122 lines
4.3 KiB
Python
122 lines
4.3 KiB
Python
from rich.console import Console
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from rich.table import Table
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from rich.progress import Progress
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from database import fetch_all
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from kubernetes import client, config
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import requests
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from datetime import datetime, timezone
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# Define constants
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THINK_K8S_URL = "http://localhost:8000/think/k8s"
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console = Console()
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# Helper functions for conversions
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def calculate_time_on_duty(creation_timestamp):
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"""
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Calculate the time on duty in hours, days, or minutes from the creation timestamp.
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"""
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now = datetime.now(timezone.utc)
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delta = now - creation_timestamp
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if delta.days < 1 and delta.seconds < 3600:
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minutes = delta.seconds // 60
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return f"{minutes} minutes" if minutes > 1 else "less than a minute"
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if delta.days < 1:
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hours = delta.seconds // 3600
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return f"{hours} hours" if hours > 1 else "1 hour"
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return f"{delta.days} days" if delta.days > 1 else "1 day"
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def convert_cpu_to_cores(cpu):
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if "n" in cpu:
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return round(int(cpu.replace("n", "")) / 1e9, 4)
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elif "u" in cpu:
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return round(int(cpu.replace("u", "")) / 1e6, 4)
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elif "m" in cpu:
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return round(int(cpu.replace("m", "")) / 1000, 4)
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return float(cpu)
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def convert_memory_to_mib(memory):
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if "Ki" in memory:
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return int(memory.replace("Ki", "")) / 1024
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elif "Mi" in memory:
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return int(memory.replace("Mi", ""))
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elif "Gi" in memory:
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return int(memory.replace("Gi", "")) * 1024
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return float(memory)
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def convert_memory_to_gb(memory):
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if "Ki" in memory:
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return int(memory.replace("Ki", "")) / (1024 ** 2)
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elif "Mi" in memory:
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return int(memory.replace("Mi", "")) / 1024
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elif "Gi" in memory:
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return int(memory.replace("Gi", ""))
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return float(memory)
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# Display tables
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def display_kubernetes_nodes():
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config.load_incluster_config()
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v1 = client.CoreV1Api()
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table = Table(title="📦 Kubernetes Nodes", style="bold yellow")
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table.add_column("Node Name", style="white")
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table.add_column("CPU", justify="right", style="yellow")
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table.add_column("Memory (MiB)", justify="right", style="cyan")
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table.add_column("Storage (GB)", justify="right", style="green")
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table.add_column("Instance Type", style="blue")
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table.add_column("Pods Allocatable", justify="right", style="magenta")
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table.add_column("Time on Duty", justify="right", style="magenta")
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nodes = v1.list_node()
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for node in nodes.items:
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ephemeral_storage = node.status.capacity.get("ephemeral-storage", "0")
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instance_type = node.metadata.labels.get("beta.kubernetes.io/instance-type", "N/A")
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creation_timestamp = node.metadata.creation_timestamp
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table.add_row(
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node.metadata.name,
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node.status.capacity.get("cpu"),
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f"{round(convert_memory_to_mib(node.status.capacity.get('memory')), 2)}",
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f"{round(convert_memory_to_gb(ephemeral_storage), 2)}",
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instance_type,
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node.status.allocatable.get("pods"),
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calculate_time_on_duty(creation_timestamp) if creation_timestamp else "N/A"
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)
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console.print(table)
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# Fetch and display AI summary
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def fetch_ai_summary():
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with Progress() as progress:
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task = progress.add_task("[cyan]Thinking about Kubernetes...", total=100)
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try:
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for _ in range(10): # Simulate progress
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progress.update(task, advance=10)
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import time; time.sleep(0.1)
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response = requests.get(THINK_K8S_URL)
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progress.update(task, completed=100)
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if response.status_code == 200:
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data = response.json()
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return data.get("summary", "No summary provided.")
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else:
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return f"Failed to fetch summary: {response.status_code} {response.text}"
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except requests.RequestException as e:
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return f"An error occurred while fetching the summary: {str(e)}"
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def display_ai_summary():
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summary = fetch_ai_summary()
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console.print("\n[bold magenta]AI Summary of Kubernetes Cluster:[/bold magenta]")
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console.print(f"[green]{summary}[/green]\n")
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if __name__ == "__main__":
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console.print("✨ [bold green]Welcome to the Metal Check Dashboard![/bold green] ✨\n")
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display_metal_nodes()
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display_virtual_machines()
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display_kubernetes_nodes()
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display_namespace_usage()
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display_ai_summary()
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