Monitoring - vCluster

Overview

Effective monitoring is essential for maintaining healthy virtual clusters. This guide covers monitoring strategies, metrics collection, and observability best practices for vCluster deployments.

Monitoring Architecture

vCluster monitoring operates at multiple levels:

Control Plane

Monitor vCluster control plane pods, API server health, and syncer performance

Virtual Resources

Track resources running inside the virtual cluster

Host Resources

Monitor synced resources in the host cluster namespace

Quick Health Checks

vCluster Control Plane Status

Check if vCluster control plane is running:

# List all vClusters
vcluster list

# Check pods in host namespace
kubectl get pods -n production -l release=my-vcluster

# Check pod health details
kubectl describe pod -n production -l app=vcluster,release=my-vcluster

Virtual Cluster Connectivity

Test connection to the virtual cluster:

# Connect and check nodes
vcluster connect my-vcluster --namespace production
kubectl get nodes
kubectl get pods --all-namespaces

# Check API server responsiveness
kubectl get --raw /healthz
kubectl get --raw /readyz

Resource Syncing Status

Verify resources are syncing correctly:

# Create test resource in virtual cluster
vcluster connect my-vcluster --namespace production
kubectl create deployment test-sync --image=nginx

# Verify it synced to host namespace
vcluster disconnect
kubectl get pods -n production | grep test-sync

# Cleanup
vcluster connect my-vcluster --namespace production
kubectl delete deployment test-sync

Prometheus Integration

Enabling Metrics

Configure vCluster to expose Prometheus metrics:

# vcluster.yaml
controlPlane:
  statefulSet:
    podMetadata:
      annotations:
        prometheus.io/scrape: "true"
        prometheus.io/port: "8443"
        prometheus.io/path: "/metrics"

observability:
  metrics:
    enabled: true

Apply the configuration:

helm upgrade my-vcluster vcluster \
  --repo https://charts.loft.sh \
  --namespace production \
  --values vcluster.yaml

ServiceMonitor for Prometheus Operator

If using Prometheus Operator, create a ServiceMonitor:

apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: vcluster-my-vcluster
  namespace: production
spec:
  selector:
    matchLabels:
      app: vcluster
      release: my-vcluster
  endpoints:
  - port: https
    interval: 30s
    scheme: https
    tlsConfig:
      insecureSkipVerify: true
    path: /metrics

Apply the ServiceMonitor:

kubectl apply -f servicemonitor.yaml

Key Metrics to Monitor

Control Plane Metrics

API Server Metrics

Important metrics:

apiserver_request_total - Total API requests
apiserver_request_duration_seconds - Request latency
apiserver_request_errors_total - Failed requests
apiserver_storage_objects - Number of stored objects

Prometheus query examples:

# API server request rate
rate(apiserver_request_total[5m])

# API server error rate
rate(apiserver_request_errors_total[5m])

# P95 API latency
histogram_quantile(0.95, rate(apiserver_request_duration_seconds_bucket[5m]))

Syncer Metrics

Important metrics:

vcluster_syncer_sync_operations_total - Sync operations count
vcluster_syncer_sync_errors_total - Sync failures
vcluster_syncer_sync_duration_seconds - Sync operation duration
vcluster_syncer_resources_synced - Number of synced resources

Prometheus query examples:

# Sync error rate
rate(vcluster_syncer_sync_errors_total[5m])

# Average sync duration
rate(vcluster_syncer_sync_duration_seconds_sum[5m]) / 
rate(vcluster_syncer_sync_duration_seconds_count[5m])

# Resources synced by type
vcluster_syncer_resources_synced

Resource Usage

Important metrics:

container_memory_usage_bytes - Memory usage
container_cpu_usage_seconds_total - CPU usage
container_network_receive_bytes_total - Network ingress
container_network_transmit_bytes_total - Network egress

Prometheus query examples:

# Memory usage by container
container_memory_usage_bytes{
  namespace="production",
  pod=~"my-vcluster-.*"
}

# CPU usage rate
rate(container_cpu_usage_seconds_total{
  namespace="production",
  pod=~"my-vcluster-.*"
}[5m])

Grafana Dashboards

Pre-built Dashboard

Import the vCluster Grafana dashboard:

Open Grafana
Go to Dashboards → Import
Use dashboard ID: 15843 (community vCluster dashboard)
Or import from JSON:

{
  "dashboard": {
    "title": "vCluster Overview",
    "panels": [
      {
        "title": "API Server Request Rate",
        "targets": [{
          "expr": "rate(apiserver_request_total{namespace='production'}[5m])"
        }]
      },
      {
        "title": "Sync Operations",
        "targets": [{
          "expr": "rate(vcluster_syncer_sync_operations_total[5m])"
        }]
      },
      {
        "title": "Memory Usage",
        "targets": [{
          "expr": "container_memory_usage_bytes{namespace='production',pod=~'my-vcluster-.*'}"
        }]
      }
    ]
  }
}

Custom Dashboard Panels

Health Status
Resource Sync
Performance
Errors

# Panel: vCluster Health
up{job="vcluster", namespace="production"}

# Use single stat visualization
# Thresholds: 1 = green, 0 = red

# Panel: Synced Resources by Type
sum by (resource_type) (
  vcluster_syncer_resources_synced{namespace="production"}
)

# Use bar chart or table visualization

# Panel: API Latency P95
histogram_quantile(0.95,
  rate(apiserver_request_duration_seconds_bucket{
    namespace="production"
  }[5m])
)

# Use time series graph
# Alert threshold: > 1s

# Panel: Error Rate
sum(rate(apiserver_request_errors_total{
  namespace="production"
}[5m]))

# Use time series with alert threshold

Logging

Centralized Log Collection

Using Fluentd/Fluent Bit

# fluentbit-config.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: fluent-bit-config
  namespace: logging
data:
  fluent-bit.conf: |
    [INPUT]
        Name              tail
        Path              /var/log/containers/my-vcluster-*.log
        Parser            docker
        Tag               vcluster.*
        Refresh_Interval  5
    
    [FILTER]
        Name    kubernetes
        Match   vcluster.*
        Kube_URL https://kubernetes.default.svc:443
    
    [OUTPUT]
        Name  es
        Match vcluster.*
        Host  elasticsearch.logging.svc
        Port  9200
        Index vcluster-logs

Using Loki

# promtail-config.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: promtail-config
  namespace: logging
data:
  promtail.yaml: |
    server:
      http_listen_port: 9080
    
    positions:
      filename: /tmp/positions.yaml
    
    clients:
      - url: http://loki.logging.svc:3100/loki/api/v1/push
    
    scrape_configs:
      - job_name: vcluster
        kubernetes_sd_configs:
          - role: pod
            namespaces:
              names:
                - production
        relabel_configs:
          - source_labels: [__meta_kubernetes_pod_label_app]
            regex: vcluster
            action: keep

Viewing vCluster Logs

# View control plane logs
kubectl logs -n production -l app=vcluster,release=my-vcluster

# Follow logs in real-time
kubectl logs -n production -l app=vcluster,release=my-vcluster -f

# View specific container logs
kubectl logs -n production my-vcluster-0 -c syncer

# View previous container logs (after restart)
kubectl logs -n production my-vcluster-0 --previous

# Export logs to file
kubectl logs -n production -l app=vcluster,release=my-vcluster > vcluster-logs.txt

Log Levels and Debugging

Increase log verbosity for troubleshooting:

# vcluster.yaml
controlPlane:
  statefulSet:
    env:
    - name: DEBUG
      value: "true"
    - name: VCLUSTER_LOG_LEVEL
      value: "debug"  # Options: info, debug, trace

Alerting

Prometheus AlertManager Rules

# vcluster-alerts.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: vcluster-alerts
  namespace: monitoring
data:
  alerts.yaml: |
    groups:
    - name: vcluster
      interval: 30s
      rules:
      # Control plane health
      - alert: VClusterDown
        expr: up{job="vcluster"} == 0
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "vCluster {{ $labels.namespace }}/{{ $labels.vcluster }} is down"
          description: "vCluster has been down for more than 5 minutes"
      
      # High error rate
      - alert: VClusterHighErrorRate
        expr: |
          rate(apiserver_request_errors_total[5m]) > 0.05
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "High error rate in vCluster API server"
          description: "Error rate is {{ $value | humanizePercentage }}"
      
      # Sync failures
      - alert: VClusterSyncFailures
        expr: |
          rate(vcluster_syncer_sync_errors_total[5m]) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          summary: "vCluster sync failures detected"
          description: "Syncer is failing to sync resources"
      
      # High memory usage
      - alert: VClusterHighMemory
        expr: |
          container_memory_usage_bytes{pod=~"my-vcluster-.*"} / 
          container_spec_memory_limit_bytes{pod=~"my-vcluster-.*"} > 0.9
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "vCluster high memory usage"
          description: "Memory usage is above 90%"
      
      # API latency
      - alert: VClusterHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(apiserver_request_duration_seconds_bucket[5m])
          ) > 1
        for: 10m
        labels:
          severity: warning
        annotations:
          summary: "vCluster API server high latency"
          description: "P95 latency is {{ $value }}s"
      
      # Pod restarts
      - alert: VClusterFrequentRestarts
        expr: |
          rate(kube_pod_container_status_restarts_total{
            namespace="production",
            pod=~"my-vcluster-.*"
          }[15m]) > 0
        for: 15m
        labels:
          severity: warning
        annotations:
          summary: "vCluster pod restarting frequently"
          description: "Pod {{ $labels.pod }} has restarted {{ $value }} times"

Apply the alerts:

kubectl apply -f vcluster-alerts.yaml

Distributed Tracing

OpenTelemetry Integration

Configure vCluster to export traces:

# vcluster.yaml
observability:
  tracing:
    enabled: true
    endpoint: "otel-collector.observability.svc:4317"
    serviceName: "vcluster-my-vcluster"
    samplingRate: 0.1  # Sample 10% of requests

Jaeger Configuration

# Deploy Jaeger operator
apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: vcluster-tracing
  namespace: observability
spec:
  strategy: production
  storage:
    type: elasticsearch
    options:
      es:
        server-urls: http://elasticsearch:9200
  ingress:
    enabled: true

Health Checks and Probes

Custom Liveness Probe

# vcluster.yaml
controlPlane:
  statefulSet:
    containers:
      - name: vcluster
        livenessProbe:
          httpGet:
            path: /healthz
            port: 8443
            scheme: HTTPS
          initialDelaySeconds: 30
          periodSeconds: 10
          timeoutSeconds: 5
          failureThreshold: 3

External Monitoring Script

#!/bin/bash
# monitor-vcluster.sh

VCLUSTER_NAME="my-vcluster"
NAMESPACE="production"
ALERT_WEBHOOK="https://hooks.slack.com/services/YOUR/WEBHOOK/URL"

check_health() {
  # Check if pods are running
  RUNNING=$(kubectl get pods -n $NAMESPACE -l release=$VCLUSTER_NAME \
    -o jsonpath='{.items[*].status.phase}' | grep -c "Running")
  
  if [ $RUNNING -eq 0 ]; then
    echo "CRITICAL: No running pods found for $VCLUSTER_NAME"
    send_alert "vCluster $VCLUSTER_NAME is down!"
    return 1
  fi
  
  # Check API server
  if ! vcluster connect $VCLUSTER_NAME --namespace $NAMESPACE -- kubectl get --raw /healthz &>/dev/null; then
    echo "WARNING: API server not responding"
    send_alert "vCluster $VCLUSTER_NAME API server not responding"
    return 1
  fi
  
  echo "OK: vCluster $VCLUSTER_NAME is healthy"
  return 0
}

send_alert() {
  MESSAGE=$1
  curl -X POST $ALERT_WEBHOOK \
    -H 'Content-Type: application/json' \
    -d "{\"text\": \"$MESSAGE\"}"
}

check_health
exit $?

Schedule with cron:

# Run every 5 minutes
*/5 * * * * /usr/local/bin/monitor-vcluster.sh

Performance Monitoring

Resource Usage Over Time

# Monitor CPU and memory
watch -n 5 'kubectl top pods -n production -l release=my-vcluster'

# Export metrics for analysis
kubectl top pods -n production -l release=my-vcluster --containers > metrics-$(date +%Y%m%d-%H%M%S).txt

Network Monitoring

# Network I/O
kubectl get pods -n production -l release=my-vcluster -o json | \
  jq -r '.items[] | .status.containerStatuses[] | 
    "\(.name): RX=\(.stats.network.rxBytes) TX=\(.stats.network.txBytes)"'

Debugging Tools

Debug Collect Command

Generate comprehensive debug bundle:

vcluster debug collect my-vcluster --namespace production

This creates a tarball with:

vCluster release info
Pod logs (current and previous)
Host cluster info and resources
Virtual cluster info and resources
Resource counts

Debug Shell

Direct shell access to vCluster pod:

vcluster debug shell my-vcluster --namespace production

Best Practices

Multi-Level Monitoring

Monitor at all levels: control plane, virtual resources, and host resources.

Set Meaningful Alerts

Configure alerts for actionable issues, not just symptoms. Avoid alert fatigue.

Retain Historical Data

Keep metrics and logs for at least 30 days for trend analysis and troubleshooting.

Dashboard for Each Environment

Create dedicated dashboards for production, staging, and development clusters.

Regular Reviews

Schedule weekly reviews of monitoring data to identify trends and issues early.

Document Baselines

Establish and document normal performance baselines for comparison.

Next Steps

Troubleshooting

Learn how to diagnose and fix issues detected by monitoring

Managing vClusters

Return to general management operations

Get Started

Architecture

Deployment

Operations

Resource Syncing

Use Cases

Security

Integrations

​Overview

​Monitoring Architecture

Control Plane

Virtual Resources

Host Resources

​Quick Health Checks

​vCluster Control Plane Status

​Virtual Cluster Connectivity

​Resource Syncing Status

​Prometheus Integration

​Enabling Metrics

​ServiceMonitor for Prometheus Operator

​Key Metrics to Monitor

​Control Plane Metrics

​Grafana Dashboards

​Pre-built Dashboard

​Custom Dashboard Panels

​Logging

​Centralized Log Collection

​Using Fluentd/Fluent Bit

​Using Loki

​Viewing vCluster Logs

​Log Levels and Debugging

​Alerting

​Prometheus AlertManager Rules

​Distributed Tracing

​OpenTelemetry Integration

​Jaeger Configuration

​Health Checks and Probes

​Custom Liveness Probe

​External Monitoring Script

​Performance Monitoring

​Resource Usage Over Time

​Network Monitoring

​Debugging Tools

​Debug Collect Command

​Debug Shell

​Best Practices

Multi-Level Monitoring

Set Meaningful Alerts

Retain Historical Data

Dashboard for Each Environment

Regular Reviews

Document Baselines

​Next Steps

Troubleshooting

Managing vClusters

Overview

Monitoring Architecture

Quick Health Checks

vCluster Control Plane Status

Virtual Cluster Connectivity

Resource Syncing Status

Prometheus Integration

Enabling Metrics

ServiceMonitor for Prometheus Operator

Key Metrics to Monitor

Control Plane Metrics

Grafana Dashboards

Pre-built Dashboard

Custom Dashboard Panels

Logging

Centralized Log Collection

Using Fluentd/Fluent Bit

Using Loki

Viewing vCluster Logs

Log Levels and Debugging

Alerting

Prometheus AlertManager Rules

Distributed Tracing

OpenTelemetry Integration

Jaeger Configuration

Health Checks and Probes

Custom Liveness Probe

External Monitoring Script

Performance Monitoring

Resource Usage Over Time

Network Monitoring

Debugging Tools

Debug Collect Command

Debug Shell

Best Practices

Next Steps