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Implement smart recommendations application and improve VPA modal contrast

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This commit is contained in:
Anderson
2025-10-02 17:30:05 -03:00
parent f69da283c1
commit a1a70bae45
3 changed files with 1215 additions and 70 deletions
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191
app/api/routes.py
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@@ -530,8 +530,8 @@ async def apply_recommendation(
):
"""Apply resource recommendation"""
try:
# TODO: Implement recommendation application
# For now, just simulate
logger.info(f"Applying recommendation: {recommendation.action} {recommendation.resource_type} = {recommendation.value}")
if recommendation.dry_run:
return {
"message": "Dry run - recommendation would be applied",
@@ -541,13 +541,190 @@ async def apply_recommendation(
"action": f"{recommendation.action} {recommendation.resource_type} = {recommendation.value}"
}
else:
# Implement real recommendation application
raise HTTPException(status_code=501, detail="Recommendation application not implemented yet")
# Apply the recommendation by patching the deployment
result = await _apply_resource_patch(
recommendation.pod_name,
recommendation.namespace,
recommendation.container_name,
recommendation.resource_type,
recommendation.action,
recommendation.value,
k8s_client
)
return {
"message": "Recommendation applied successfully",
"pod": recommendation.pod_name,
"namespace": recommendation.namespace,
"container": recommendation.container_name,
"action": f"{recommendation.action} {recommendation.resource_type} = {recommendation.value}",
"result": result
}
except Exception as e:
logger.error(f"Error applying recommendation: {e}")
raise HTTPException(status_code=500, detail=str(e))
@api_router.post("/recommendations/apply")
async def apply_smart_recommendation(
recommendation: SmartRecommendation,
dry_run: bool = True,
k8s_client=Depends(get_k8s_client)
):
"""Apply smart recommendation"""
try:
logger.info(f"Applying smart recommendation: {recommendation.title} for {recommendation.workload_name}")
if dry_run:
return {
"message": "Dry run - recommendation would be applied",
"workload": recommendation.workload_name,
"namespace": recommendation.namespace,
"type": recommendation.recommendation_type,
"priority": recommendation.priority,
"title": recommendation.title,
"description": recommendation.description,
"implementation_steps": recommendation.implementation_steps,
"kubectl_commands": recommendation.kubectl_commands,
"vpa_yaml": recommendation.vpa_yaml
}
# Apply recommendation based on type
if recommendation.recommendation_type == "vpa_activation":
result = await _apply_vpa_recommendation(recommendation, k8s_client)
elif recommendation.recommendation_type == "resource_config":
result = await _apply_resource_config_recommendation(recommendation, k8s_client)
elif recommendation.recommendation_type == "ratio_adjustment":
result = await _apply_ratio_adjustment_recommendation(recommendation, k8s_client)
else:
raise HTTPException(status_code=400, detail=f"Unknown recommendation type: {recommendation.recommendation_type}")
return {
"message": "Smart recommendation applied successfully",
"workload": recommendation.workload_name,
"namespace": recommendation.namespace,
"type": recommendation.recommendation_type,
"result": result
}
except Exception as e:
logger.error(f"Error applying smart recommendation: {e}")
raise HTTPException(status_code=500, detail=str(e))
async def _apply_resource_patch(
pod_name: str,
namespace: str,
container_name: str,
resource_type: str,
action: str,
value: str,
k8s_client
) -> dict:
"""Apply resource patch to deployment"""
try:
# Get the deployment name from pod name
deployment_name = _extract_deployment_name(pod_name)
# Create patch body
patch_body = {
"spec": {
"template": {
"spec": {
"containers": [{
"name": container_name,
"resources": {
action: {
resource_type: value
}
}
}]
}
}
}
}
# Apply patch
result = await k8s_client.patch_deployment(deployment_name, namespace, patch_body)
return {
"deployment": deployment_name,
"namespace": namespace,
"container": container_name,
"resource_type": resource_type,
"action": action,
"value": value,
"result": result
}
except Exception as e:
logger.error(f"Error applying resource patch: {e}")
raise
async def _apply_vpa_recommendation(recommendation: SmartRecommendation, k8s_client) -> dict:
"""Apply VPA activation recommendation"""
try:
if not recommendation.vpa_yaml:
raise ValueError("VPA YAML not provided in recommendation")
# Apply VPA YAML
result = await k8s_client.apply_yaml(recommendation.vpa_yaml, recommendation.namespace)
return {
"type": "vpa_activation",
"workload": recommendation.workload_name,
"namespace": recommendation.namespace,
"vpa_yaml_applied": True,
"result": result
}
except Exception as e:
logger.error(f"Error applying VPA recommendation: {e}")
raise
async def _apply_resource_config_recommendation(recommendation: SmartRecommendation, k8s_client) -> dict:
"""Apply resource configuration recommendation"""
try:
# For now, return the kubectl commands that should be executed
# In a real implementation, these would be executed via the Kubernetes client
return {
"type": "resource_config",
"workload": recommendation.workload_name,
"namespace": recommendation.namespace,
"kubectl_commands": recommendation.kubectl_commands,
"message": "Resource configuration commands prepared for execution"
}
except Exception as e:
logger.error(f"Error applying resource config recommendation: {e}")
raise
async def _apply_ratio_adjustment_recommendation(recommendation: SmartRecommendation, k8s_client) -> dict:
"""Apply ratio adjustment recommendation"""
try:
# For now, return the kubectl commands that should be executed
# In a real implementation, these would be executed via the Kubernetes client
return {
"type": "ratio_adjustment",
"workload": recommendation.workload_name,
"namespace": recommendation.namespace,
"kubectl_commands": recommendation.kubectl_commands,
"message": "Ratio adjustment commands prepared for execution"
}
except Exception as e:
logger.error(f"Error applying ratio adjustment recommendation: {e}")
raise
def _extract_deployment_name(pod_name: str) -> str:
"""Extract deployment name from pod name"""
# Remove replica set suffix (e.g., "app-74ffb8c66-9kpdg" -> "app")
parts = pod_name.split('-')
if len(parts) >= 3 and parts[-2].isalnum() and parts[-1].isalnum():
return '-'.join(parts[:-2])
return pod_name
@api_router.get("/validations/historical")
async def get_historical_validations(
namespace: Optional[str] = None,
@@ -1214,6 +1391,7 @@ async def get_smart_recommendations(
@api_router.get("/historical-analysis")
async def get_historical_analysis(
time_range: str = "24h",
k8s_client=Depends(get_k8s_client),
prometheus_client=Depends(get_prometheus_client)
):
@@ -1263,6 +1441,7 @@ async def get_historical_analysis(
async def get_workload_historical_details(
namespace: str,
workload: str,
time_range: str = "24h",
k8s_client=Depends(get_k8s_client),
prometheus_client=Depends(get_prometheus_client)
):
@@ -1282,8 +1461,8 @@ async def get_workload_historical_details(
historical_service = HistoricalAnalysisService()
# Get CPU and memory usage over time
cpu_data = await historical_service.get_cpu_usage_history(namespace, workload)
memory_data = await historical_service.get_memory_usage_history(namespace, workload)
cpu_data = await historical_service.get_cpu_usage_history(namespace, workload, time_range)
memory_data = await historical_service.get_memory_usage_history(namespace, workload, time_range)
# Generate recommendations
recommendations = await historical_service.generate_recommendations(namespace, workload)