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

Controller 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

Next Steps

• Tuning - Detailed tuning parameters
• Benchmarking - Performance testing methodology