#!/usr/bin/env python

#

# This script shows an advanced Sysdig Cloud data request that leverages

# filtering and segmentation.

#

# The request returns the last 10 minutes of CPU utilization for all of the

# containers inside the given host, with 1 minute data granularity

#

import os

import sys

sys.path.insert(0, os.path.join(os.path.dirname(os.path.realpath(sys.argv[0])), '..'))

from sdcclient import SdcClient

#

# Parse arguments

#

if len(sys.argv) != 3:

print 'usage: %s <sysdig-token> <hostname>' % sys.argv[0]

print 'You can find your token at https://app.sysdigcloud.com/#/settings/user'

sys.exit(1)

sdc_token = sys.argv[1]

hostname = sys.argv[2]

#

# Instantiate the SDC client

#

sdclient = SdcClient(sdc_token)

#

# Prepare the metrics list.

#

metrics = [

# The first metric we request is the container name. This is a segmentation

# metric, and you can tell by the fact that we don't specify any aggregation

# criteria. This entry tells Sysdig Cloud that we want to see the CPU

# utilization for each container separately.

{"id": "container.name"},

# The second metric we reuest is the CPU. We aggregate it as an average.

{"id": "cpu.used.percent",

"aggregations": {

"time": "avg",

"group": "avg"

}

}

]

#

# Prepare the filter

#

filter = "host.hostName = '%s'" % hostname

#

# Fire the query.

#

res = sdclient.get_data(metrics, # metrics list

-600, # start_ts = 600 seconds ago

0, # end_ts = now

60, # 1 data point per minute

filter, # The filter

'container') # The source for our metrics is the container

#

# Show the result!

#

print res[1]

if not res[0]:

sys.exit(1)