Cloud Resource Utilization

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

fig, ax = plt.subplots(figsize=(12, 8), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

np.random.seed(42)
services = ['EC2', 'Lambda', 'S3', 'RDS', 'DynamoDB', 'ElastiCache', 'EKS']
regions = ['us-east-1', 'us-west-2', 'eu-west-1', 'ap-southeast-1', 'ap-northeast-1']
data = np.random.randint(10, 95, (len(services), len(regions)))

# Modern gradient: Purple to Blue (AWS-inspired)
colors = ['#ede9fe', '#a78bfa', '#7c3aed', '#4f46e5', '#1e1b4b']
cmap = LinearSegmentedColormap.from_list('modern', colors, N=256)

im = ax.imshow(data, cmap=cmap, aspect='auto', vmin=0, vmax=100)

ax.set_xticks(range(len(regions)))
ax.set_yticks(range(len(services)))
ax.set_xticklabels(regions, rotation=45, ha='right', color='#374151', fontsize=9)
ax.set_yticklabels(services, color='#1f2937', fontsize=10, fontweight='500', family='monospace')

for i in range(len(services)):
    for j in range(len(regions)):
        val = data[i, j]
        color = '#ffffff' if val > 50 else '#1f2937'
        ax.text(j, i, f'{val}%', ha='center', va='center', color=color, fontsize=10, fontweight='bold')

cbar = plt.colorbar(im, ax=ax, shrink=0.8, pad=0.02)
cbar.set_label('Utilization (%)', color='#1f2937', fontsize=11)
cbar.outline.set_edgecolor('#e5e7eb')
plt.setp(plt.getp(cbar.ax.axes, 'yticklabels'), color='#6b7280')

for spine in ax.spines.values():
    spine.set_color('#e5e7eb')
ax.set_title('AWS Resource Utilization by Region', fontsize=16, color='#111827', fontweight='bold', pad=15)
plt.tight_layout()
plt.show()