonDoc["lab"]
except Exception as e:
# Logging
errorExceptionInfo = "[awsResume] Critical Error extracting 'taskId' and 'accountName' from 'jsonDoc': {}".format(
str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# Extract parameters from main(jsonDoc)
try:
region = jsonDoc["region"]
except Exception as e:
# Logging
errorExceptionInfo = "[awsResume] Critical Error Extracting 'jsonDoc' Parameters: {}".format(
str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# variables
listOfInstancesIdsRaw = []
listOfInstancesIdsFiltered = []
listOfInstancesStates = []
# ==========================
# Creating the boto3 session
# ==========================
try:
# Session [Most Important] | Used to access student child accounts
session = boto3.Session(profile_name=accountName, region_name=region)
except Exception as e:
# Logging
errorExceptionInfo = "[awsResume | {}] Failed to create a boto3 session. Error: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# =============================
# Getting all EC2 Instances Ids
# =============================
try:
getAllEc2Instances(session, listOfInstancesIdsRaw,
listOfInstancesStates, accountName, log)
except Exception as e:
errorExceptionInfo = "[awsResume | {}] Failed to Get EC2 Instances. Error: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# ================================================
# Filter any terminated instances to prevent error
# ================================================
try:
if (listOfInstancesIdsRaw):
filterInstances(listOfInstancesIdsRaw, listOfInstancesStates,
listOfInstancesIdsFiltered, accountName, log)
except Exception as e:
errorExceptionInfo = "[awsResume | {}] Failed to Filter EC2 Instances. Error: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# ==============================
# Starting all EC2 Instances Ids
# ==============================
if (listOfInstancesIdsFiltered):
try:
startAllEc2Instances(session, listOfInstancesIdsFiltered,
accountName, log)
# give time for the request to go through and start stopping instances
time.sleep(10)
# timeout variable
timeoutCounter = 0
# check if the instances have running
while True:
# variables to determine instance status
instancesStates = []
completeInstanceStatusCounter = 0
# getting the state/status of each filtered instance
for instanceId in listOfInstancesIdsFiltered:
getInstanceStatus(instanceId, instancesStates, session)
# if instance is running, add +1 to counter for every instance running
for instanceStatus in instancesStates:
# stack success
if (instanceStatus == 'running'):
completeInstanceStatusCounter += 1
# success, the number of running instances in the counter matches the length of a list of instances
if (completeInstanceStatusCounter == len(instancesStates)):
# update task status to ready
# DBConnect ============================
# Update task['taskStatus']
DBConnect.setTaskStatusToReady(taskId)
# ======================================
# logging
log.info(
"[awsResume | {}] Resume successful. Marked task as ready."
.format(str(accountName)))
return
# exit with timeout of 60 min
elif (timeoutCounter > 60):
# update task status error error
errorExceptionInfo = "[awsResume | {}] Timeout error. Marked task as error.".format(
str(accountName))
log.error(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
return
# add to counter
timeoutCounter += 1
# sleep timer
time.sleep(60)
except Exception as e:
# logging
errorExceptionInfo = "[awsResume | {}] Failed to Stop EC2 Instances. Error: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
return
else:
log.warning("[awsResume | {}] No Instances found to stop.".format(
str(accountName)))
# DBConnect ============================
# Update task['taskStatus']
DBConnect.setTaskStatusToReady(taskId)
# ======================================
return
def main(jsonDoc):
# Example of 'jsonDoc'
'''
{
"task_id" : "abc111555566abbca",
"lab" : "Student01",
"courseName" : "ANYDC",
Everything passed in from the 'generateStartLabTaskBuffer' function in the scheduler,
along with cloudFormation parameters processed by the scheduler.
}
'''
# Logger setup
try:
logging.basicConfig(filename='/var/log/boru.log',
level=logging.INFO,
format="%(asctime)s: %(levelname)s: %(message)s")
log = logging.getLogger('awsStart')
except Exception as e:
# Logging* just print, can't log
print("[awsStart] Critical Logger Setup Error: {}".format(str(e)))
# Exit
return
# Extracting the taskId and accountName for the DBConnect to start working from the next step
try:
taskId = jsonDoc['task_id']
accountName = jsonDoc['lab']
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart] Critical Error extracting 'taskId' and 'accountName' from 'jsonDoc': {}".format(
str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# Extract parameters from main(jsonDoc)
try:
courseName = jsonDoc['courseName']
startDate = jsonDoc['startDate']
finishDate = jsonDoc['finishDate']
timezone = jsonDoc['timezone']
instructor = jsonDoc['instructor']
tag = jsonDoc['tag']
region = jsonDoc['region']
cloudFormationParameters = jsonDoc['parameters']
startTemplateUrl = jsonDoc['courseTemplate']
sensorTemplate = jsonDoc['sensorTemplate']
sensor = jsonDoc['sensor']
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart] Critical Error Extracting 'jsonDoc' Parameters: {}".format(
str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
''' Below the main stuff happens '''
# Just a sleep timer variable. Call him Gary
garyTheSnail = 30
# ===================
# Generate Stack Name
# ===================
# The stackName will look similar to: 'ANYDC-2-4Jul-Central-joriordan-ANYDC-CET-LabsTest'
# This name will be passed into 'cloudFormation.create_stack' as the 'StackName'
''' !!! If ANYDC removed from tag, add courseName to start, Else, dont add courseName'''
try:
stackName = generateStackName(courseName, startDate, finishDate,
timezone, instructor, tag)
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error generating the stack name: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# ====================================================
# Create a boto3 session and a cloudFormation resource
# ====================================================
# Creating the boto3 session that will communicate with AWS.
# Creating a session resource for a cloudFormation
try:
session = boto3.Session(profile_name=accountName, region_name=region)
cloudFormation = session.resource('cloudformation')
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error creating the boto3 session: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# ==================================================================
# Extracting all cloudFormationParameters from jsonDoc['parameters']
# ==================================================================
# Extracting all the raw parameters into lists that will be used to create a
# 'cloudFormationParametersBuffer', which will be passed into 'cloudFormation.create_stack'
try:
# Buffer, will be ignored
parametersKeysBuffer = []
parametersValsBuffer = []
# Add to the buffer
for param in cloudFormationParameters[0]:
parametersKeysBuffer.append(list(param.keys()))
parametersValsBuffer.append(list(param.values()))
# Final keys and values
cloudFormationParametersKeys = []
cloudFormationParametersVals = []
# Extracting keys
for item in parametersKeysBuffer:
cloudFormationParametersKeys.append(item[0])
# Extracting values
for item in parametersValsBuffer:
cloudFormationParametersVals.append(item[0])
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error extracting cloudFormation parameters: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# ================================
# cloudFormation Parameters Buffer
# ================================
# This buffer is passed into 'cloudFormation.create_stack'
try:
# The buffer containing all cloudFormationParametersKeys and parametersValsBuffer ready for 'cloudFormation.create_stack'
parametersBuffer = []
# Creating the buffer
for paramIndex in range(len(cloudFormationParametersKeys)):
parametersBuffer.append({
'ParameterKey':
str(cloudFormationParametersKeys[paramIndex]),
'ParameterValue':
str(cloudFormationParametersVals[paramIndex])
})
# logging
log.info("[awsStart | {}] Course Parameters Buffer: {}".format(
str(accountName), str(parametersBuffer)))
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error creating cloudFormation parameters buffer: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# =====================
# Cloud Formation Stack
# =====================
# Creating the cloudFormation stack in AWS using 'cloudFormation.create_stack'
try:
cloudFormation.create_stack(StackName=str(stackName),
TemplateURL=str(startTemplateUrl),
Parameters=parametersBuffer,
Capabilities=['CAPABILITY_NAMED_IAM'])
# logging
log.info("[awsStart | {}] starting course cloudFormation...".format(
str(accountName)))
# Wait Gary number seconds to give time for AWS to set up stacks. Stack creation will take many minutes anyway
time.sleep(garyTheSnail)
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error creating AWS stack: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# =====================
# |Query the AWS Stack|
# =====================
# Query the AWS Stack and wait until it finishes deploying or until a timeout is reached.
response = queryAllStacks(session, accountName, log)
# If stacks failed to deploy, update task to error, log and exit
if (response):
# Logging
errorExceptionInfo = "[awsStart | {}] Error AWS stack(s) failed to deploy.".format(
str(accountName))
log.error(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# Need to get the stack info now BUT not store it yet as the senson might need to be spun up.
# If queryStackAndReturnInfo() is called after the sensor is up, it will return the sensor output, so do it now and store it.
successInfoToAppendToTask = queryStackAndReturnInfo(
session, taskId, accountName, log)
# ======
# Sensor
# ======
# Check if a sensor is required
if (sensor == "yes"):
# =====================
# Get Sensor Parameters
# =====================
# Get the course['sensorParameters'] from the DBConnect
courseSensorParameters = DBConnect.returnCourseSensorParameters(
courseName)
# Create lists used for each parameted. All of them are sorted by index.
listOfSensorParamFiles = []
listOfSensorParamKeys = []
listOfSensorParamValues = []
listOfSensorParamTypes = []
# Processed final values used for the buffer.
listOfSensorParamValuesProcessed = []
# =========================
# Process Sensor Parameters
# =========================
# Append all the information about each sensor parameter to lists.
# All lists are ordered by index
for param in courseSensorParameters['sensorParameters']:
listOfSensorParamFiles.append(param['paramFile'])
listOfSensorParamKeys.append(param['paramKey'])
listOfSensorParamValues.append(param['paramValue'])
listOfSensorParamTypes.append(param['paramType'])
# Now the big part, processing the sensor parameters. This must be done in the awsStart script and not the scheduler.
# This is done because some parameters require the course cloudFormation to be up and running. (It creates things required for the sensor)
try:
# Go through each parameter and process it. The final processed result is appended to 'listOfSensorParamValuesProcessed' (Plugins need to be processed)
for index in range(len(listOfSensorParamFiles)):
# There are two types of sensor parameters possible, 'plugin-static' and 'static'
# -------------
# plugin-static
# -------------
if (listOfSensorParamTypes[index] == "plugin-static"):
# Get the paramFile as it is required to process the plugin
paramFile = listOfSensorParamFiles[index]
# Get the Key of the parameter
paramKey = listOfSensorParamKeys[index]
# Get the static Value of the parameter stored in DB as it is static
paramUnprocessedValue = listOfSensorParamValues[index]
# ---
# Now run and process the parameter as it is a plugin
sensorParamProcessedValue = sensorParameterPluginStatic(
paramFile, paramUnprocessedValue, accountName, region)
for key in sensorParamProcessedValue:
value = sensorParamProcessedValue[key]
if (checkParamValueForError(key)):
# Logging
errorExceptionInfo = "[awsStart | {}] Failed to process plugin parameter: {}. Plugin response: {}".format(
str(accountName), str(key), str(value))
log.error(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(
taskId, accountName, errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
else:
listOfSensorParamValuesProcessed.append(str(value))
# There are two types of sensor parameters possible, 'plugin-static' and 'static'
# ------
# static
# ------
elif (listOfSensorParamTypes[index] == "static"):
# Append the static param value. No processing required as it is not a plugin
listOfSensorParamValuesProcessed.append(
str(listOfSensorParamValues[index]))
# All other types are not supporded for now
# No other parameter types accapted. Return error
else:
# Logging
error = "[awsStart | {}] Sensor parameter Type '{}' not accepted for sensor Parameters.".format(
str(accountName), str(listOfSensorParamTypes[index]))
log.error(error)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName, error)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error processing sensor parameters: {}".format(
str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# ========================
# Sensor Parameters Buffer
# ========================
# This buffer is passed into 'cloudFormation.create_stack'
try:
# The buffer containing all sensorParametersKeys and parametersValsBuffer ready for 'cloudFormation.create_stack'
parametersBuffer = []
# Creating the buffer
for paramIndex in range(len(listOfSensorParamKeys)):
parametersBuffer.append({
'ParameterKey':
str(listOfSensorParamKeys[paramIndex]),
'ParameterValue':
str(listOfSensorParamValuesProcessed[paramIndex])
})
# logging
log.info("[awsStart | {}] Course Parameters Buffer: {}".format(
str(accountName), str(parametersBuffer)))
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error creating sensor parameters buffer: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# =====================
# Cloud Formation Stack
# =====================
# Creating the cloudFormation stack in AWS using 'cloudFormation.create_stack'
try:
cloudFormation.create_stack(StackName="Sensor",
TemplateURL=str(sensorTemplate),
Parameters=parametersBuffer,
Capabilities=['CAPABILITY_NAMED_IAM'])
# logging
log.info(
"[awsStart | {}] starting sensor cloudFormation...".format(
str(accountName)))
# Wait Gary number seconds to give time for AWS to set up stacks. Stack creation will take many minutes anyway
time.sleep(garyTheSnail)
except Exception as e:
# Logging
errorExceptionInfo = "[awsStart | {}] Error creating AWS stack: {}".format(
str(accountName), str(e))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# =====================
# |Query the AWS Stack|
# =====================
# Query the AWS Stack and wait until it finishes deploying or until a timeout is reached.
response = queryAllStacks(session, accountName, log)
# If stacks failed to deploy, update task to error, log and exit
if (response):
# Logging
errorExceptionInfo = "[awsStart | {}] Error AWS sensor stack(s) failed to deploy.".format(
str(accountName))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# ===============================================================================
# Adding --protocol all to a security group begining with "Sensor-USM-ServicesSG"
# ===============================================================================
response = addProtocolAllToSensorUSMServicesSG(session, accountName,
log)
# If adding the security group fails, update task to error, log and exit
if (response[0]):
# Logging
errorExceptionInfo = "[awsStart | {}] Failed to add --protocol all to Sensor-USM-ServicesSG security group. Error: {}".format(
str(accountName), str(response[1]))
log.exception(errorExceptionInfo)
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
errorExceptionInfo)
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
# Exit
return
# Add sensor public and private IP's
successInfoToAppendToTask = appendInternalAndExternalIpsForSuccessInfo(
session, successInfoToAppendToTask, accountName, log)
# Add the output information from the cloudFormation to task['successInfo']
addStackSuccessInfoToTask(session, taskId, accountName,
successInfoToAppendToTask)
# After the sensor is up, now we can finish the task successfully
# DBConnect ============================
# Update task['taskStatus']
DBConnect.setTaskStatusToReady(taskId)
# ======================================
# Jump to here if no sensor is required and mark the task successfully
else:
# Add the output information from the cloudFormation to task['successInfo']
addStackSuccessInfoToTask(session, taskId, accountName,
successInfoToAppendToTask)
# DBConnect ============================
# Update task['taskStatus']
DBConnect.setTaskStatusToReady(taskId)
def queryAllStacks(session, accountName, log):
try:
# Timeout counter variable
timeoutCounter = 0
# Fail flag, set when a task timeouts or has one of the unsuccessful states like: CREATE_FAILED
failFlag = False
# Loop until a timeout is reached (will break out of loop)
while (True):
# Get all stacks in the account using boto3 session
allStacks = session.client("cloudformation").list_stacks()
# Log the loop for something to look at
log.info("[awsStart | {}] Querying all stacks...".format(
str(accountName)))
# Variables
# 2 lists one for stackNames and other for its status.
# To successfully exit this function, all stacks in these arrays have to be 'CREATE_COMPLETE'
stackNames = []
stackStatuses = []
# Counter incremented when a stack finished successfully. Compared with list of stackNames in order to exit the function.
completeStackStatusCounter = 0
# Loop through all the stacks in 'allStacks'
for stack in allStacks['StackSummaries']:
if ((stack['StackStatus'] == 'CREATE_IN_PROGRESS')
or (stack['StackStatus'] == 'CREATE_COMPLETE')
or (stack['StackStatus'] == 'CREATE_FAILED')
or (stack['StackStatus'] == 'ROLLBACK_IN_PROGRESS')
or (stack['StackStatus'] == 'ROLLBACK_FAILED')
or (stack['StackStatus'] == 'ROLLBACK_COMPLETE')):
stackNames.append(str(stack['StackName']))
stackStatuses.append(str(stack['StackStatus']))
# Add +1 to the 'completeStackStatusCounter' when a stack has status of 'CREATE_COMPLETE'
for stackStatus in stackStatuses:
# stack success
if (stackStatus == 'CREATE_COMPLETE'):
completeStackStatusCounter += 1
# stack fail, set the fail flag and break the loop. It's over, a stack failed to deploy
elif ((stackStatus == 'CREATE_FAILED')
or (stackStatus == 'ROLLBACK_IN_PROGRESS')
or (stackStatus == 'ROLLBACK_FAILED')
or (stackStatus == 'ROLLBACK_COMPLETE')):
# mark the fail flag true
failFlag = True
# DBConnect ============================
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(
taskId, accountName,
"CloudFormation for {} failed to deploy. Log in with Admin and inspect the cloudFormation events."
.format(str(accountName)))
# Update task['taskStatus']
DBConnect.setTaskStatusToError(taskId)
# ======================================
break
# Check if all stacks are up successfully
if (completeStackStatusCounter == len(stackNames)):
# logging
log.info("[awsStart | {}] Stacks created.".format(
str(accountName)))
# this will be False, no fail or error
# Exit function
return failFlag
# Add to the timeout counter
timeoutCounter += 1
# Check for timeout, exit function if true
if (timeoutCounter > 60):
# logging
log.error(
"[awsStart | {}] 60 minute timeout in queryAllStacks method, Timeout error."
.format(str(accountName)))
# mark the fail flag true
failFlag = True
# Check if the failFlag is set, if it is, a stack didn't deploy
if (failFlag):
# logging
log.error("[awsStart | {}] Failed to create stack.".format(
str(accountName)))
# this will be True, some error occured or cloudFormation failed to deploy
return failFlag
# Sleep and give time for stacks to deploy
time.sleep(60)
except Exception as e:
log.exception(
"[awsStart | {}] Query All Stacks function failed: {}.".format(
str(accountName), str(e)))
return True
def main(jsonDoc):
# ------------
# Logger setup
# ------------
try:
logging.basicConfig(filename='/var/log/boru.log',
level=logging.INFO,
format="%(asctime)s: %(levelname)s: %(message)s")
log = logging.getLogger('SCRIPT_NAME')
except Exception as e:
# No logging, just print, can't log :(
print("[SCRIPT_NAME] Critical Logger Setup Error: {}".format(str(e)))
# Exit
return
# -----------------------------------
# Extracting the task_id from jsonDoc
# -----------------------------------
# Required to use DBConnect, passed into every jsonDoc.
taskId = jsonDoc['task_id']
# --------------
# YOUR CODE HERE
# --------------
# --------------------------------------------------------------------------------------------------------------------
# EXAMPLES BELOW
# --------------------------------------------------------------------------------------------------------------------
# ----------------------------------------------------------
# Example of appending 'ERROR' information using 'DBConnect'
# ----------------------------------------------------------
# NOTE: This script MUST update the Task Status to 'Error' or 'Ready' before exiting any script.
try:
i = 10 / 0
except Exception as e:
# Logging
errorExceptionInfo = "[SCRIPT_NAME] Example Function Error: {}".format(
str(e))
log.exception(errorExceptionInfo)
# Update task['errorInfo']
DBConnect.appendTaskErrorInfo(taskId, accountName,
"Error: {}".format(str(e)))
# Update task['taskStatus'] to 'Error'
DBConnect.setTaskStatusToError(taskId)
# Exit
return
# ------------------------------------------------------------
# Example of appending 'SUCCESS' information using 'DBConnect'
# ------------------------------------------------------------
# NOTE: This script MUST update the Task Status to 'Ready' or 'Error' before exiting any script.
# Update task['successInfo']
DBConnect.appendTaskSuccessInfo(taskId, accountName,
"Successful Info Here")
# Update task['taskStatus'] to 'Ready'
DBConnect.setTaskStatusToReady(taskId)
# Exit
return
# --------------------------------------------------------------------------------------------------------------------
