parallelvirtualcluster
/
pvc
1
0
Fork 0
Code Issues 15 Pull Requests Projects Releases 106 Wiki Activity

Add total cluster utilization stats 

Useful for evaluating the cluster resources as a whole.
This commit is contained in:
Joshua Boniface 2024-09-05 13:41:01 -04:00
parent 7543eb839d
commit 2de999c700
3 changed files with 203 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

57
api-daemon/pvcapid/flaskapi.py
View File

@ -576,6 +576,63 @@ class API_Status(Resource):
snapshots:
type: integer
description: The total number of snapshots in the storage cluster
resources:
type: object
properties:
memory:
type: object
properties:
total:
type: integer
description: The total amount of RAM (all nodes) in MB
used:
type: integer
description: The total used RAM (all nodes) in MB
free:
type: integer
description: The total free RAM (all nodes) in MB
allocated:
type: integer
description: The total amount of RAM allocated to running domains in MB
provisioned:
type: integer
description: The total amount of RAM provisioned to all domains (regardless of state) in MB
utilization:
type: float
description: The memory utilization percentage (average) of the cluster
vcpu:
type: object
properties:
total:
type: integer
description: The total number of real CPU cores (all nodes)
load:
type: float
description: The current 5-minute CPU load (all nodes summed)
allocated:
type: integer
description: The total number of vCPUs allocated to running domains
provisioned:
type: integer
description: The total number of vCPUs provisioned to all domains (regardless of state)
utilization:
type: float
description: The CPU utilization percentage (average) of the cluster
disk:
type: object
properties:
total:
type: integer
description: The total size of all OSDs in KB
used:
type: integer
description: The total used size of all OSDs in KB
free:
type: integer
description: The total free size of all OSDs in KB
utilization:
type: float
description: The disk utilization percentage (average) of the cluster
400:
description: Bad request
"""

37
client-cli/pvc/cli/formatters.py
View File

@ -83,6 +83,37 @@ def cli_cluster_status_format_pretty(CLI_CONFIG, data):
total_volumes = data.get("volumes", 0)
total_snapshots = data.get("snapshots", 0)
total_cpu_total = data.get("resources", {}).get("cpu", {}).get("total", 0)
total_cpu_load = data.get("resources", {}).get("cpu", {}).get("load", 0)
total_cpu_utilization = (
data.get("resources", {}).get("cpu", {}).get("utilization", 0)
)
total_cpu_str = (
f"{total_cpu_utilization:.1f}% ({total_cpu_load:.1f} / {total_cpu_total})"
)
total_memory_total = (
data.get("resources", {}).get("memory", {}).get("total", 0) / 1024
)
total_memory_used = (
data.get("resources", {}).get("memory", {}).get("used", 0) / 1024
)
total_memory_utilization = (
data.get("resources", {}).get("memory", {}).get("utilization", 0)
)
total_memory_str = f"{total_memory_utilization:.1f}% ({total_memory_used:.1f} GB / {total_memory_total:.1f} GB)"
total_disk_total = (
data.get("resources", {}).get("disk", {}).get("total", 0) / 1024 / 1024
)
total_disk_used = (
data.get("resources", {}).get("disk", {}).get("used", 0) / 1024 / 1024
)
total_disk_utilization = round(
data.get("resources", {}).get("disk", {}).get("utilization", 0)
)
total_disk_str = f"{total_disk_utilization:.1f}% ({total_disk_used:.1f} GB / {total_disk_total:.1f} GB)"
if maintenance == "true" or health == -1:
health_colour = ansii["blue"]
elif health > 90:
@ -234,6 +265,12 @@ def cli_cluster_status_format_pretty(CLI_CONFIG, data):
output.append("")
output.append(f"{ansii['purple']}CPU Usage:{ansii['end']} {total_cpu_str}")
output.append(f"{ansii['purple']}Memory Usage:{ansii['end']} {total_memory_str}")
output.append(f"{ansii['purple']}Disk Usage:{ansii['end']} {total_disk_str}")
return "\n".join(output)

111
daemon-common/cluster.py
View File

@ -262,6 +262,22 @@ def getClusterInformation(zkhandler):
# Get cluster maintenance state
maintenance_state = zkhandler.read("base.config.maintenance")
# Prepare cluster total values
cluster_total_node_memory = 0
cluster_total_used_memory = 0
cluster_total_free_memory = 0
cluster_total_allocated_memory = 0
cluster_total_provisioned_memory = 0
cluster_total_average_memory_utilization = 0
cluster_total_cpu_cores = 0
cluster_total_cpu_load = 0
cluster_total_average_cpu_utilization = 0
cluster_total_allocated_cores = 0
cluster_total_osd_space = 0
cluster_total_used_space = 0
cluster_total_free_space = 0
cluster_total_average_osd_utilization = 0
# Get primary node
maintenance_state, primary_node = zkhandler.read_many(
[
@ -276,19 +292,36 @@ def getClusterInformation(zkhandler):
# Get the list of Nodes
node_list = zkhandler.children("base.node")
node_count = len(node_list)
# Get the daemon and domain states of all Nodes
# Get the information of all Nodes
node_state_reads = list()
node_memory_reads = list()
node_cpu_reads = list()
for node in node_list:
node_state_reads += [
("node.state.daemon", node),
("node.state.domain", node),
]
node_memory_reads += [
("node.memory.total", node),
("node.memory.used", node),
("node.memory.free", node),
("node.memory.allocated", node),
("node.memory.provisioned", node),
]
node_cpu_reads += [
("node.data.static", node),
("node.vcpu.allocated", node),
("node.cpu.load", node),
]
all_node_states = zkhandler.read_many(node_state_reads)
all_node_memory = zkhandler.read_many(node_memory_reads)
all_node_cpu = zkhandler.read_many(node_cpu_reads)
# Parse out the Node states
node_data = list()
formatted_node_states = {"total": node_count}
for nidx, node in enumerate(node_list):
# Split the large list of return values by the IDX of this node
# Split the large list of return values by the IDX of this node (states)
# Each node result is 2 fields long
pos_start = nidx * 2
pos_end = nidx * 2 + 2
@ -308,6 +341,46 @@ def getClusterInformation(zkhandler):
else:
formatted_node_states[node_state] = 1
# Split the large list of return values by the IDX of this node (memory)
# Each node result is 5 fields long
pos_start = nidx * 5
pos_end = nidx * 5 + 5
(
node_memory_total,
node_memory_used,
node_memory_free,
node_memory_allocated,
node_memory_provisioned,
) = tuple(all_node_memory[pos_start:pos_end])
cluster_total_node_memory += int(node_memory_total)
cluster_total_used_memory += int(node_memory_used)
cluster_total_free_memory += int(node_memory_free)
cluster_total_allocated_memory += int(node_memory_allocated)
cluster_total_provisioned_memory += int(node_memory_provisioned)
# Split the large list of return values by the IDX of this node (cpu)
# Each nod result is 3 fields long
pos_start = nidx * 3
pos_end = nidx * 3 + 3
node_static_data, node_vcpu_allocated, node_cpu_load = tuple(
all_node_cpu[pos_start:pos_end]
)
cluster_total_cpu_cores += int(node_static_data.split()[0])
cluster_total_cpu_load += round(float(node_cpu_load), 2)
cluster_total_allocated_cores += int(node_vcpu_allocated)
cluster_total_average_memory_utilization = (
(round((cluster_total_used_memory / cluster_total_node_memory) * 100, 2))
if cluster_total_node_memory > 0
else 0.00
)
cluster_total_average_cpu_utilization = (
(round((cluster_total_cpu_load / cluster_total_cpu_cores) * 100, 2))
if cluster_total_cpu_cores > 0
else 0.00
)
# Get the list of VMs
vm_list = zkhandler.children("base.domain")
vm_count = len(vm_list)
@ -380,6 +453,18 @@ def getClusterInformation(zkhandler):
else:
formatted_osd_states[osd_state] = 1
# Add the OSD utilization
cluster_total_osd_space += int(osd_stats["kb"])
cluster_total_used_space += int(osd_stats["kb_used"])
cluster_total_free_space += int(osd_stats["kb_avail"])
cluster_total_average_osd_utilization += float(osd_stats["utilization"])
cluster_total_average_osd_utilization = (
(round(cluster_total_average_osd_utilization / len(ceph_osd_list), 2))
if ceph_osd_list
else 0.00
)
# Get the list of Networks
network_list = zkhandler.children("base.network")
network_count = len(network_list)
@ -424,6 +509,28 @@ def getClusterInformation(zkhandler):
"pools": ceph_pool_count,
"volumes": ceph_volume_count,
"snapshots": ceph_snapshot_count,
"resources": {
"memory": {
"total": cluster_total_node_memory,
"free": cluster_total_free_memory,
"used": cluster_total_used_memory,
"allocated": cluster_total_allocated_memory,
"provisioned": cluster_total_provisioned_memory,
"utilization": cluster_total_average_memory_utilization,
},
"cpu": {
"total": cluster_total_cpu_cores,
"load": cluster_total_cpu_load,
"allocated": cluster_total_allocated_cores,
"utilization": cluster_total_average_cpu_utilization,
},
"disk": {
"total": cluster_total_osd_space,
"used": cluster_total_used_space,
"free": cluster_total_free_space,
"utilization": cluster_total_average_osd_utilization,
},
},
"detail": {
"node": node_data,
"vm": vm_data,