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Performance

Optimize Bindy DNS infrastructure for maximum performance and efficiency.

Performance Metrics

Key metrics to monitor: - Query latency - Time to respond to DNS queries - Throughput - Queries per second (QPS) - Resource usage - CPU and memory utilization - Cache hit ratio - Percentage of cached responses - Reconciliation loops - Unnecessary status updates

Operator Performance

Status Update Optimization

The Bindy operator implements status change detection in all reconcilers to prevent tight reconciliation loops. This optimization:

  • Reduces Kubernetes API calls by skipping unnecessary status updates
  • Prevents reconciliation storms that can occur when status updates trigger new reconciliations
  • Improves overall system performance by reducing CPU and network overhead

All reconcilers check if the status has actually changed before updating the status subresource. Status updates only occur when: - Condition type changes - Status value changes - Message changes - Status doesn't exist yet

This optimization is implemented across all resource types: - Bind9Cluster - Bind9Instance - DNSZone - All DNS record types (A, AAAA, CNAME, MX, NS, SRV, TXT, CAA)

For more details, see the Reconciliation Logic documentation.

Optimization Strategies

1. Resource Allocation

Provide adequate CPU and memory:

spec:
  resources:
    requests:
      cpu: "500m"
      memory: "512Mi"
    limits:
      cpu: "2000m"
      memory: "2Gi"

2. Horizontal Scaling

Add more replicas for higher capacity:

spec:
  replicas: 5  # More replicas = more capacity

3. Geographic Distribution

Place DNS servers near clients: - Reduced network latency - Better user experience - Regional load distribution

4. Caching Strategy

Configure BIND9 caching (when appropriate): - Longer TTLs reduce upstream queries - Negative caching for NXDOMAIN - Prefetching for popular domains

Performance Testing

Baseline Testing

# Single query latency
time dig @$SERVICE_IP example.com

# Sustained load (100 QPS for 60 seconds)
dnsp erf -s $SERVICE_IP -d example.com -q 100 -t 60

Load Testing

# Using dnsperf
dnsperf -s $SERVICE_IP -d queries.txt -l 60 -Q 1000

# Using custom script
for i in {1..1000}; do
  dig @$SERVICE_IP test$i.example.com &
done
wait

Resource Optimization

CPU Optimization

  • Use efficient query algorithms
  • Enable query parallelization
  • Optimize zone file format

Memory Optimization

  • Right-size zone cache
  • Limit journal size
  • Regular zone file cleanup

Network Optimization

  • Use UDP for queries (TCP for transfers)
  • Enable TCP Fast Open
  • Optimize MTU size

Monitoring Performance

# Real-time resource usage
kubectl top pods -n dns-system -l app=bind9

# Query statistics
kubectl exec -n dns-system deployment/primary-dns -- \
  rndc stats

# View statistics file
kubectl exec -n dns-system deployment/primary-dns -- \
  cat /var/cache/bind/named.stats

Performance Targets

Metric Target Good Excellent
Query Latency < 50ms < 20ms < 10ms
Throughput > 1000 QPS > 5000 QPS > 10000 QPS
CPU Usage < 70% < 50% < 30%
Memory Usage < 80% < 60% < 40%
Cache Hit Ratio > 60% > 80% > 90%

Next Steps