Performance Tuning Guide¶

This guide provides comprehensive information on optimizing the performance of ZeroTrustKerberosLink for high-throughput and low-latency environments while maintaining security.

Overview¶

Performance tuning is essential for ensuring that ZeroTrustKerberosLink can handle your organization's authentication and authorization workload efficiently. This guide covers key aspects of performance optimization.

Performance Metrics¶

Key performance metrics to monitor include:

Authentication Latency: Time to authenticate a user
Role Assumption Latency: Time to assume an AWS role
Request Throughput: Number of requests processed per second
Concurrent Sessions: Number of active sessions
Resource Utilization: CPU, memory, network, and disk usage

Server Configuration¶

Connection Handling¶

Optimize connection handling for high throughput:

server:
  connection_pool:
    max_connections: 1000
    max_idle_connections: 100
    idle_timeout: "60s"
    keep_alive: "30s"
  timeouts:
    read: "30s"
    write: "30s"
    idle: "60s"
  tcp:
    no_delay: true
    keep_alive: true
    keep_alive_period: "30s"

Worker Configuration¶

Configure worker threads for optimal performance:

server:
  workers:
    min: 10
    max: 100
    queue_size: 1000
    idle_timeout: "60s"

Caching Optimization¶

Redis Cache Configuration¶

Optimize Redis cache for performance:

cache:
  redis:
    pool_size: 20
    min_idle_connections: 5
    max_retries: 3
    dial_timeout: "5s"
    read_timeout: "3s"
    write_timeout: "3s"
    pool_timeout: "4s"
    idle_timeout: "300s"
    max_conn_age: "3600s"
    pipeline_window: "1ms"
    pipeline_limit: 100

Cache Sizing¶

Configure cache sizes based on workload:

cache:
  aws_roles:
    max_size: 10000
  kerberos_principals:
    max_size: 50000
  aws_credentials:
    max_size: 10000

Cache Preloading¶

Preload frequently used cache entries:

cache:
  preload:
    enabled: true
    role_mappings: true
    principals: false

Kerberos Optimization¶

Optimize Kerberos authentication:

kerberos:
  ticket_cache:
    enabled: true
    size: 10000
    ttl: "10m"
  dns_lookup_kdc: false
  dns_lookup_realm: false
  max_retries: 3
  retry_interval: "1s"

AWS API Optimization¶

Optimize AWS API interactions:

aws:
  connection_pool:
    max_idle_connections: 100
    idle_timeout: "60s"
  retry:
    max_retries: 3
    mode: "standard"  # standard, adaptive
  endpoint_discovery:
    enabled: true
    cache_period: "10m"
  regional_endpoints: true

JVM Tuning (for Java-based deployments)¶

For Java-based deployments, optimize JVM settings:

JAVA_OPTS="-Xms2g -Xmx2g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:ParallelGCThreads=4 -XX:ConcGCThreads=2 -XX:InitiatingHeapOccupancyPercent=70"

Golang Tuning (for Go-based deployments)¶

For Go-based deployments, optimize Go settings:

GOMAXPROCS=8
GOGC=100

Load Testing¶

Perform load testing to identify performance bottlenecks:

# Basic load test
zerotrustkerberos benchmark --concurrency 100 --duration 60s

# Authentication load test
zerotrustkerberos benchmark auth --principals 1000 --concurrency 50 --duration 300s

# Role assumption load test
zerotrustkerberos benchmark aws --roles 100 --concurrency 20 --duration 300s

Performance Profiles¶

ZeroTrustKerberosLink provides predefined performance profiles:

Small Deployment Profile¶

For deployments handling up to 100 concurrent users:

performance:
  profile: "small"
  # Equivalent to:
  # server.workers.max: 20
  # cache.redis.pool_size: 10
  # kerberos.ticket_cache.size: 1000

Medium Deployment Profile¶

For deployments handling up to 1,000 concurrent users:

performance:
  profile: "medium"
  # Equivalent to:
  # server.workers.max: 50
  # cache.redis.pool_size: 20
  # kerberos.ticket_cache.size: 10000

Large Deployment Profile¶

For deployments handling up to 10,000 concurrent users:

performance:
  profile: "large"
  # Equivalent to:
  # server.workers.max: 200
  # cache.redis.pool_size: 50
  # kerberos.ticket_cache.size: 50000

Security Considerations¶

When optimizing performance, follow these security best practices:

Balance Performance and Security

Ensure that performance optimizations do not compromise security controls.

Secure Cache Data

Implement appropriate encryption and access controls for cached data.

Resource Limits

Implement resource limits to prevent denial of service conditions.

Monitor Performance Anomalies

Monitor for performance anomalies that could indicate security issues.

Regular Testing

Regularly test performance under various conditions to ensure consistent behavior.

Performance Monitoring¶

ZeroTrustKerberosLink provides metrics for monitoring performance:

Request Latency: Time to process requests
Authentication Latency: Time to authenticate users
Role Assumption Latency: Time to assume AWS roles
Cache Hit Rate: Percentage of cache hits
Worker Utilization: Percentage of workers in use
Connection Pool Utilization: Percentage of connections in use

These metrics are available through the monitoring endpoints. See the Monitoring Guide for details.

Troubleshooting Performance Issues¶

Common performance issues include:

Issue	Possible Causes	Resolution
High authentication latency	Slow KDC response, insufficient caching	Optimize KDC connectivity, increase cache size
High role assumption latency	AWS API throttling, network latency	Implement exponential backoff, use regional endpoints
Low request throughput	Insufficient workers, connection limits	Increase worker count, optimize connection handling
High memory usage	Large cache size, memory leaks	Adjust cache size, investigate memory leaks
High CPU usage	Inefficient processing, excessive logging	Profile application, optimize processing, reduce logging