⚡ Control Plane Optimization and Scaling

Strategies for optimizing and scaling the Control Core Control Plane for high-performance production deployments.

📌 Overview

The Control Plane provides:

Administration Console - Web interface for policy management
Administration API - REST API for policy operations and user management
Policy Bridge - Real-time policy and data distribution to bouncers
Database - Policy and configuration storage
Cache - Session and coordination storage
Work ID Server (optional) - Cryptographic workload identity

🏗️ Architecture for Scale

At scale, the Control Plane uses a load balancer, multiple API and Policy Bridge replicas (with leader election), and shared database and cache.

Click to enlarge

Component layout:

┌─────────────────────────────────────────────────────────────────────────┐
│                         Load Balancer (L7)                              │
└────────────────────────────┬────────────────────────────────────────────┘
                             │
        ┌────────────────────┼────────────────────┐
        │                    │                    │
        ▼                    ▼                    ▼
┌──────────────┐    ┌──────────────┐    ┌──────────────┐
│  API #1      │    │  API #2      │    │  API #N      │
│  + Bridge    │    │  + Bridge    │    │  + Bridge    │
│  + Work ID*  │    │  (Follower)  │    │  (Follower)  │
│  (Leader)    │    │              │    │              │
└──────┬───────┘    └──────┬───────┘    └──────┬───────┘
       │                   │                    │
       └───────────────────┼────────────────────┘
                           │
                  ┌────────┴────────┐
                  │                 │
                  ▼                 ▼
         ┌────────────────┐ ┌────────────────┐
         │  Database      │ │     Cache      │
         │  (Primary +    │ │   (Cluster)    │
         │   Replicas)    │ │                │
         └────────────────┘ └────────────────┘
                  │                 │
                  └────────┬────────┘
                           │ Policy Distribution
                           ▼
                    Bouncer Fleet

📌 Resource Sizing

Small Deployment (Development/Testing)

Component	Replicas	CPU	Memory
Administration API	1	0.5	1 GB
Console	1	0.25	512 MB
Policy Bridge	1	0.5	512 MB
Database	1	1	2 GB
Cache	1	0.5	1 GB

Medium Deployment (Production)

Component	Replicas	CPU	Memory
Administration API	3	1-2	2-4 GB
Console	3	0.5-1	1-2 GB
Policy Bridge	3	1	1-2 GB
Database	3 (1 primary + 2 replicas)	2-4	8-16 GB
Cache	6 (cluster)	1-2	4-8 GB

Large Deployment (Enterprise)

Component	Replicas	CPU	Memory
Administration API	5-10	2-4	4-8 GB
Console	3-5	1-2	2-4 GB
Policy Bridge	3-5	1-2	2-4 GB
Database	3+ (1 primary + 2+ replicas)	4-8	16-32 GB
Cache	6-12 (cluster)	2-4	8-16 GB

🔧 API Optimization

Key Settings

Setting	Description	Recommended
Workers	Concurrent request handlers	4 per instance
Connection pool size	Database connections	50
Pool overflow	Extra connections under load	20
Request timeout	Maximum request duration	60 seconds
Rate limit	Requests per minute	1,000
Log level	Production logging	INFO or WARNING

High Availability

Deploy API replicas across availability zones
Use pod anti-affinity to spread instances
Configure health checks and readiness probes
Set appropriate resource requests and limits

⚡ Policy Bridge Optimization

Sync Settings

Setting	Development	Staging	Production
Policy sync interval	60s	30s	30s
Data sync interval	5 min	2 min	1 min
Keep-alive	60s	30s	30s

Leader Election

The Policy Bridge uses leader election for high availability. Configure multiple replicas (2-3 minimum); one acts as leader while others follow.

⚡ Database Optimization

Connection Pooling

Setting	Small	Medium	Large
Pool size	20	50	100
Max overflow	10	20	40
Pool timeout	30s	30s	30s
Pool recycle	3600s	3600s	3600s

Read Replicas

For production, use a primary database with read replicas. Route read-heavy operations to replicas.

Managed Database Options

AWS: RDS PostgreSQL with Multi-AZ
GCP: Cloud SQL with read replicas
Azure: Azure Database for PostgreSQL with high availability

📌 Cache Configuration

Setting	Small	Medium	Large
Cluster size	1	6	6-12
Memory per node	1 GB	4-8 GB	8-16 GB
Persistence	Optional	Recommended	Required
Replication	None	1 replica	2 replicas

📌 Load Balancing

Ingress Configuration

Use Layer 7 load balancer (NGINX, ALB, or cloud equivalent)
Enable SSL/TLS termination
Configure rate limiting and timeouts
Set appropriate buffer sizes

Session Affinity

Enable client IP session affinity for API requests when needed (default: 3 hours).

📌 Monitoring

Key Metrics

Metric	Description
Request rate	Requests per second
Request latency	P50, P95, P99
Error rate	4xx and 5xx responses
Database connections	Active and idle
Cache hit rate	Cache effectiveness
Policy sync lag	Time since last sync

Health Endpoints

API health: GET /api/v1/health
Ready check: GET /api/v1/health/ready

Alerts

Set up alerts for:

API error rate > 5%
P95 latency > 1 second
Database connection pool exhaustion
Policy sync failure > 5 minutes

⚡ Performance Benchmarks

Deployment Size	API Requests/sec	Policy Updates/sec	Latency (p95)
Small	100-500	1-5	<100ms
Medium	500-2,000	5-20	<50ms
Large	2,000-10,000	20-100	<20ms
Enterprise	10,000+	100+	<10ms

🛠️ Troubleshooting

Issue	What to check
High API or Policy Bridge latency	Review API Optimization and Policy Bridge Optimization. Scale replicas and check database (e.g. Postgres) and cache (e.g. Redis) health.
Database or cache errors under load	Verify connection pools and Database Optimization. Ensure Redis/storage is sized and reachable.
Bouncers not receiving updates	Confirm Policy Bridge and Control Plane URL from bouncers. Check API key and network connectivity.
Uneven load across replicas	Validate load balancer and health checks. See Load Balancing.

For more, see the Troubleshooting Guide.

Multiple Bouncers - Scale the enforcement layer
Enterprise Deployment - Complete enterprise setup
Security Best Practices - Security hardening