Files
ProxLB/proxlb
2024-08-19 16:53:32 +02:00

1286 lines
68 KiB
Python
Executable File

#!/usr/bin/env python3
# ProxLB
# ProxLB (re)balances VM workloads across nodes in Proxmox clusters.
# ProxLB obtains current metrics from all nodes within the cluster for
# further auto balancing by memory, disk or cpu and rebalances the VMs
# over all available nodes in a cluster by having an equal resource usage.
# Copyright (C) 2024 Florian Paul Azim Hoberg @gyptazy <gyptazy@gyptazy.ch>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import argparse
import configparser
import json
import logging
import os
try:
import proxmoxer
_imports = True
except ImportError:
_imports = False
import random
import re
import requests
import socket
import sys
import time
import urllib3
# Constants
__appname__ = "ProxLB"
__version__ = "1.0.3"
__author__ = "Florian Paul Azim Hoberg <gyptazy@gyptazy.ch> @gyptazy"
__errors__ = False
# Classes
## Logging class
class SystemdHandler(logging.Handler):
""" Class to handle logging options. """
PREFIX = {
logging.CRITICAL: "<2> " + __appname__ + ": ",
logging.ERROR: "<3> " + __appname__ + ": ",
logging.WARNING: "<4> " + __appname__ + ": ",
logging.INFO: "<6> " + __appname__ + ": ",
logging.DEBUG: "<7> " + __appname__ + ": ",
logging.NOTSET: "<7 " + __appname__ + ": ",
}
def __init__(self, stream=sys.stdout):
self.stream = stream
logging.Handler.__init__(self)
def emit(self, record):
try:
msg = self.PREFIX[record.levelno] + self.format(record) + "\n"
self.stream.write(msg)
self.stream.flush()
except Exception:
self.handleError(record)
# Functions
def initialize_logger(log_level, update_log_verbosity=False):
""" Initialize ProxLB logging handler. """
info_prefix = 'Info: [logger]:'
root_logger = logging.getLogger()
root_logger.setLevel(log_level)
if not update_log_verbosity:
root_logger.addHandler(SystemdHandler())
logging.info(f'{info_prefix} Logger got initialized.')
else:
logging.info(f'{info_prefix} Logger verbosity got updated to: {log_level}.')
def pre_validations(config_path):
""" Run pre-validations as sanity checks. """
info_prefix = 'Info: [pre-validations]:'
__validate_imports()
__validate_config_file(config_path)
logging.info(f'{info_prefix} All pre-validations done.')
def post_validations():
""" Run post-validations as sanity checks. """
error_prefix = 'Error: [post-validations]:'
info_prefix = 'Info: [post-validations]:'
if __errors__:
logging.critical(f'{error_prefix} Not all post-validations succeeded. Please validate!')
else:
logging.info(f'{info_prefix} All post-validations succeeded.')
def validate_daemon(daemon, schedule):
""" Validate if ProxLB runs as a daemon. """
info_prefix = 'Info: [daemon]:'
if bool(int(daemon)):
logging.info(f'{info_prefix} Running in daemon mode. Next run in {schedule} hours.')
time.sleep(int(schedule) * 60 * 60)
else:
logging.info(f'{info_prefix} Not running in daemon mode. Quitting.')
sys.exit(0)
def __validate_imports():
""" Validate if all Python imports succeeded. """
error_prefix = 'Error: [python-imports]:'
info_prefix = 'Info: [python-imports]:'
if not _imports:
logging.critical(f'{error_prefix} Could not import all dependencies. Please install "proxmoxer".')
sys.exit(2)
else:
logging.info(f'{info_prefix} All required dependencies were imported.')
def __validate_config_file(config_path):
""" Validate if all Python imports succeeded. """
error_prefix = 'Error: [config]:'
info_prefix = 'Info: [config]:'
if not os.path.isfile(config_path):
logging.critical(f'{error_prefix} Could not find config file in: {config_path}.')
sys.exit(2)
else:
logging.info(f'{info_prefix} Configuration file loaded from: {config_path}.')
def initialize_args():
""" Initialize given arguments for ProxLB. """
argparser = argparse.ArgumentParser(description='ProxLB')
argparser.add_argument('-c', '--config', type=str, help='Path to config file.', required=False)
argparser.add_argument('-d', '--dry-run', help='Perform a dry-run without doing any actions.', action='store_true', required=False)
argparser.add_argument('-j', '--json', help='Return a JSON of the VM movement.', action='store_true', required=False)
return argparser.parse_args()
def initialize_config_path(app_args):
""" Initialize path to ProxLB config file. """
info_prefix = 'Info: [config]:'
config_path = app_args.config
if app_args.config is None:
config_path = '/etc/proxlb/proxlb.conf'
logging.info(f'{info_prefix} No config file provided. Falling back to: {config_path}.')
else:
logging.info(f'{info_prefix} Using config file: {config_path}.')
return config_path
def initialize_config_options(config_path):
""" Read configuration from given config file for ProxLB. """
error_prefix = 'Error: [config]:'
info_prefix = 'Info: [config]:'
try:
config = configparser.ConfigParser()
config.read(config_path)
# Proxmox config
proxmox_api_host = config['proxmox']['api_host']
proxmox_api_user = config['proxmox']['api_user']
proxmox_api_pass = config['proxmox']['api_pass']
proxmox_api_ssl_v = config['proxmox']['verify_ssl']
# VM Balancing
vm_balancing_enable = config['vm_balancing'].get('enable', 1)
vm_balancing_method = config['vm_balancing'].get('method', 'memory')
vm_balancing_mode = config['vm_balancing'].get('mode', 'used')
vm_balancing_mode_option = config['vm_balancing'].get('mode_option', 'bytes')
vm_balancing_type = config['vm_balancing'].get('type', 'vm')
vm_balanciness = config['vm_balancing'].get('balanciness', 10)
vm_parallel_migrations = config['vm_balancing'].get('parallel_migrations', 1)
vm_ignore_nodes = config['vm_balancing'].get('ignore_nodes', None)
vm_ignore_vms = config['vm_balancing'].get('ignore_vms', None)
# Storage Balancing
storage_balancing_enable = config['storage_balancing'].get('enable', 0)
storage_balancing_method = config['storage_balancing'].get('method', 'disk_space')
storage_balancing_balanciness = config['storage_balancing'].get('balanciness', 10)
storage_parallel_migrations = config['storage_balancing'].get('parallel_migrations', 0)
# Service
master_only = config['service'].get('master_only', 0)
daemon = config['service'].get('daemon', 1)
schedule = config['service'].get('schedule', 24)
log_verbosity = config['service'].get('log_verbosity', 'CRITICAL')
except configparser.NoSectionError:
logging.critical(f'{error_prefix} Could not find the required section.')
sys.exit(2)
except configparser.ParsingError:
logging.critical(f'{error_prefix} Unable to parse the config file.')
sys.exit(2)
except KeyError:
logging.critical(f'{error_prefix} Could not find the required options in config file.')
sys.exit(2)
logging.info(f'{info_prefix} Configuration file loaded.')
return proxmox_api_host, proxmox_api_user, proxmox_api_pass, proxmox_api_ssl_v, vm_balancing_enable, vm_balancing_method, vm_balancing_mode, vm_balancing_mode_option, \
vm_balancing_type, vm_balanciness, vm_parallel_migrations, vm_ignore_nodes, vm_ignore_vms, storage_balancing_enable, storage_balancing_method, storage_balancing_balanciness, storage_parallel_migrations, master_only, daemon, schedule, log_verbosity
def api_connect(proxmox_api_host, proxmox_api_user, proxmox_api_pass, proxmox_api_ssl_v):
""" Connect and authenticate to the Proxmox remote API. """
error_prefix = 'Error: [api-connection]:'
warn_prefix = 'Warning: [api-connection]:'
info_prefix = 'Info: [api-connection]:'
proxmox_api_ssl_v = bool(int(proxmox_api_ssl_v))
if not proxmox_api_ssl_v:
requests.packages.urllib3.disable_warnings()
logging.warning(f'{warn_prefix} API connection does not verify SSL certificate.')
try:
api_object = proxmoxer.ProxmoxAPI(proxmox_api_host, user=proxmox_api_user, password=proxmox_api_pass, verify_ssl=proxmox_api_ssl_v)
except urllib3.exceptions.NameResolutionError:
logging.critical(f'{error_prefix} Could not resolve the given host: {proxmox_api_host}.')
sys.exit(2)
except requests.exceptions.ConnectTimeout:
logging.critical(f'{error_prefix} Connection time out to host: {proxmox_api_host}.')
sys.exit(2)
except requests.exceptions.SSLError:
logging.critical(f'{error_prefix} SSL certificate verification failed for host: {proxmox_api_host}.')
sys.exit(2)
logging.info(f'{info_prefix} API connection succeeded to host: {proxmox_api_host}.')
return api_object
def execute_rebalancing_only_by_master(api_object, master_only):
""" Validate if balancing should only be done by the cluster master. Afterwards, validate if this node is the cluster master. """
info_prefix = 'Info: [only-on-master-executor]:'
master_only = bool(int(master_only))
if bool(int(master_only)):
logging.info(f'{info_prefix} Master only rebalancing is defined. Starting validation.')
cluster_master_node = get_cluster_master(api_object)
cluster_master = validate_cluster_master(cluster_master_node)
return cluster_master, master_only
else:
logging.info(f'{info_prefix} No master only rebalancing is defined. Skipping validation.')
return False, master_only
def get_cluster_master(api_object):
""" Get the current master of the Proxmox cluster. """
error_prefix = 'Error: [cluster-master-getter]:'
info_prefix = 'Info: [cluster-master-getter]:'
try:
ha_status_object = api_object.cluster().ha().status().manager_status().get()
logging.info(f'{info_prefix} Master node: {ha_status_object.get("manager_status", None).get("master_node", None)}')
except urllib3.exceptions.NameResolutionError:
logging.critical(f'{error_prefix} Could not resolve the API.')
sys.exit(2)
except requests.exceptions.ConnectTimeout:
logging.critical(f'{error_prefix} Connection time out to API.')
sys.exit(2)
except requests.exceptions.SSLError:
logging.critical(f'{error_prefix} SSL certificate verification failed for API.')
sys.exit(2)
cluster_master = ha_status_object.get("manager_status", None).get("master_node", None)
if cluster_master:
return cluster_master
else:
logging.critical(f'{error_prefix} Could not obtain cluster master. Please check your configuration - stopping.')
sys.exit(2)
def validate_cluster_master(cluster_master):
""" Validate if the current execution node is the cluster master. """
info_prefix = 'Info: [cluster-master-validator]:'
node_executor_hostname = socket.gethostname()
logging.info(f'{info_prefix} Node executor hostname is: {node_executor_hostname}')
if node_executor_hostname != cluster_master:
logging.info(f'{info_prefix} {node_executor_hostname} is not the cluster master ({cluster_master}).')
return False
else:
return True
def get_node_statistics(api_object, ignore_nodes):
""" Get statistics of cpu, memory and disk for each node in the cluster. """
info_prefix = 'Info: [node-statistics]:'
node_statistics = {}
ignore_nodes_list = ignore_nodes.split(',')
for node in api_object.nodes.get():
if node['status'] == 'online' and node['node'] not in ignore_nodes_list:
node_statistics[node['node']] = {}
node_statistics[node['node']]['cpu_total'] = node['maxcpu']
node_statistics[node['node']]['cpu_assigned'] = node['cpu']
node_statistics[node['node']]['cpu_assigned_percent'] = int((node_statistics[node['node']]['cpu_assigned']) / int(node_statistics[node['node']]['cpu_total']) * 100)
node_statistics[node['node']]['cpu_assigned_percent_last_run'] = 0
node_statistics[node['node']]['cpu_used'] = 0
node_statistics[node['node']]['cpu_free'] = int(node['maxcpu']) - int(node['cpu'])
node_statistics[node['node']]['cpu_free_percent'] = int((node_statistics[node['node']]['cpu_free']) / int(node['maxcpu']) * 100)
node_statistics[node['node']]['cpu_free_percent_last_run'] = 0
node_statistics[node['node']]['memory_total'] = node['maxmem']
node_statistics[node['node']]['memory_assigned'] = 0
node_statistics[node['node']]['memory_assigned_percent'] = int((node_statistics[node['node']]['memory_assigned']) / int(node_statistics[node['node']]['memory_total']) * 100)
node_statistics[node['node']]['memory_assigned_percent_last_run'] = 0
node_statistics[node['node']]['memory_used'] = node['mem']
node_statistics[node['node']]['memory_free'] = int(node['maxmem']) - int(node['mem'])
node_statistics[node['node']]['memory_free_percent'] = int((node_statistics[node['node']]['memory_free']) / int(node['maxmem']) * 100)
node_statistics[node['node']]['memory_free_percent_last_run'] = 0
node_statistics[node['node']]['disk_total'] = node['maxdisk']
node_statistics[node['node']]['disk_assigned'] = 0
node_statistics[node['node']]['disk_assigned_percent'] = int((node_statistics[node['node']]['disk_assigned']) / int(node_statistics[node['node']]['disk_total']) * 100)
node_statistics[node['node']]['disk_assigned_percent_last_run'] = 0
node_statistics[node['node']]['disk_used'] = node['disk']
node_statistics[node['node']]['disk_free'] = int(node['maxdisk']) - int(node['disk'])
node_statistics[node['node']]['disk_free_percent'] = int((node_statistics[node['node']]['disk_free']) / int(node['maxdisk']) * 100)
node_statistics[node['node']]['disk_free_percent_last_run'] = 0
logging.info(f'{info_prefix} Added node {node["node"]}.')
logging.info(f'{info_prefix} Created node statistics.')
return node_statistics
def get_vm_statistics(api_object, ignore_vms, balancing_type):
""" Get statistics of cpu, memory and disk for each vm in the cluster. """
info_prefix = 'Info: [vm-statistics]:'
warn_prefix = 'Warn: [vm-statistics]:'
vm_statistics = {}
ignore_vms_list = ignore_vms.split(',')
group_include = None
group_exclude = None
vm_ignore = None
vm_ignore_wildcard = False
# Wildcard support: Initially validate if we need to honour
# any wildcards within the vm_ignore list.
vm_ignore_wildcard = __validate_ignore_vm_wildcard(ignore_vms)
for node in api_object.nodes.get():
# Add all virtual machines if type is vm or all.
if balancing_type == 'vm' or balancing_type == 'all':
for vm in api_object.nodes(node['node']).qemu.get():
# Get the VM tags from API.
vm_tags = __get_vm_tags(api_object, node, vm['vmid'], 'vm')
if vm_tags is not None:
group_include, group_exclude, vm_ignore = __get_proxlb_groups(vm_tags)
# Get wildcard match for VMs to ignore if a wildcard pattern was
# previously found. Wildcards may slow down the task when using
# many patterns in the ignore list. Therefore, run this only if
# a wildcard pattern was found. We also do not need to validate
# this if the VM is already being ignored by a defined tag.
if vm_ignore_wildcard and not vm_ignore:
vm_ignore = __check_vm_name_wildcard_pattern(vm['name'], ignore_vms_list)
if vm['status'] == 'running' and vm['name'] not in ignore_vms_list and not vm_ignore:
vm_statistics[vm['name']] = {}
vm_statistics[vm['name']]['group_include'] = group_include
vm_statistics[vm['name']]['group_exclude'] = group_exclude
vm_statistics[vm['name']]['cpu_total'] = vm['cpus']
vm_statistics[vm['name']]['cpu_used'] = vm['cpu']
vm_statistics[vm['name']]['memory_total'] = vm['maxmem']
vm_statistics[vm['name']]['memory_used'] = vm['mem']
vm_statistics[vm['name']]['disk_total'] = vm['maxdisk']
vm_statistics[vm['name']]['disk_used'] = vm['disk']
vm_statistics[vm['name']]['vmid'] = vm['vmid']
vm_statistics[vm['name']]['node_parent'] = node['node']
vm_statistics[vm['name']]['storages'] = {}
vm_statistics[vm['name']]['type'] = 'vm'
# Get disk details of the related object.
_vm_details = api_object.nodes(node['node']).qemu(vm['vmid']).config.get()
_vm_details_storage_allowed = ['ide', 'nvme', 'scsi', 'virtio', 'sata']
logging.info(f'{info_prefix} Getting disk information for vm {vm["name"]}.')
for vm_detail_key, vm_detail_value in _vm_details.items():
vm_detail_key_validator = re.sub("\d+$", "", vm_detail_key)
if vm_detail_key_validator in _vm_details_storage_allowed:
vm_statistics[vm['name']]['storages'][vm_detail_key] = {}
match = re.match(r'([^:]+):[^/]+/(.+),iothread=\d+,size=(\d+G)', _vm_details[vm_detail_key])
# Create an efficient match group and split the strings to assign them to the storage information.
if match:
_volume = match.group(1)
_disk_name = match.group(2)
_disk_size = match.group(3)
vm_statistics[vm['name']]['storages'][vm_detail_key]['name'] = _disk_name
vm_statistics[vm['name']]['storages'][vm_detail_key]['device_name'] = vm_detail_key
vm_statistics[vm['name']]['storages'][vm_detail_key]['volume'] = _volume
vm_statistics[vm['name']]['storages'][vm_detail_key]['storage_parent'] = _volume
vm_statistics[vm['name']]['storages'][vm_detail_key]['storage_rebalance'] = None
vm_statistics[vm['name']]['storages'][vm_detail_key]['size'] = _disk_size
logging.info(f'{info_prefix} Added disk for {vm["name"]}: Name {_disk_name} on volume {_volume} with size {_disk_size}.')
else:
logging.info(f'{info_prefix} No disks for {vm["name"]} found.')
# Rebalancing node will be overwritten after calculations.
# If the vm stays on the node, it will be removed at a
# later time.
vm_statistics[vm['name']]['node_rebalance'] = node['node']
logging.info(f'{info_prefix} Added vm {vm["name"]}.')
# Add all containers if type is ct or all.
if balancing_type == 'ct' or balancing_type == 'all':
for vm in api_object.nodes(node['node']).lxc.get():
logging.warning(f'{warn_prefix} Rebalancing on LXC containers (CT) always requires them to shut down.')
logging.warning(f'{warn_prefix} {vm["name"]} is from type CT and cannot be live migrated!')
# Get the VM tags from API.
vm_tags = __get_vm_tags(api_object, node, vm['vmid'], 'ct')
if vm_tags is not None:
group_include, group_exclude, vm_ignore = __get_proxlb_groups(vm_tags)
# Get wildcard match for VMs to ignore if a wildcard pattern was
# previously found. Wildcards may slow down the task when using
# many patterns in the ignore list. Therefore, run this only if
# a wildcard pattern was found. We also do not need to validate
# this if the VM is already being ignored by a defined tag.
if vm_ignore_wildcard and not vm_ignore:
vm_ignore = __check_vm_name_wildcard_pattern(vm['name'], ignore_vms_list)
if vm['status'] == 'running' and vm['name'] not in ignore_vms_list and not vm_ignore:
vm_statistics[vm['name']] = {}
vm_statistics[vm['name']]['group_include'] = group_include
vm_statistics[vm['name']]['group_exclude'] = group_exclude
vm_statistics[vm['name']]['cpu_total'] = vm['cpus']
vm_statistics[vm['name']]['cpu_used'] = vm['cpu']
vm_statistics[vm['name']]['memory_total'] = vm['maxmem']
vm_statistics[vm['name']]['memory_used'] = vm['mem']
vm_statistics[vm['name']]['disk_total'] = vm['maxdisk']
vm_statistics[vm['name']]['disk_used'] = vm['disk']
vm_statistics[vm['name']]['vmid'] = vm['vmid']
vm_statistics[vm['name']]['node_parent'] = node['node']
vm_statistics[vm['name']]['storages'] = {}
vm_statistics[vm['name']]['type'] = 'ct'
# Get disk details of the related object.
_vm_details = api_object.nodes(node['node']).qemu(vm['vmid']).config.get()
_vm_details_storage_allowed = ['ide', 'nvme', 'scsi']
logging.info(f'{info_prefix} Getting disk information for vm {vm["name"]}.')
for vm_detail_key, vm_detail_value in _vm_details.items():
vm_detail_key_validator = re.sub("\d+$", "", vm_detail_key)
if vm_detail_key_validator in _vm_details_storage_allowed:
vm_statistics[vm['name']]['storages'][vm_detail_key] = {}
match = re.match(r'([^:]+):[^/]+/(.+),iothread=\d+,size=(\d+G)', _vm_details[vm_detail_key])
# Create an efficient match group and split the strings to assign them to the storage information.
if match:
_volume = match.group(1)
_disk_name = match.group(2)
_disk_size = match.group(3)
vm_statistics[vm['name']]['storages'][vm_detail_key]['name'] = _disk_name
vm_statistics[vm['name']]['storages'][vm_detail_key]['device_name'] = vm_detail_key
vm_statistics[vm['name']]['storages'][vm_detail_key]['volume'] = _volume
vm_statistics[vm['name']]['storages'][vm_detail_key]['storage_parent'] = _volume
vm_statistics[vm['name']]['storages'][vm_detail_key]['storage_rebalance'] = None
vm_statistics[vm['name']]['storages'][vm_detail_key]['size'] = _disk_size
logging.info(f'{info_prefix} Added disk for {vm["name"]}: Name {_disk_name} on volume {_volume} with size {_disk_size}.')
else:
logging.info(f'{info_prefix} No disks for {vm["name"]} found.')
# Rebalancing node will be overwritten after calculations.
# If the vm stays on the node, it will be removed at a
# later time.
vm_statistics[vm['name']]['node_rebalance'] = node['node']
logging.info(f'{info_prefix} Added vm {vm["name"]}.')
logging.info(f'{info_prefix} Created VM statistics.')
return vm_statistics
def get_storage_statistics(api_object):
""" Get statistics of all storages in the cluster. """
info_prefix = 'Info: [storage-statistics]:'
warn_prefix = 'Warn: [storage-statistics]:'
storage_statistics = {}
for node in api_object.nodes.get():
for storage in api_object.nodes(node['node']).storage.get():
# Only add enabled and active storage repositories that might be suitable for further
# storage balancing.
if storage['enabled'] and storage['active'] and storage['shared']:
storage_statistics[storage['storage']] = {}
storage_statistics[storage['storage']]['name'] = storage['storage']
storage_statistics[storage['storage']]['total'] = storage['total']
storage_statistics[storage['storage']]['used'] = storage['used']
storage_statistics[storage['storage']]['used_percent'] = storage['used'] / storage['total'] * 100
storage_statistics[storage['storage']]['used_percent_last_run'] = 0
storage_statistics[storage['storage']]['free'] = storage['total'] - storage['used']
storage_statistics[storage['storage']]['free_percent'] = storage_statistics[storage['storage']]['free'] / storage['total'] * 100
storage_statistics[storage['storage']]['used_fraction'] = storage['used_fraction']
storage_statistics[storage['storage']]['type'] = storage['type']
storage_statistics[storage['storage']]['content'] = storage['content']
storage_statistics[storage['storage']]['usage_type'] = ''
# Split the Proxmox returned values to a list and validate the supported
# types of the underlying storage for further migrations.
storage_content_list = storage['content'].split(',')
usage_ct = False
usage_vm = False
if 'rootdir' in storage_content_list:
usage_ct = True
storage_statistics[storage['storage']]['usage_type'] = 'ct'
logging.info(f'{info_prefix} Storage {storage["storage"]} support CTs.')
if 'images' in storage_content_list:
usage_vm = True
storage_statistics[storage['storage']]['usage_type'] = 'vm'
logging.info(f'{info_prefix} Storage {storage["storage"]} support VMs.')
if usage_ct and usage_vm:
storage_statistics[storage['storage']]['usage_type'] = 'all'
logging.info(f'{info_prefix} Updateing storage {storage["storage"]} support to CTs and VMs.')
logging.info(f'{info_prefix} Added storage {storage["storage"]}.')
logging.info(f'{info_prefix} Created storage statistics.')
return storage_statistics
def update_node_statistics(node_statistics, vm_statistics):
""" Update node statistics by VMs statistics. """
info_prefix = 'Info: [node-update-statistics]:'
warn_prefix = 'Warning: [node-update-statistics]:'
for vm, vm_value in vm_statistics.items():
node_statistics[vm_value['node_parent']]['cpu_assigned'] = node_statistics[vm_value['node_parent']]['cpu_assigned'] + int(vm_value['cpu_total'])
node_statistics[vm_value['node_parent']]['cpu_assigned_percent'] = (node_statistics[vm_value['node_parent']]['cpu_assigned'] / node_statistics[vm_value['node_parent']]['cpu_total']) * 100
node_statistics[vm_value['node_parent']]['memory_assigned'] = node_statistics[vm_value['node_parent']]['memory_assigned'] + int(vm_value['memory_total'])
node_statistics[vm_value['node_parent']]['memory_assigned_percent'] = (node_statistics[vm_value['node_parent']]['memory_assigned'] / node_statistics[vm_value['node_parent']]['memory_total']) * 100
node_statistics[vm_value['node_parent']]['disk_assigned'] = node_statistics[vm_value['node_parent']]['disk_assigned'] + int(vm_value['disk_total'])
node_statistics[vm_value['node_parent']]['disk_assigned_percent'] = (node_statistics[vm_value['node_parent']]['disk_assigned'] / node_statistics[vm_value['node_parent']]['disk_total']) * 100
if node_statistics[vm_value['node_parent']]['cpu_assigned_percent'] > 99:
logging.warning(f'{warn_prefix} Node {vm_value["node_parent"]} is overprovisioned for CPU by {int(node_statistics[vm_value["node_parent"]]["cpu_assigned_percent"])}%.')
if node_statistics[vm_value['node_parent']]['memory_assigned_percent'] > 99:
logging.warning(f'{warn_prefix} Node {vm_value["node_parent"]} is overprovisioned for memory by {int(node_statistics[vm_value["node_parent"]]["memory_assigned_percent"])}%.')
if node_statistics[vm_value['node_parent']]['disk_assigned_percent'] > 99:
logging.warning(f'{warn_prefix} Node {vm_value["node_parent"]} is overprovisioned for disk by {int(node_statistics[vm_value["node_parent"]]["disk_assigned_percent"])}%.')
logging.info(f'{info_prefix} Updated node resource assignments by all VMs.')
logging.debug('node_statistics')
return node_statistics
def __validate_ignore_vm_wildcard(ignore_vms):
""" Validate if a wildcard is used for ignored VMs. """
if '*' in ignore_vms:
return True
def __check_vm_name_wildcard_pattern(vm_name, ignore_vms_list):
""" Validate if the VM name is in the ignore list pattern included. """
for ignore_vm in ignore_vms_list:
if '*' in ignore_vm:
if ignore_vm[:-1] in vm_name:
return True
def __get_vm_tags(api_object, node, vmid, balancing_type):
""" Get tags for a VM/CT for a given VMID. """
info_prefix = 'Info: [api-get-vm-tags]:'
if balancing_type == 'vm':
vm_config = api_object.nodes(node['node']).qemu(vmid).config.get()
if balancing_type == 'ct':
vm_config = api_object.nodes(node['node']).lxc(vmid).config.get()
logging.info(f'{info_prefix} Got VM/CT tag from API.')
return vm_config.get('tags', None)
def __get_proxlb_groups(vm_tags):
""" Get ProxLB related include and exclude groups. """
info_prefix = 'Info: [api-get-vm-include-exclude-tags]:'
group_include = None
group_exclude = None
vm_ignore = None
group_list = re.split(";", vm_tags)
for group in group_list:
if group.startswith('plb_include_'):
logging.info(f'{info_prefix} Got PLB include group.')
group_include = group
if group.startswith('plb_exclude_'):
logging.info(f'{info_prefix} Got PLB include group.')
group_exclude = group
if group.startswith('plb_ignore_vm'):
logging.info(f'{info_prefix} Got PLB ignore group.')
vm_ignore = True
return group_include, group_exclude, vm_ignore
def balancing_vm_calculations(balancing_method, balancing_mode, balancing_mode_option, node_statistics, vm_statistics, balanciness, rebalance, processed_vms):
""" Calculate re-balancing of VMs on present nodes across the cluster. """
info_prefix = 'Info: [vm-rebalancing-calculator]:'
# Validate for a supported balancing method, mode and if rebalancing is required.
__validate_balancing_method(balancing_method)
__validate_balancing_mode(balancing_mode)
__validate_vm_statistics(vm_statistics)
rebalance = __validate_vm_balanciness(balanciness, balancing_method, balancing_mode, node_statistics)
if rebalance:
# Get most used/assigned resources of the VM and the most free or less allocated node.
resources_vm_most_used, processed_vms = __get_most_used_resources_vm(balancing_method, balancing_mode, vm_statistics, processed_vms)
resources_node_most_free = __get_most_free_resources_node(balancing_method, balancing_mode, balancing_mode_option, node_statistics)
# Update resource statistics for VMs and nodes.
node_statistics, vm_statistics = __update_resource_statistics(resources_vm_most_used, resources_node_most_free,
vm_statistics, node_statistics, balancing_method, balancing_mode)
# Start recursion until we do not have any needs to rebalance anymore.
balancing_vm_calculations(balancing_method, balancing_mode, balancing_mode_option, node_statistics, vm_statistics, balanciness, rebalance, processed_vms)
# Honour groupings for include and exclude groups for rebalancing VMs.
node_statistics, vm_statistics = __get_vm_tags_include_groups(vm_statistics, node_statistics, balancing_method, balancing_mode)
node_statistics, vm_statistics = __get_vm_tags_exclude_groups(vm_statistics, node_statistics, balancing_method, balancing_mode)
# Remove VMs that are not being relocated.
vms_to_remove = [vm_name for vm_name, vm_info in vm_statistics.items() if 'node_rebalance' in vm_info and vm_info['node_rebalance'] == vm_info.get('node_parent')]
for vm_name in vms_to_remove:
del vm_statistics[vm_name]
logging.info(f'{info_prefix} Balancing calculations done.')
return node_statistics, vm_statistics
def balancing_storage_calculations(storage_balancing_method, storage_statistics, vm_statistics, balanciness, rebalance, processed_vms):
""" Calculate re-balancing of storage on present datastores across the cluster. """
info_prefix = 'Info: [storage-rebalancing-calculator]:'
# Validate for a supported balancing method, mode and if rebalancing is required.
__validate_vm_statistics(vm_statistics)
rebalance = __validate_storage_balanciness(balanciness, storage_balancing_method, storage_statistics)
if rebalance:
vm_name, vm_disk_device, vm_disk_name = __get_most_used_resources_vm_storage(vm_statistics)
if vm_name not in processed_vms:
processed_vms.append(vm_name)
resources_storage_most_free = __get_most_free_storage(storage_balancing_method, storage_statistics)
# Update resource statistics for VMs and storage.
storage_statistics, vm_statistics = __update_resource_storage_statistics(storage_statistics, resources_storage_most_free, vm_statistics, vm_name, vm_disk_device)
# Start recursion until we do not have any needs to rebalance anymore.
balancing_storage_calculations(storage_balancing_method, storage_statistics, vm_statistics, balanciness, rebalance, processed_vms)
# Remove VMs where their storage is not being relocated.
vms_to_remove = [vm_name for vm_name, vm_info in vm_statistics.items() if all(storage.get('storage_rebalance') is None for storage in vm_info.get('storages', {}).values())]
for vm_name in vms_to_remove:
del vm_statistics[vm_name]
logging.info(f'{info_prefix} Balancing calculations done.')
return storage_statistics, vm_statistics
def size_in_bytes(size_str):
size_unit = size_str[-1].upper()
size_value = float(size_str[:-1])
size_multipliers = {'K': 1024, 'M': 1024**2, 'G': 1024**3, 'T': 1024**4}
return size_value * size_multipliers.get(size_unit, 1)
def __validate_balancing_method(balancing_method):
""" Validate for valid and supported balancing method. """
error_prefix = 'Error: [balancing-method-validation]:'
info_prefix = 'Info: [balancing-method-validation]:'
if balancing_method not in ['memory', 'disk', 'cpu']:
logging.error(f'{error_prefix} Invalid balancing method: {balancing_method}')
sys.exit(2)
else:
logging.info(f'{info_prefix} Valid balancing method: {balancing_method}')
def __validate_balancing_mode(balancing_mode):
""" Validate for valid and supported balancing mode. """
error_prefix = 'Error: [balancing-mode-validation]:'
info_prefix = 'Info: [balancing-mode-validation]:'
if balancing_mode not in ['used', 'assigned', 'io']:
logging.error(f'{error_prefix} Invalid balancing method: {balancing_mode}')
sys.exit(2)
else:
logging.info(f'{info_prefix} Valid balancing method: {balancing_mode}')
def __validate_vm_statistics(vm_statistics):
""" Validate for at least a single object of type CT/VM to rebalance. """
error_prefix = 'Error: [balancing-vm-stats-validation]:'
if len(vm_statistics) == 0:
logging.error(f'{error_prefix} Not a single CT/VM found in cluster.')
sys.exit(1)
def __validate_vm_balanciness(balanciness, balancing_method, balancing_mode, node_statistics):
""" Validate for balanciness for VMs/CTs to ensure further rebalancing is needed. """
info_prefix = 'Info: [vm-balanciness-validation]:'
node_resource_percent_list = []
node_assigned_percent_match = []
# Remap balancing mode to get the related values from nodes dict.
if balancing_mode == 'used':
node_resource_selector = 'free'
if balancing_mode == 'assigned':
node_resource_selector = 'assigned'
for node_name, node_info in node_statistics.items():
# Save information of nodes from current run to compare them in the next recursion.
if node_statistics[node_name][f'{balancing_method}_{node_resource_selector}_percent_last_run'] == node_statistics[node_name][f'{balancing_method}_{node_resource_selector}_percent']:
node_statistics[node_name][f'{balancing_method}_{node_resource_selector}_percent_match'] = True
else:
node_statistics[node_name][f'{balancing_method}_{node_resource_selector}_percent_match'] = False
# Update value to the current value of the recursion run.
node_statistics[node_name][f'{balancing_method}_{node_resource_selector}_percent_last_run'] = node_statistics[node_name][f'{balancing_method}_{node_resource_selector}_percent']
# If all node resources are unchanged, the recursion can be left.
for key, value in node_statistics.items():
node_assigned_percent_match.append(value.get(f'{balancing_method}_{node_resource_selector}_percent_match', False))
if False not in node_assigned_percent_match:
return False
# Add node information to resource list.
node_resource_percent_list.append(int(node_info[f'{balancing_method}_{node_resource_selector}_percent']))
logging.debug(f'{info_prefix} Node: {node_name} with values: {node_info}')
# Create a sorted list of the delta + balanciness between the node resources.
node_resource_percent_list_sorted = sorted(node_resource_percent_list)
node_lowest_percent = node_resource_percent_list_sorted[0]
node_highest_percent = node_resource_percent_list_sorted[-1]
# Validate if the recursion should be proceeded for further rebalancing.
if (int(node_lowest_percent) + int(balanciness)) < int(node_highest_percent):
logging.info(f'{info_prefix} Rebalancing for {balancing_method} of VMs/CTs is needed. Highest usage: {int(node_highest_percent)}% | Lowest usage: {int(node_lowest_percent)}%.')
return True
else:
logging.info(f'{info_prefix} Rebalancing for {balancing_method} of VMs/CTs is not needed. Highest usage: {int(node_highest_percent)}% | Lowest usage: {int(node_lowest_percent)}%.')
return False
def __validate_storage_balanciness(balanciness, storage_balancing_method, storage_statistics):
""" Validate for balanciness of storage to ensure further rebalancing is needed. """
info_prefix = 'Info: [storage-balanciness-validation]:'
error_prefix = 'Error: [storage-balanciness-validation]:'
storage_resource_percent_list = []
storage_assigned_percent_match = []
# Validate for an allowed balancing method and define the storage resource selector.
if storage_balancing_method == 'disk_space':
logging.info(f'{info_prefix} Getting most free storage volume by disk size..')
storage_resource_selector = 'used'
elif storage_balancing_method == 'disk_io':
logging.error(f'{error_prefix} Getting most free storage volume by disk IO is not yet supported.')
sys.exit(2)
else:
logging.error(f'{error_prefix} Getting most free storage volume by disk IO is not yet supported.')
sys.exit(2)
# Obtain the metrics
for storage_name, storage_info in storage_statistics.items():
logging.info(f'{info_prefix} Validating storage: {storage_name} for balanciness for usage with: {storage_balancing_method}.')
# Save information of nodes from current run to compare them in the next recursion.
if storage_statistics[storage_name][f'{storage_resource_selector}_percent_last_run'] == storage_statistics[storage_name][f'{storage_resource_selector}_percent']:
storage_statistics[storage_name][f'{storage_resource_selector}_percent_match'] = True
else:
storage_statistics[storage_name][f'{storage_resource_selector}_percent_match'] = False
# Update value to the current value of the recursion run.
storage_statistics[storage_name][f'{storage_resource_selector}_percent_last_run'] = storage_statistics[storage_name][f'{storage_resource_selector}_percent']
# If all node resources are unchanged, the recursion can be left.
for key, value in storage_statistics.items():
storage_assigned_percent_match.append(value.get(f'{storage_resource_selector}_percent_match', False))
if False not in storage_assigned_percent_match:
return False
# Add node information to resource list.
storage_resource_percent_list.append(int(storage_info[f'{storage_resource_selector}_percent']))
logging.info(f'{info_prefix} Storage: {storage_name} with values: {storage_info}')
# Create a sorted list of the delta + balanciness between the node resources.
storage_resource_percent_list_sorted = sorted(storage_resource_percent_list)
storage_lowest_percent = storage_resource_percent_list_sorted[0]
storage_highest_percent = storage_resource_percent_list_sorted[-1]
# Validate if the recursion should be proceeded for further rebalancing.
if (int(storage_lowest_percent) + int(balanciness)) < int(storage_highest_percent):
logging.info(f'{info_prefix} Rebalancing for type "{storage_resource_selector}" of storage is needed. Highest usage: {int(storage_highest_percent)}% | Lowest usage: {int(storage_lowest_percent)}%.')
return True
else:
logging.info(f'{info_prefix} Rebalancing for type "{storage_resource_selector}" of storage is not needed. Highest usage: {int(storage_highest_percent)}% | Lowest usage: {int(storage_lowest_percent)}%.')
return False
def __get_most_used_resources_vm(balancing_method, balancing_mode, vm_statistics, processed_vms):
""" Get and return the most used resources of a VM by the defined balancing method. """
info_prefix = 'Info: [get-most-used-resources-vm]:'
# Remap balancing mode to get the related values from nodes dict.
if balancing_mode == 'used':
vm_resource_selector = 'used'
if balancing_mode == 'assigned':
vm_resource_selector = 'total'
vm = max(vm_statistics.items(), key=lambda item: item[1][f'{balancing_method}_{vm_resource_selector}'] if item[0] not in processed_vms else -float('inf'))
processed_vms.append(vm[0])
logging.info(f'{info_prefix} {vm}')
return vm, processed_vms
def __get_most_free_resources_node(balancing_method, balancing_mode, balancing_mode_option, node_statistics):
""" Get and return the most free resources of a node by the defined balancing method. """
info_prefix = 'Info: [get-most-free-resources-nodes]:'
# Return the node information based on the balancing mode.
if balancing_mode == 'used' and balancing_mode_option == 'bytes':
node = max(node_statistics.items(), key=lambda item: item[1][f'{balancing_method}_free'])
if balancing_mode == 'used' and balancing_mode_option == 'percent':
node = max(node_statistics.items(), key=lambda item: item[1][f'{balancing_method}_free_percent'])
if balancing_mode == 'assigned':
node = min(node_statistics.items(), key=lambda item: item[1][f'{balancing_method}_assigned'] if item[1][f'{balancing_method}_assigned_percent'] > 0 or item[1][f'{balancing_method}_assigned_percent'] < 100 else -float('inf'))
logging.info(f'{info_prefix} {node}')
return node
def __get_most_used_resources_vm_storage(vm_statistics):
""" Get and return the most used disk of a VM by storage. """
info_prefix = 'Info: [get-most-used-disks-resources-vm]:'
biggest_entry = None
vm_name = None
max_size = 0
# Get the biggest storage of a VM/CT. A VM/CT can hold multiple disks. Therefore, we need to iterate
# over all assigned disks to get the biggest one.
vm_biggest_storage = sorted(
vm_statistics.items(),
key=lambda x: max(
(size_in_bytes(storage['size']) for storage in x[1].get('storages', {}).values() if 'size' in storage),
default=0
),
reverse=True
)
# Iterate over all attached disks to the VM that were returned for the VM object holding the biggest disk.
# Return: disk name and parent stroage volume for further calculations and migrations
for key, value in vm_biggest_storage[0][1]['storages'].items():
if 'size' in value and value['size']:
size_str = value['size'].upper()
if size_str.endswith('G'):
size = float(size_str[:-1]) * 1024 # Convert GB to MB
elif size_str.endswith('M'):
size = float(size_str[:-1])
elif size_str.endswith('T'):
size = float(size_str[:-1]) * 1024 * 1024 # Convert TB to MB
else:
size = 0
if size > max_size:
max_size = size
vm_name = vm_biggest_storage[0][0]
biggest_entry = value
if biggest_entry:
return vm_name, biggest_entry['device_name'], biggest_entry['storage_parent']
else:
return None
def __get_most_free_storage(storage_balancing_method, storage_statistics):
""" Get the storage with the most free space or IO, depending on the balancing mode. """
info_prefix = 'Info: [get-most-free-storage]:'
error_prefix = 'Error: [get-most-free-storage]:'
storage_volume = None
logging.info(f'{info_prefix} Starting to evaluate the most free storage volume.')
if storage_balancing_method == 'disk_space':
logging.info(f'{info_prefix} Getting most free storage volume by disk space.')
storage_volume = max(storage_statistics, key=lambda x: storage_statistics[x]['free_percent'])
if storage_balancing_method == 'disk_io':
logging.info(f'{info_prefix} Getting most free storage volume by disk IO.')
logging.error(f'{error_prefix} Getting most free storage volume by disk IO is not yet supported.')
sys.exit(2)
return storage_volume
def __update_resource_statistics(resource_highest_used_resources_vm, resource_highest_free_resources_node, vm_statistics, node_statistics, balancing_method, balancing_mode):
""" Update VM and node resource statistics. """
info_prefix = 'Info: [rebalancing-resource-statistics-update]:'
if resource_highest_used_resources_vm[1]['node_parent'] != resource_highest_free_resources_node[0]:
vm_name = resource_highest_used_resources_vm[0]
vm_node_parent = resource_highest_used_resources_vm[1]['node_parent']
vm_node_rebalance = resource_highest_free_resources_node[0]
vm_resource_used = vm_statistics[resource_highest_used_resources_vm[0]][f'{balancing_method}_used']
vm_resource_total = vm_statistics[resource_highest_used_resources_vm[0]][f'{balancing_method}_total']
# Update dictionaries for new values
# Assign new rebalance node to vm
vm_statistics[vm_name]['node_rebalance'] = vm_node_rebalance
logging.info(f'Moving {vm_name} from {vm_node_parent} to {vm_node_rebalance}')
# Recalculate values for nodes
## Add freed resources to old parent node
node_statistics[vm_node_parent][f'{balancing_method}_used'] = int(node_statistics[vm_node_parent][f'{balancing_method}_used']) - int(vm_resource_used)
node_statistics[vm_node_parent][f'{balancing_method}_free'] = int(node_statistics[vm_node_parent][f'{balancing_method}_free']) + int(vm_resource_used)
node_statistics[vm_node_parent][f'{balancing_method}_free_percent'] = int(int(node_statistics[vm_node_parent][f'{balancing_method}_free']) / int(node_statistics[vm_node_parent][f'{balancing_method}_total']) * 100)
node_statistics[vm_node_parent][f'{balancing_method}_assigned'] = int(node_statistics[vm_node_parent][f'{balancing_method}_assigned']) - int(vm_resource_total)
node_statistics[vm_node_parent][f'{balancing_method}_assigned_percent'] = int(int(node_statistics[vm_node_parent][f'{balancing_method}_assigned']) / int(node_statistics[vm_node_parent][f'{balancing_method}_total']) * 100)
## Removed newly allocated resources to new rebalanced node
node_statistics[vm_node_rebalance][f'{balancing_method}_used'] = int(node_statistics[vm_node_rebalance][f'{balancing_method}_used']) + int(vm_resource_used)
node_statistics[vm_node_rebalance][f'{balancing_method}_free'] = int(node_statistics[vm_node_rebalance][f'{balancing_method}_free']) - int(vm_resource_used)
node_statistics[vm_node_rebalance][f'{balancing_method}_free_percent'] = int(int(node_statistics[vm_node_rebalance][f'{balancing_method}_free']) / int(node_statistics[vm_node_rebalance][f'{balancing_method}_total']) * 100)
node_statistics[vm_node_rebalance][f'{balancing_method}_assigned'] = int(node_statistics[vm_node_rebalance][f'{balancing_method}_assigned']) + int(vm_resource_total)
node_statistics[vm_node_rebalance][f'{balancing_method}_assigned_percent'] = int(int(node_statistics[vm_node_rebalance][f'{balancing_method}_assigned']) / int(node_statistics[vm_node_rebalance][f'{balancing_method}_total']) * 100)
logging.info(f'{info_prefix} Updated VM and node statistics.')
return node_statistics, vm_statistics
def __update_resource_storage_statistics(storage_statistics, resources_storage_most_free, vm_statistics, vm_name, vm_disk_device):
""" Update VM and storage resource statistics. """
info_prefix = 'Info: [rebalancing-storage-resource-statistics-update]:'
current_storage = vm_statistics[vm_name]['storages'][vm_disk_device]['storage_parent']
rebalance_storage = resources_storage_most_free
vm_storage_size = vm_statistics[vm_name]['storages'][vm_disk_device]['size'][:-1]
vm_storage_size_bytes = int(vm_storage_size) * 1024**3
# Assign new storage device to vm
logging.info(f'{info_prefix} Validating VM {vm_name} for potential storage rebalancing.')
if vm_statistics[vm_name]['storages'][vm_disk_device]['storage_rebalance'] is None and vm_statistics[vm_name]['storages'][vm_disk_device]['storage_rebalance'] != vm_statistics[vm_name]['storages'][vm_disk_device]['storage_parent']:
logging.info(f'{info_prefix} Setting VM {vm_name} from {current_storage} to {rebalance_storage} storage.')
vm_statistics[vm_name]['storages'][vm_disk_device]['storage_rebalance'] = resources_storage_most_free
else:
logging.info(f'{info_prefix} Setting VM {vm_name} from {current_storage} to {rebalance_storage} storage.')
# Recalculate values for storage
## Add freed resources to old parent storage device
storage_statistics[current_storage]['used'] = storage_statistics[current_storage]['used'] - vm_storage_size_bytes
storage_statistics[current_storage]['free'] = storage_statistics[current_storage]['free'] + vm_storage_size_bytes
storage_statistics[current_storage]['free_percent'] = (storage_statistics[current_storage]['free'] / storage_statistics[current_storage]['total']) * 100
storage_statistics[current_storage]['used_percent'] = (storage_statistics[current_storage]['used'] / storage_statistics[current_storage]['total']) * 100
## Removed newly allocated resources to new rebalanced storage device
storage_statistics[rebalance_storage]['used'] = storage_statistics[rebalance_storage]['used'] + vm_storage_size_bytes
storage_statistics[rebalance_storage]['free'] = storage_statistics[rebalance_storage]['free'] - vm_storage_size_bytes
storage_statistics[rebalance_storage]['free_percent'] = (storage_statistics[rebalance_storage]['free'] / storage_statistics[rebalance_storage]['total']) * 100
storage_statistics[rebalance_storage]['used_percent'] = (storage_statistics[rebalance_storage]['used'] / storage_statistics[rebalance_storage]['total']) * 100
logging.info(f'{info_prefix} Updated VM and storage statistics.')
return storage_statistics, vm_statistics
def __get_vm_tags_include_groups(vm_statistics, node_statistics, balancing_method, balancing_mode):
""" Get VMs tags for include groups. """
info_prefix = 'Info: [rebalancing-tags-group-include]:'
tags_include_vms = {}
processed_vm = []
# Create groups of tags with belongings hosts.
for vm_name, vm_values in vm_statistics.items():
if vm_values.get('group_include', None):
if not tags_include_vms.get(vm_values['group_include'], None):
tags_include_vms[vm_values['group_include']] = [vm_name]
else:
tags_include_vms[vm_values['group_include']] = tags_include_vms[vm_values['group_include']] + [vm_name]
# Update the VMs to the corresponding node to their group assignments.
for group, vm_names in tags_include_vms.items():
# Do not take care of tags that have only a single host included.
if len(vm_names) < 2:
logging.info(f'{info_prefix} Only one host in group assignment.')
return node_statistics, vm_statistics
vm_node_rebalance = False
logging.info(f'{info_prefix} Create include groups of VM hosts.')
for vm_name in vm_names:
if vm_name not in processed_vm:
if not vm_node_rebalance:
vm_node_rebalance = vm_statistics[vm_name]['node_rebalance']
else:
_mocked_vm_object = (vm_name, vm_statistics[vm_name])
node_statistics, vm_statistics = __update_resource_statistics(_mocked_vm_object, [vm_node_rebalance], vm_statistics, node_statistics, balancing_method, balancing_mode)
processed_vm.append(vm_name)
return node_statistics, vm_statistics
def __get_vm_tags_exclude_groups(vm_statistics, node_statistics, balancing_method, balancing_mode):
""" Get VMs tags for exclude groups. """
info_prefix = 'Info: [rebalancing-tags-group-exclude]:'
tags_exclude_vms = {}
processed_vm = []
# Create groups of tags with belongings hosts.
for vm_name, vm_values in vm_statistics.items():
if vm_values.get('group_include', None):
if not tags_exclude_vms.get(vm_values['group_include'], None):
tags_exclude_vms[vm_values['group_include']] = [vm_name]
else:
tags_exclude_vms[vm_values['group_include']] = tags_exclude_vms[vm_values['group_include']] + [vm_name]
# Update the VMs to the corresponding node to their group assignments.
for group, vm_names in tags_exclude_vms.items():
# Do not take care of tags that have only a single host included.
if len(vm_names) < 2:
logging.info(f'{info_prefix} Only one host in group assignment.')
return node_statistics, vm_statistics
vm_node_rebalance = False
logging.info(f'{info_prefix} Create exclude groups of VM hosts.')
for vm_name in vm_names:
if vm_name not in processed_vm:
if not vm_node_rebalance:
random_node = vm_statistics[vm_name]['node_parent']
# Get a random node and make sure that it is not by accident the
# currently assigned one.
while random_node == vm_statistics[vm_name]['node_parent']:
random_node = random.choice(list(node_statistics.keys()))
else:
_mocked_vm_object = (vm_name, vm_statistics[vm_name])
node_statistics, vm_statistics = __update_resource_statistics(_mocked_vm_object, [random_node], vm_statistics, node_statistics, balancing_method, balancing_mode)
processed_vm.append(vm_name)
return node_statistics, vm_statistics
def __wait_job_finalized(api_object, node_name, job_id, counter):
""" Wait for a job to be finalized. """
error_prefix = 'Error: [job-status-getter]:'
info_prefix = 'Info: [job-status-getter]:'
logging.info(f'{info_prefix} Getting job status for job {job_id}.')
task = api_object.nodes(node_name).tasks(job_id).status().get()
logging.info(f'{info_prefix} {task}')
if task['status'] == 'running':
logging.info(f'{info_prefix} Validating job {job_id} for the {counter} run.')
# Do not run for infinity this recursion and fail when reaching the limit.
if counter == 300:
logging.critical(f'{error_prefix} The job {job_id} on node {node_name} did not finished in time for migration.')
time.sleep(5)
counter = counter + 1
logging.info(f'{info_prefix} Revalidating job {job_id} in a next run.')
__wait_job_finalized(api_object, node_name, job_id, counter)
logging.info(f'{info_prefix} Job {job_id} for migration from {node_name} terminiated succesfully.')
def __run_vm_rebalancing(api_object, vm_statistics, app_args, parallel_migrations):
""" Run & execute the VM rebalancing via API. """
error_prefix = 'Error: [rebalancing-executor]:'
info_prefix = 'Info: [rebalancing-executor]:'
if len(vm_statistics) > 0 and not app_args.dry_run:
for vm, value in vm_statistics.items():
try:
# Migrate type VM (live migration).
if value['type'] == 'vm':
logging.info(f'{info_prefix} Rebalancing VM {vm} from node {value["node_parent"]} to node {value["node_rebalance"]}.')
job_id = api_object.nodes(value['node_parent']).qemu(value['vmid']).migrate().post(target=value['node_rebalance'],online=1)
# Migrate type CT (requires restart of container).
if value['type'] == 'ct':
logging.info(f'{info_prefix} Rebalancing CT {vm} from node {value["node_parent"]} to node {value["node_rebalance"]}.')
job_id = api_object.nodes(value['node_parent']).lxc(value['vmid']).migrate().post(target=value['node_rebalance'],restart=1)
except proxmoxer.core.ResourceException as error_resource:
logging.critical(f'{error_prefix} {error_resource}')
# Wait for migration to be finished unless running parallel migrations.
if not bool(int(parallel_migrations)):
logging.info(f'{info_prefix} Rebalancing will be performed sequentially.')
__wait_job_finalized(api_object, value['node_parent'], job_id, counter=1)
else:
logging.info(f'{info_prefix} Rebalancing will be performed parallely.')
else:
logging.info(f'{info_prefix} No rebalancing needed.')
def __run_storage_rebalancing(api_object, vm_statistics, app_args, parallel_migrations):
""" Run & execute the storage rebalancing via API. """
error_prefix = 'Error: [rebalancing-executor]:'
info_prefix = 'Info: [rebalancing-executor]:'
if len(vm_statistics) > 0 and not app_args.dry_run:
for vm, value in vm_statistics.items():
for disk, disk_info in value['storages'].items():
if disk_info.get('storage_rebalance', None) is not None:
try:
# Migrate type VM (live migration).
logging.info(f'{info_prefix} Rebalancing storage of VM {vm} from node.')
job_id = api_object.nodes(value['node_parent']).qemu(value['vmid']).move_disk().post(disk=disk,storage=disk_info.get('storage_rebalance', None), delete=1)
except proxmoxer.core.ResourceException as error_resource:
logging.critical(f'{error_prefix} {error_resource}')
# Wait for migration to be finished unless running parallel migrations.
if not bool(int(parallel_migrations)):
logging.info(f'{info_prefix} Rebalancing will be performed sequentially.')
__wait_job_finalized(api_object, value['node_parent'], job_id, counter=1)
else:
logging.info(f'{info_prefix} Rebalancing will be performed parallely.')
else:
logging.info(f'{info_prefix} No rebalancing needed.')
def __create_json_output(vm_statistics_rebalanced, app_args):
""" Create a machine parsable json output of VM rebalance statitics. """
info_prefix = 'Info: [json-output-generator]:'
if app_args.json:
logging.info(f'{info_prefix} Printing json output of VM statistics.')
print(json.dumps(vm_statistics_rebalanced))
def __create_cli_output(vm_statistics_rebalanced, app_args):
""" Create output for CLI when running in dry-run mode. """
info_prefix_dry_run = 'Info: [cli-output-generator-dry-run]:'
info_prefix_run = 'Info: [cli-output-generator]:'
vm_to_node_list = []
if app_args.dry_run:
info_prefix = info_prefix_dry_run
logging.info(f'{info_prefix} Starting dry-run to rebalance vms to their new nodes.')
else:
info_prefix = info_prefix_run
logging.info(f'{info_prefix} Start rebalancing vms to their new nodes.')
vm_to_node_list.append(['VM', 'Current Node', 'Rebalanced Node', 'Current Storage', 'Rebalanced Storage', 'VM Type'])
for vm_name, vm_values in vm_statistics_rebalanced.items():
for disk, disk_info in vm_values['storages'].items():
vm_to_node_list.append([vm_name, vm_values['node_parent'], vm_values['node_rebalance'], disk_info.get('storage_parent', 'NA'), disk_info.get('storage_rebalance', 'NA'), vm_values['type']])
if len(vm_statistics_rebalanced) > 0:
logging.info(f'{info_prefix} Printing cli output of VM rebalancing.')
__print_table_cli(vm_to_node_list, app_args.dry_run)
else:
logging.info(f'{info_prefix} No rebalancing needed.')
def __print_table_cli(table, dry_run=False):
""" Pretty print a given table to the cli. """
info_prefix_dry_run = 'Info: [cli-output-generator-table-dryn-run]:'
info_prefix_run = 'Info: [cli-output-generator-table]:'
info_prefix = info_prefix_run
longest_cols = [
(max([len(str(row[i])) for row in table]) + 3)
for i in range(len(table[0]))
]
row_format = "".join(["{:>" + str(longest_col) + "}" for longest_col in longest_cols])
for row in table:
# Print CLI output when running in dry-run mode to make the user's life easier.
if dry_run:
info_prefix = info_prefix_dry_run
print(row_format.format(*row))
# Log all items in info mode.
logging.info(f'{info_prefix} {row_format.format(*row)}')
def run_rebalancing(api_object, vm_statistics, app_args, parallel_migrations, balance_type):
""" Run rebalancing of vms to new nodes in cluster. """
error_prefix = 'Error: [rebalancing-executor]:'
info_prefix = 'Info: [rebalancing-executor]:'
if balance_type == 'vm':
logging.info(f'{info_prefix} Starting executor for type vm.')
__run_vm_rebalancing(api_object, vm_statistics, app_args, parallel_migrations)
if balance_type == 'storage':
logging.info(f'{info_prefix} Starting executor for type vm.')
__run_storage_rebalancing(api_object, vm_statistics, app_args, parallel_migrations)
__create_json_output(vm_statistics, app_args)
__create_cli_output(vm_statistics, app_args)
def main():
""" Run ProxLB for balancing VM workloads across a Proxmox cluster. """
# Initialize PAS.
initialize_logger('CRITICAL')
app_args = initialize_args()
config_path = initialize_config_path(app_args)
pre_validations(config_path)
# Parse global config.
proxmox_api_host, proxmox_api_user, proxmox_api_pass, proxmox_api_ssl_v, vm_balancing_enable, vm_balancing_method, vm_balancing_mode, vm_balancing_mode_option, vm_balancing_type, vm_balanciness, vm_parallel_migrations, vm_ignore_nodes, vm_ignore_vms, storage_balancing_enable, storage_balancing_method, storage_balancing_balanciness, storage_parallel_migrations, master_only, daemon, schedule, log_verbosity = initialize_config_options(config_path)
# Overwrite logging handler with user defined log verbosity.
initialize_logger(log_verbosity, update_log_verbosity=True)
while True:
# API Authentication.
api_object = api_connect(proxmox_api_host, proxmox_api_user, proxmox_api_pass, proxmox_api_ssl_v)
# Get master node of cluster and ensure that ProxLB is only performed on the
# cluster master node to avoid ongoing rebalancing.
cluster_master, master_only = execute_rebalancing_only_by_master(api_object, master_only)
# Validate daemon service and skip following tasks when not being the cluster master.
if not cluster_master and master_only:
validate_daemon(daemon, schedule)
continue
# Get metric & statistics for vms and nodes.
node_statistics = get_node_statistics(api_object, vm_ignore_nodes)
vm_statistics = get_vm_statistics(api_object, vm_ignore_vms, vm_balancing_type)
storage_statistics = get_storage_statistics(api_object)
node_statistics = update_node_statistics(node_statistics, vm_statistics)
# Calculate rebalancing of vms.
vm_balancing_enable = False
if vm_balancing_enable:
node_statistics, vm_statistics = balancing_vm_calculations(vm_balancing_method, vm_balancing_mode, vm_balancing_mode_option, node_statistics, vm_statistics, vm_balanciness, rebalance=False, processed_vms=[])
run_rebalancing(api_object, vm_statistics, app_args, vm_parallel_migrations, balance_type='vm')
# Calculate rebalancing of storage.
storage_balancing_enable = True
#storage_balancing_method = 'disk_space'
if storage_balancing_enable:
storage_statistics, vm_statistics = balancing_storage_calculations(storage_balancing_method, storage_statistics, vm_statistics, storage_balancing_balanciness, rebalance=False, processed_vms=[])
run_rebalancing(api_object, vm_statistics, app_args, storage_parallel_migrations, balance_type='storage')
# Validate for any errors.
post_validations()
# Validate daemon service.
validate_daemon(daemon, schedule)
if __name__ == '__main__':
main()