feat: implement real cluster analysis with Kubernetes API data
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@@ -26,45 +26,97 @@ def analyze_cluster(self, cluster_config=None):
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# Update task state
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self.update_state(
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state='PROGRESS',
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meta={'current': 0, 'total': 3, 'status': 'Starting cluster analysis...'}
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meta={'current': 0, 'total': 5, 'status': 'Starting cluster analysis...'}
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)
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# Step 1: Simple test
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# Step 1: Initialize clients
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self.update_state(
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state='PROGRESS',
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meta={'current': 1, 'total': 3, 'status': 'Testing basic functionality...'}
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meta={'current': 1, 'total': 5, 'status': 'Initializing Kubernetes client...'}
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)
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# Simple test without complex clients
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logger.info("Starting simple cluster analysis test")
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k8s_client = K8sClient()
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logger.info("Starting real cluster analysis")
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# Step 2: Return simple results
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# Step 2: Get cluster info
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self.update_state(
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state='PROGRESS',
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meta={'current': 2, 'total': 3, 'status': 'Generating results...'}
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meta={'current': 2, 'total': 5, 'status': 'Analyzing cluster resources...'}
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)
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# Simple results without complex operations
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# Get real cluster data
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namespaces = k8s_client.list_namespaces()
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pods = k8s_client.list_pods()
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nodes = k8s_client.list_nodes()
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# Step 3: Analyze workloads
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self.update_state(
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state='PROGRESS',
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meta={'current': 3, 'total': 5, 'status': 'Analyzing workloads...'}
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)
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# Count workloads by type
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workload_counts = {}
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for pod in pods:
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workload_type = pod.metadata.labels.get('app.kubernetes.io/name', 'unknown')
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workload_counts[workload_type] = workload_counts.get(workload_type, 0) + 1
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# Step 4: Get resource utilization
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self.update_state(
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state='PROGRESS',
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meta={'current': 4, 'total': 5, 'status': 'Calculating resource utilization...'}
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)
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# Calculate resource requests and limits
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total_cpu_requests = 0
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total_memory_requests = 0
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total_cpu_limits = 0
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total_memory_limits = 0
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for pod in pods:
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for container in pod.spec.containers:
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if container.resources and container.resources.requests:
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if 'cpu' in container.resources.requests:
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total_cpu_requests += _parse_cpu_value(container.resources.requests['cpu'])
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if 'memory' in container.resources.requests:
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total_memory_requests += _parse_memory_value(container.resources.requests['memory'])
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if container.resources and container.resources.limits:
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if 'cpu' in container.resources.limits:
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total_cpu_limits += _parse_cpu_value(container.resources.limits['cpu'])
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if 'memory' in container.resources.limits:
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total_memory_limits += _parse_memory_value(container.resources.limits['memory'])
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# Step 5: Generate results
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self.update_state(
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state='PROGRESS',
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meta={'current': 5, 'total': 5, 'status': 'Generating analysis results...'}
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)
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# Real analysis results
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results = {
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'cluster_info': {
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'total_namespaces': 5,
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'total_pods': 20,
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'total_nodes': 3,
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'total_namespaces': len(namespaces),
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'total_pods': len(pods),
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'total_nodes': len(nodes),
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'workload_types': len(workload_counts)
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},
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'resource_summary': {
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'cpu_requests': total_cpu_requests,
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'memory_requests': total_memory_requests,
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'cpu_limits': total_cpu_limits,
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'memory_limits': total_memory_limits
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},
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'workload_breakdown': workload_counts,
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'summary': {
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'total_errors': 2,
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'total_warnings': 5,
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'total_info': 10,
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'total_errors': 0, # Will be calculated by validation service
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'total_warnings': 0, # Will be calculated by validation service
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'total_info': len(pods),
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},
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'status': 'completed'
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}
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self.update_state(
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state='PROGRESS',
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meta={'current': 3, 'total': 3, 'status': 'Analysis completed successfully'}
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)
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logger.info(f"Simple cluster analysis completed successfully. Found {results['summary']['total_errors']} errors, {results['summary']['total_warnings']} warnings")
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logger.info(f"Real cluster analysis completed successfully. Found {len(namespaces)} namespaces, {len(pods)} pods, {len(nodes)} nodes")
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return results
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@@ -78,6 +130,32 @@ def analyze_cluster(self, cluster_config=None):
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'summary': {'total_errors': 0, 'total_warnings': 0, 'total_info': 0}
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}
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def _parse_cpu_value(cpu_str):
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"""Parse CPU value from string to float (cores)"""
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if cpu_str.endswith('m'):
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return float(cpu_str[:-1]) / 1000
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elif cpu_str.endswith('n'):
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return float(cpu_str[:-1]) / 1000000000
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else:
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return float(cpu_str)
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def _parse_memory_value(memory_str):
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"""Parse memory value from string to float (bytes)"""
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if memory_str.endswith('Ki'):
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return float(memory_str[:-2]) * 1024
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elif memory_str.endswith('Mi'):
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return float(memory_str[:-2]) * 1024 * 1024
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elif memory_str.endswith('Gi'):
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return float(memory_str[:-2]) * 1024 * 1024 * 1024
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elif memory_str.endswith('K'):
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return float(memory_str[:-1]) * 1000
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elif memory_str.endswith('M'):
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return float(memory_str[:-1]) * 1000 * 1000
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elif memory_str.endswith('G'):
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return float(memory_str[:-1]) * 1000 * 1000 * 1000
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else:
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return float(memory_str)
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@celery_app.task(name='app.tasks.cluster_analysis.health_check')
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def health_check():
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"""
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