def compose_metric(self, request, cluster_data):
metrics_cpu, metrics_mem, metrics_disk = [], [], []
for i in cluster_data['results']:
time = arrow.get(i['capacity_updated_at']).timestamp * 1000
metrics_cpu.append({
'time': time,
'remain_cpu': num_transform(i['remain_cpu']),
'total_cpu': i['total_cpu']
})
if request.project.kind == app_constants.ProjectKind.MESOS.value:
# transfer GB
total_mem = normalize_metric(i['total_mem'] / 1024)
remain_mem = normalize_metric(
num_transform(i['remain_mem']) / 1024)
else:
total_mem = normalize_metric(i['total_mem'])
remain_mem = normalize_metric(num_transform(i['remain_mem']))
metrics_mem.append({
'time': time,
'remain_mem': remain_mem,
'total_mem': total_mem
})
# add disk metric
metrics_disk.append({
'time':
time,
'remain_disk':
normalize_metric(num_transform(i['remain_disk']) / 1024),
'total_disk':
normalize_metric(i['total_disk'] / 1024)
})
return metrics_cpu, metrics_mem, metrics_disk
def compose_metric(self, request, cluster_data):
metrics_cpu, metrics_mem, metrics_disk = [], [], []
for i in cluster_data['results']:
time = arrow.get(i['capacity_updated_at']).timestamp * 1000
metrics_cpu.append({
'time': time,
'remain_cpu': num_transform(i['remain_cpu']),
'total_cpu': i['total_cpu']
})
total_mem = normalize_metric(i['total_mem'])
remain_mem = normalize_metric(num_transform(i['remain_mem']))
metrics_mem.append({
'time': time,
'remain_mem': remain_mem,
'total_mem': total_mem
})
# add disk metric
metrics_disk.append({
'time':
time,
'remain_disk':
normalize_metric(num_transform(i['remain_disk']) / 1024),
'total_disk':
normalize_metric(i['total_disk'] / 1024),
})
return metrics_cpu, metrics_mem, metrics_disk