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Add simulated data fallback for historical analysis when Prometheus is not accessible

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This commit is contained in:
Anderson
2025-09-30 18:06:10 -03:00
parent 2b2b3c23b2
commit 5f3f737b3a
2 changed files with 72 additions and 29 deletions
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94
app/api/routes.py
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@@ -526,15 +526,18 @@ async def get_workload_historical_metrics(
cluster_cpu_data = await prometheus_client.query(cluster_cpu_query)
cluster_memory_data = await prometheus_client.query(cluster_memory_query)
# Extract values
cpu_usage = 0
memory_usage = 0
cpu_requests = 0
memory_requests = 0
cpu_limits = 0
memory_limits = 0
cluster_cpu_total = 0
cluster_memory_total = 0
# Extract values
cpu_usage = 0
memory_usage = 0
cpu_requests = 0
memory_requests = 0
cpu_limits = 0
memory_limits = 0
cluster_cpu_total = 0
cluster_memory_total = 0
# Check if we got any data from Prometheus
prometheus_available = False
if cpu_usage_data.get("status") == "success" and cpu_usage_data.get("data", {}).get("result"):
cpu_usage = float(cpu_usage_data["data"]["result"][0]["value"][1])
@@ -557,26 +560,61 @@ async def get_workload_historical_metrics(
if cluster_cpu_data.get("status") == "success" and cluster_cpu_data.get("data", {}).get("result"):
cluster_cpu_total = float(cluster_cpu_data["data"]["result"][0]["value"][1])
if cluster_memory_data.get("status") == "success" and cluster_memory_data.get("data", {}).get("result"):
cluster_memory_total = float(cluster_memory_data["data"]["result"][0]["value"][1])
if cluster_memory_data.get("status") == "success" and cluster_memory_data.get("data", {}).get("result"):
cluster_memory_total = float(cluster_memory_data["data"]["result"][0]["value"][1])
# Check if Prometheus is available (any non-zero values)
if cluster_cpu_total > 0 or cluster_memory_total > 0:
prometheus_available = True
# If Prometheus is not available, provide simulated data for demonstration
if not prometheus_available:
# Simulate cluster resources (typical OpenShift cluster)
cluster_cpu_total = 24.0 # 6 nodes * 4 cores each
cluster_memory_total = 96.0 * (1024**3) # 6 nodes * 16GB each
# Simulate workload metrics based on namespace
if namespace == "resource-governance":
cpu_usage = 0.05
memory_usage = 128 * (1024**2) # 128MB
cpu_requests = 0.1
memory_requests = 128 * (1024**2)
cpu_limits = 0.5
memory_limits = 512 * (1024**2)
elif namespace == "shishika01":
cpu_usage = 0.15
memory_usage = 256 * (1024**2) # 256MB
cpu_requests = 0.2
memory_requests = 256 * (1024**2)
cpu_limits = 1.0
memory_limits = 1024 * (1024**2)
else:
cpu_usage = 0.08
memory_usage = 192 * (1024**2) # 192MB
cpu_requests = 0.15
memory_requests = 192 * (1024**2)
cpu_limits = 0.8
memory_limits = 768 * (1024**2)
# Calculate percentages
cpu_usage_percent = (cpu_usage / cluster_cpu_total * 100) if cluster_cpu_total > 0 else 0
memory_usage_percent = (memory_usage / cluster_memory_total * 100) if cluster_memory_total > 0 else 0
cpu_requests_percent = (cpu_requests / cluster_cpu_total * 100) if cluster_cpu_total > 0 else 0
memory_requests_percent = (memory_requests / cluster_memory_total * 100) if cluster_memory_total > 0 else 0
cpu_limits_percent = (cpu_limits / cluster_cpu_total * 100) if cluster_cpu_total > 0 else 0
memory_limits_percent = (memory_limits / cluster_memory_total * 100) if cluster_memory_total > 0 else 0
# Calculate percentages
cpu_usage_percent = (cpu_usage / cluster_cpu_total * 100) if cluster_cpu_total > 0 else 0
memory_usage_percent = (memory_usage / cluster_memory_total * 100) if cluster_memory_total > 0 else 0
cpu_requests_percent = (cpu_requests / cluster_cpu_total * 100) if cluster_cpu_total > 0 else 0
memory_requests_percent = (memory_requests / cluster_memory_total * 100) if cluster_memory_total > 0 else 0
cpu_limits_percent = (cpu_limits / cluster_cpu_total * 100) if cluster_cpu_total > 0 else 0
memory_limits_percent = (memory_limits / cluster_memory_total * 100) if cluster_memory_total > 0 else 0
return {
"workload": workload,
"namespace": namespace,
"time_range": time_range,
"cluster_total": {
"cpu_cores": cluster_cpu_total,
"memory_bytes": cluster_memory_total,
"memory_gb": cluster_memory_total / (1024**3)
},
return {
"workload": workload,
"namespace": namespace,
"time_range": time_range,
"prometheus_available": prometheus_available,
"data_source": "simulated" if not prometheus_available else "prometheus",
"cluster_total": {
"cpu_cores": cluster_cpu_total,
"memory_bytes": cluster_memory_total,
"memory_gb": cluster_memory_total / (1024**3)
},
"workload_metrics": {
"cpu": {
"usage_cores": cpu_usage,