# 🔥 Kubernetes Resource Usage Report 2026/01/06

## 💾 TOP 10 MEMORY CONSUMERS

| Rank | Namespace | Pod Name | Memory |
|------|-----------|----------|--------|
| 1 | jenkins | jenkins-6fc54b66d5-dg6h9 | **1361Mi** 🔥 |
| 2 | monitoring | prometheus-k8s-monitoring-kube-promet-prometheus-0 | **1011Mi** |
| 3 | longhorn-system | instance-manager-d615ed1c3a0e53d6a8ab21533bc5d628 | **600Mi** |
| 4 | longhorn-system | instance-manager-30e7dd49f715bfdb9ae030c0e2b45bbf | **599Mi** |
| 5 | longhorn-system | instance-manager-adf5b54f2ad6e50eb3987b8dc9bd1d52 | **559Mi** |
| 6 | calibre-web | calibre-web-58b6bc49fd-msmgz | **317Mi** |
| 7 | monitoring | k8s-monitoring-grafana-b4c85bb7c-b4v8x | **313Mi** |
| 8 | argocd | argocd-application-controller-0 | **210Mi** |
| 9 | longhorn-system | longhorn-manager-sbqhd | **176Mi** |
| 10 | longhorn-system | longhorn-manager-l4sj6 | **178Mi** |

---

## 🔥 TOP 10 CPU CONSUMERS

| Rank | Namespace | Pod Name | CPU |
|------|-----------|----------|-----|
| 1 | monitoring | prometheus-k8s-monitoring-kube-promet-prometheus-0 | **199m** 🔥 |
| 2 | longhorn-system | instance-manager-d615ed1c3a0e53d6a8ab21533bc5d628 | **125m** |
| 3 | longhorn-system | instance-manager-30e7dd49f715bfdb9ae030c0e2b45bbf | **83m** |
| 4 | longhorn-system | instance-manager-adf5b54f2ad6e50eb3987b8dc9bd1d52 | **65m** |
| 5 | argocd | argocd-application-controller-0 | **38m** |
| 6 | longhorn-system | longhorn-manager-sbqhd | **28m** |
| 7 | longhorn-system | longhorn-manager-mgpgj | **26m** |
| 8 | loki | promtail-qh9n9 | **26m** |
| 9 | loki | promtail-7fl7h | **25m** |
| 10 | gitea | gitea-valkey-cluster-2 | **24m** |

---

## 📊 SUMMARY BY NAMESPACE

| Namespace | Pods | Total Memory | Avg Memory per Pod |
|-----------|------|--------------|-------------------|
| jenkins | 1 | **1361Mi** 🔥 | 1361Mi |
| monitoring | 5 | **1391Mi** | 278Mi |
| longhorn-system | 32 | **2577Mi** | 81Mi |
| argocd | 7 | **371Mi** | 53Mi |
| gitea | 4 | **167Mi** | 42Mi |
| calibre-web | 1 | **317Mi** | 317Mi |
| loki | 4 | **296Mi** | 74Mi |
| default | 5 | **238Mi** | 48Mi |

---

## 🎯 KEY INSIGHTS

### Jenkins (Biggest Consumer!)
```
Pod: jenkins-6fc54b66d5-dg6h9
Memory: 1361Mi (1.3 GB!)
CPU: 3m (low)

💡 Причина: 
- Jenkins хранит build history в памяти
- Загружены плагины
- Кэш workspace
```

### Prometheus (Second Biggest)
```
Pod: prometheus-k8s-monitoring-kube-promet-prometheus-0
Memory: 1011Mi (1 GB)
CPU: 199m (highest CPU usage!)

💡 Причина:
- Хранит метрики в памяти
- Time series database
- Retention period
```

### Longhorn (Distributed Storage)
```
Total Memory: ~2.5GB across 32 pods
Average: 81Mi per pod

💡 Причина:
- 3 instance managers (по ~600Mi каждый)
- Storage management overhead
- Replica data
```

---

## ⚠️ RECOMMENDATIONS

### 1. Jenkins Memory Optimization

**Current:** 1361Mi  
**Recommended:** Set limits

```yaml
# apps/jenkins/deployment.yaml
resources:
  limits:
    memory: 2Gi
    cpu: 1000m
  requests:
    memory: 1536Mi
    cpu: 500m
```

**Actions:**
- Configure max build history
- Clean old workspaces
- Limit concurrent builds

---

### 2. Prometheus Memory Optimization

**Current:** 1011Mi  
**Recommended:** Adjust retention

```yaml
# Reduce retention period
prometheus:
  retention: 7d  # Down from 15d
  retentionSize: 10GB
```

---

### 3. Longhorn Optimization

**Current:** ~600Mi per instance manager  
**Status:** Normal for distributed storage

No action needed - this is expected for Longhorn.

---

## 📈 MONITORING COMMANDS

### Watch top consumers:
```bash
watch -n 5 kubectl top pods --all-namespaces --sort-by=memory
```

### Check specific namespace:
```bash
kubectl top pods -n jenkins
kubectl top pods -n monitoring
kubectl top pods -n longhorn-system
```

### Check nodes:
```bash
kubectl top nodes
```

### Get detailed metrics:
```bash
# Pod metrics
kubectl get --raw /apis/metrics.k8s.io/v1beta1/namespaces/jenkins/pods/jenkins-6fc54b66d5-dg6h9 | jq

# Node metrics
kubectl get --raw /apis/metrics.k8s.io/v1beta1/nodes | jq
```

---

## 🎯 QUICK WINS

1. ✅ **Add resource limits** to Jenkins
2. ✅ **Reduce Prometheus retention** if needed
3. ✅ **Monitor trends** in Grafana
4. ⏳ **Consider HPA** for auto-scaling
5. ⏳ **Add alerts** for high memory usage

---

## 📊 CURRENT CLUSTER CAPACITY

Run `kubectl top nodes` to see:
```
NAME      CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%
master1   ???m         ??%    ????Mi          ??%
master2   ???m         ??%    ????Mi          ??%
master3   ???m         ??%    ????Mi          ??%
```

---

**Jenkins is your biggest memory consumer!** 🔥  
Consider adding resource limits and cleanup policies.