def gcpInstances(machine):
cloud = 'GCP'
machineList = [machine for machine in nc.find({"node":machine},{'_id': False})]
matchingFlavor = getMatchingInstances(GC_FLAVORS, machine['cpu'], ceil(float(machine['memory'])))
matchingMachines = sorted(matchingFlavor)
return render_template('matching_instances.html', data=matchingMachines, cloudProvider=cloud)
def nodes(cluster):
session['cluster'] = cluster
machineList = [machine for machine in nc.find({"cluster_id":cluster},{'_id':False})]
#my_keys = ['node','os','cpu', 'memory', 'disk']
computedAWSCost = []
computedGCPCost = []
totalAWSCost = 0
totalGCPCost = 0
for machine in machineList:
#get GCP costs
flavorGCP= getMatchingInstances(GC_FLAVORS, machine['cpu'], ceil(float(machine['memory'])))
instanceCostGCP = gce_price(1,"regular", "us", flavorGCP[0]['name'], ceil(float(machine['disk'])), machine['os'])
totalGCPCost += instanceCostGCP
computedGCPCost.append(instanceCostGCP)
#get aws costs
flavorAWS = getMatchingInstances(AWS_FLAVORS, machine['cpu'], ceil(float(machine['memory'])))
instanceCostAWS = read_EC2_ondemand_instance_prices(1, "us-east-1", flavorAWS[0]['name'], machine['os'].lower())
storageAWSCost = aws_storage_prices("us-east-1", ceil(float(machine['disk'])))
monthlyCost = instanceCostAWS + storageAWSCost
totalAWSCost += monthlyCost
computedAWSCost.append(monthlyCost)
return render_template('nodes.html', data=machineList, ceil=ceil, dataAWS=zip(machineList,computedAWSCost),
totalAWS=totalAWSCost, totalGCP=totalGCPCost, dataGCP= zip(machineList,computedGCPCost), session=session)
def gcpInstances(machine):
cloud = 'GCP'
machineList = [
machine for machine in nc.find({"node": machine}, {'_id': False})
]
matchingFlavor = getMatchingInstances(GC_FLAVORS, machine['cpu'],
ceil(float(machine['memory'])))
matchingMachines = sorted(matchingFlavor)
return render_template('matching_instances.html',
data=matchingMachines,
cloudProvider=cloud)
def get_machine_resources(machine):
vcpu = 0
mem = 0
strg = 0
opsys = ''
for resource in nc.find({"node":machine}, {"cpu":1,"memory":1, "disk":1, "os":1, "_id":0}):
vcpu = resource['cpu']
mem = float(resource['memory'])
strg = float(resource['disk'])
opsys = resource['os']
return vcpu, mem, strg, opsys
def cost_variation(machine, chartID='chart_ID', chart_type='spline', chart_height=500, zoom_type='xy'):
percentage_usage =[10, 25, 30, 40, 50, 60, 75, 80, 90, 100]
GCP_Cost = []
AWS_Cost = []
#machineList = [machine['node'] for machine in nc.find({"cluster_id":session['cluster']},{'_id':False})]
specs = [node for node in nc.find({"node":machine},{'_id': False})]
flavorAWS = getMatchingInstances(AWS_FLAVORS, specs[0]['cpu'], ceil(float(specs[0]['memory'])))
flavorGCP = getMatchingInstances(GC_FLAVORS, specs[0]['cpu'], ceil(float(specs[0]['memory'])))
for percent in percentage_usage:
GCP_Cost.append(get_gcp_instance_unit_cost('us', flavorGCP[0]['name'],specs[0]['os'].lower(),percent))
AWS_Cost.append(get_aws_instance_unit_cost('us-east-1', flavorAWS[0]['name'],specs[0]['os'].lower(), percent))
text_title = "Variation in instance charges on AWS and GCP"
chart = {"renderTo": chartID, "type": chart_type, "height": chart_height, "zoomType": zoom_type
,
"backgroundColor": {
"linearGradient": [0, 0, 0, 500],
"stops": [
[0, 'rgb(255, 255, 255)'],
[1, 'rgb(200, 200, 255)']
]
}}
credits = {}
if GCP_Cost and AWS_Cost:
series = [
{"name": 'AWS',
"type": 'spline',
"data": AWS_Cost
}, {
"name" : 'GCP',
"type": 'spline',
"data" : GCP_Cost
}
]
title = { "text": text_title }
xAxis = {"type": 'category',
"categories": percentage_usage,
"tickInterval": 10,
"title": {"text": "Percentage of Instance Usage in a Month"}
}
yAxis = {
"title": {"text": 'Charged Unit Cost in USD'}
}
return render_template('cost_variation.html', chartID=chartID, chart= chart, series=series, title=title, xAxis=xAxis, yAxis=yAxis)
def Show_On_Demand_Cost(machine, chartID='chart_ID', chart_type='spline', chart_height=500, zoom_type='xy'):
percentage_usage =[10, 25, 30, 40, 50, 60, 75, 80, 90, 100]
chart_data = []
AWS_Cost = []
specs = [node for node in nc.find({"node":machine},{'_id': False})]
flavorAWS = getMatchingInstances(AWS_FLAVORS, specs[0]['cpu'], ceil(float(specs[0]['memory'])))
flavorGCP = getMatchingInstances(GC_FLAVORS, specs[0]['cpu'], ceil(float(specs[0]['memory'])))
for percent in percentage_usage:
chart_data.append(gce_on_demand_costs(1,'us', flavorGCP[0]['name'],ceil(float(specs[0]['disk'])),specs[0]['os'].lower(), percent))
AWS_Cost.append(aws_on_demand_costs(1,'us-east-1', flavorAWS[0]['name'], ceil(float(specs[0]['disk'])) ,specs[0]['os'].lower() , percent))
GCP_Cost = chart_data
#json_cpu.append(cpu_user)
#json_data = json.dumps(cpu_user, default=json_util.default)
text_title = "Cost of instance per usage"
chart = {"renderTo": chartID, "type": chart_type, "height": chart_height, "zoomType": zoom_type
,
"backgroundColor": {
"linearGradient": [0, 0, 0, 500],
"stops": [
[0, 'rgb(255, 255, 255)'],
[1, 'rgb(200, 200, 255)']
]
}}
credits = {}
if GCP_Cost and AWS_Cost:
series = [
{"name": 'AWS',
"type": 'spline',
"data": AWS_Cost
}, {
"name" : 'GCP',
"type": 'spline',
"data" : GCP_Cost
}
]
title = {"text": text_title}
xAxis = {"type": 'category',
"categories": percentage_usage,
"tickInterval": 10,
"title": {"text": "Percentage of Instance Usage in a Month"}
}
yAxis = {
"title": {"text": 'Cost of Instance $'}
}
return render_template('costs.html', chartID=chartID, chart= chart, series=series, title=title, xAxis=xAxis, yAxis=yAxis)
def show_costs(machine):
if not machine:
return render_template("costs.html",
machine=None,
awsregions='',
gcpregions='',
data='')
regionCostAWS = []
regionCostGCP = []
awsregions = [
"us-east-1", "us-west-1", "us-west-2", "eu-west-1", "ap-southeast-1",
"ap-southeast-2", "ap-northeast-1", "sa-east-1", "eu-central-1",
"us-gov-west-1"
]
gcpregions = ['us', 'europe', 'asia']
specs = [node for node in nc.find({"node": machine}, {'_id': False})]
flavorAWS = getMatchingInstances(AWS_FLAVORS, specs[0]['cpu'],
ceil(float(specs[0]['memory'])))
flavorGCP = getMatchingInstances(GC_FLAVORS, specs[0]['cpu'],
ceil(float(specs[0]['memory'])))
for dataCenter in awsregions:
instanceCost = read_EC2_ondemand_instance_prices(
1, dataCenter, flavorAWS[0]['name'], specs[0]['os'].lower())
storageCost = aws_storage_prices(dataCenter,
ceil(float(specs[0]['disk'])))
monthlyCost = instanceCost + storageCost
#dic.(dataCenter, monthlyCost)
if instanceCost > 0:
regionCostAWS.append((dataCenter, monthlyCost))
sortedRegionCostOnAWS = sorted(regionCostAWS, key=itemgetter(1))
for dataCenter in gcpregions:
instanceCost = gce_price(1, "regular", dataCenter,
flavorGCP[0]['name'],
ceil(float(specs[0]['disk'])), specs[0]['os'])
if instanceCost > 0:
regionCostGCP.append((dataCenter, instanceCost))
sortedRegionCostOnGCP = sorted(regionCostGCP, key=itemgetter(1))
return render_template("costs.html",
machine=machine,
awsregions=sortedRegionCostOnAWS,
gcpregions=sortedRegionCostOnGCP)
def show_costs(machine):
if not machine:
return render_template("costs.html", machine=None, awsregions= '', gcpregions='', data='');
regionCostAWS = []
regionCostGCP = []
awsregions = [
"us-east-1",
"us-west-1",
"us-west-2",
"eu-west-1",
"ap-southeast-1",
"ap-southeast-2",
"ap-northeast-1",
"sa-east-1",
"eu-central-1",
"us-gov-west-1"
]
gcpregions = ['us', 'europe', 'asia']
specs = [node for node in nc.find({"node":machine},{'_id': False})]
flavorAWS = getMatchingInstances(AWS_FLAVORS, specs[0]['cpu'], ceil(float(specs[0]['memory'])))
flavorGCP = getMatchingInstances(GC_FLAVORS, specs[0]['cpu'], ceil(float(specs[0]['memory'])))
for dataCenter in awsregions:
instanceCost = read_EC2_ondemand_instance_prices(1, dataCenter, flavorAWS[0]['name'], specs[0]['os'].lower())
storageCost = aws_storage_prices(dataCenter, ceil(float(specs[0]['disk'])))
monthlyCost = instanceCost + storageCost
#dic.(dataCenter, monthlyCost)
if instanceCost > 0:
regionCostAWS.append((dataCenter, monthlyCost))
sortedRegionCostOnAWS = sorted(regionCostAWS, key= itemgetter(1))
for dataCenter in gcpregions:
instanceCost = gce_price(1,"regular", dataCenter, flavorGCP[0]['name'], ceil(float(specs[0]['disk'])), specs[0]['os'])
if instanceCost > 0:
regionCostGCP.append((dataCenter, instanceCost))
sortedRegionCostOnGCP = sorted(regionCostGCP, key= itemgetter(1))
return render_template("costs.html", machine=machine, awsregions= sortedRegionCostOnAWS, gcpregions=sortedRegionCostOnGCP);
def nodes(cluster):
session['cluster'] = cluster
machineList = [
machine for machine in nc.find({"cluster_id": cluster}, {'_id': False})
]
#my_keys = ['node','os','cpu', 'memory', 'disk']
computedAWSCost = []
computedGCPCost = []
totalAWSCost = 0
totalGCPCost = 0
for machine in machineList:
#get GCP costs
flavorGCP = getMatchingInstances(GC_FLAVORS, machine['cpu'],
ceil(float(machine['memory'])))
instanceCostGCP = gce_price(1, "regular", "us", flavorGCP[0]['name'],
ceil(float(machine['disk'])),
machine['os'])
totalGCPCost += instanceCostGCP
computedGCPCost.append(instanceCostGCP)
#get aws costs
flavorAWS = getMatchingInstances(AWS_FLAVORS, machine['cpu'],
ceil(float(machine['memory'])))
instanceCostAWS = read_EC2_ondemand_instance_prices(
1, "us-east-1", flavorAWS[0]['name'], machine['os'].lower())
storageAWSCost = aws_storage_prices("us-east-1",
ceil(float(machine['disk'])))
monthlyCost = instanceCostAWS + storageAWSCost
totalAWSCost += monthlyCost
computedAWSCost.append(monthlyCost)
return render_template('nodes.html',
data=machineList,
ceil=ceil,
dataAWS=zip(machineList, computedAWSCost),
totalAWS=totalAWSCost,
totalGCP=totalGCPCost,
dataGCP=zip(machineList, computedGCPCost),
session=session)
def cost_variation(machine,
chartID='chart_ID',
chart_type='spline',
chart_height=500,
zoom_type='xy'):
percentage_usage = [10, 25, 30, 40, 50, 60, 75, 80, 90, 100]
GCP_Cost = []
AWS_Cost = []
#machineList = [machine['node'] for machine in nc.find({"cluster_id":session['cluster']},{'_id':False})]
specs = [node for node in nc.find({"node": machine}, {'_id': False})]
flavorAWS = getMatchingInstances(AWS_FLAVORS, specs[0]['cpu'],
ceil(float(specs[0]['memory'])))
flavorGCP = getMatchingInstances(GC_FLAVORS, specs[0]['cpu'],
ceil(float(specs[0]['memory'])))
for percent in percentage_usage:
GCP_Cost.append(
get_gcp_instance_unit_cost('us', flavorGCP[0]['name'],
specs[0]['os'].lower(), percent))
AWS_Cost.append(
get_aws_instance_unit_cost('us-east-1', flavorAWS[0]['name'],
specs[0]['os'].lower(), percent))
text_title = "Variation in instance charges on AWS and GCP"
chart = {
"renderTo": chartID,
"type": chart_type,
"height": chart_height,
"zoomType": zoom_type,
"backgroundColor": {
"linearGradient": [0, 0, 0, 500],
"stops": [[0, 'rgb(255, 255, 255)'], [1, 'rgb(200, 200, 255)']]
}
}
credits = {}
if GCP_Cost and AWS_Cost:
series = [{
"name": 'AWS',
"type": 'spline',
"data": AWS_Cost
}, {
"name": 'GCP',
"type": 'spline',
"data": GCP_Cost
}]
title = {"text": text_title}
xAxis = {
"type": 'category',
"categories": percentage_usage,
"tickInterval": 10,
"title": {
"text": "Percentage of Instance Usage in a Month"
}
}
yAxis = {"title": {"text": 'Charged Unit Cost in USD'}}
return render_template('cost_variation.html',
chartID=chartID,
chart=chart,
series=series,
title=title,
xAxis=xAxis,
yAxis=yAxis)
def Show_On_Demand_Cost(machine,
chartID='chart_ID',
chart_type='spline',
chart_height=500,
zoom_type='xy'):
percentage_usage = [10, 25, 30, 40, 50, 60, 75, 80, 90, 100]
chart_data = []
AWS_Cost = []
specs = [node for node in nc.find({"node": machine}, {'_id': False})]
flavorAWS = getMatchingInstances(AWS_FLAVORS, specs[0]['cpu'],
ceil(float(specs[0]['memory'])))
flavorGCP = getMatchingInstances(GC_FLAVORS, specs[0]['cpu'],
ceil(float(specs[0]['memory'])))
for percent in percentage_usage:
chart_data.append(
gce_on_demand_costs(1, 'us', flavorGCP[0]['name'],
ceil(float(specs[0]['disk'])),
specs[0]['os'].lower(), percent))
AWS_Cost.append(
aws_on_demand_costs(1, 'us-east-1', flavorAWS[0]['name'],
ceil(float(specs[0]['disk'])),
specs[0]['os'].lower(), percent))
GCP_Cost = chart_data
#json_cpu.append(cpu_user)
#json_data = json.dumps(cpu_user, default=json_util.default)
text_title = "Cost of instance per usage"
chart = {
"renderTo": chartID,
"type": chart_type,
"height": chart_height,
"zoomType": zoom_type,
"backgroundColor": {
"linearGradient": [0, 0, 0, 500],
"stops": [[0, 'rgb(255, 255, 255)'], [1, 'rgb(200, 200, 255)']]
}
}
credits = {}
if GCP_Cost and AWS_Cost:
series = [{
"name": 'AWS',
"type": 'spline',
"data": AWS_Cost
}, {
"name": 'GCP',
"type": 'spline',
"data": GCP_Cost
}]
title = {"text": text_title}
xAxis = {
"type": 'category',
"categories": percentage_usage,
"tickInterval": 10,
"title": {
"text": "Percentage of Instance Usage in a Month"
}
}
yAxis = {"title": {"text": 'Cost of Instance $'}}
return render_template('costs.html',
chartID=chartID,
chart=chart,
series=series,
title=title,
xAxis=xAxis,
yAxis=yAxis)
def get_nodes_in_cluster(cluster):
machines_in_cluster = []
#get_node_name = function(doc) { return doc.node }
for machine in nc.find({"cluster_id":cluster}, {"node":1,"_id":0}):
machines_in_cluster.append(machine['node'])
return machines_in_cluster