Filter Out Idle AKS Clusters

import azure.identity from azure.mgmt.monitor import MonitorManagementClient def filter_low_cpu_clusters(clusters, monitor_client, low_cpu_threshold): low_cpu_clusters = [] for cluster in clusters: try: # Fetch CPU utilization metrics for the cluster metrics_data = monitor_client.metrics.list( resource_uri=cluster.id, metricnames='node_cpu_usage_percentage', result_type='Data' ) # Extract non-None average values valid_averages = [time_series.average for time_series in metrics_data.value[0].timeseries[0].data if time_series.average is not None] # Check the average CPU utilization if valid_averages: # Ensure there are valid values before calculating average avg_cpu = sum(valid_averages) / len(valid_averages) if avg_cpu < int(low_cpu_threshold): low_cpu_clusters.append(cluster) except Exception as e: print(f"Failed to fetch metrics for cluster {cluster.name}: {e}") return low_cpu_clusters if subscription_id: # Initialize Azure credentials credential = azure.identity.DefaultAzureCredential() # Setup Azure Monitor client monitor_client = MonitorManagementClient(credential, subscription_id) # Filter clusters with low CPU utilization clusters_filtered = filter_low_cpu_clusters(all_clusters, monitor_client) print(clusters_filtered) # for debugging print(f"Clusters with low CPU utilization:") for cluster in clusters_filtered: print(f" - Name: {cluster.name}, Location: {cluster.location}")