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Merge pull request #257 from karaatanassov/kkaraataanassov/monitoring-sample
Sample for using appliance Monitoring
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samples/vsphere/appliances/monitoring_query.py
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samples/vsphere/appliances/monitoring_query.py
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#!/usr/bin/env python
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"""
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* *******************************************************
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* Copyright (c) VMware, Inc. 2021. All Rights Reserved.
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* SPDX-License-Identifier: MIT
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* *******************************************************
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*
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* DISCLAIMER. THIS PROGRAM IS PROVIDED TO YOU "AS IS" WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, WHETHER ORAL OR WRITTEN,
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* EXPRESS OR IMPLIED. THE AUTHOR SPECIFICALLY DISCLAIMS ANY IMPLIED
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* WARRANTIES OR CONDITIONS OF MERCHANTABILITY, SATISFACTORY QUALITY,
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* NON-INFRINGEMENT AND FITNESS FOR A PARTICULAR PURPOSE.
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"""
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__author__ = 'VMware, Inc.'
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__vcenter_version__ = '6.7+'
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from vmware.vapi.vsphere.client import create_vsphere_client
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from datetime import datetime, timedelta
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from samples.vsphere.common import (sample_cli, sample_util)
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from samples.vsphere.common.ssl_helper import get_unverified_session
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"""
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Description: Demonstrates monitoring api workflow
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1. List all memory and cpu counters
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2. Query and print daily averages
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"""
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MEMORY_CATEGORY = "com.vmware.applmgmt.mon.cat.memory"
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CPU_CATEGORY = "com.vmware.applmgmt.mon.cat.cpu"
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CATEGORIES = (MEMORY_CATEGORY, CPU_CATEGORY)
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METRIC_TITLE = "Metric"
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DAY = timedelta(days=1)
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DATE_FORMAT = "%Y-%m-%d"
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parser = sample_cli.build_arg_parser()
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args = sample_util.process_cli_args(parser.parse_args())
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session = get_unverified_session() if args.skipverification else None
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client = create_vsphere_client(server=args.server,
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username=args.username,
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password=args.password,
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session=session)
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# Get the Monitoring interface
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monitoring = client.appliance.Monitoring
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# List the available counters
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counters = monitoring.list()
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# Get the names of counters that relate to CPU and Memory categories
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conterIds = []
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for counter in counters:
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if counter.category in CATEGORIES:
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conterIds.append(counter.id)
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# Compute interval for last few days
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end = datetime.now()
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start = end - timedelta(days=2)
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# Query timeseries data
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query = monitoring.MonitoredItemDataRequest(names=conterIds,
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interval="DAY1",
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function="AVG",
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start_time=start,
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end_time=end)
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data = monitoring.query(query)
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print("Example: Query Monitoring for Timeseries Data:")
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print("-------------------\n")
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# Create title and row format strings
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# We need one labeled column for every day between start and end
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# Reserve 25 characters for the first column with metric name
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title = METRIC_TITLE + (" " * (25 - len(METRIC_TITLE)))
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columnFormat = "{0:25}"
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idx = 0
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timestamp = start
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# Create columns for each day
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while timestamp <= end:
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# 24 characters per column. In the title use 10 for date and 14 padding.
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title += timestamp.strftime(DATE_FORMAT) + " " * 14
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columnFormat += "{{1[{}]:24}}".format(idx)
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# increment
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idx = idx + 1
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timestamp = timestamp + DAY
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print(title)
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for item in data:
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print(columnFormat.format(item.name, item.data))
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