NeuroCognitive Architecture (NCA) Deployment Guide¶

Table of Contents¶

Introduction
Deployment Environments
Prerequisites
Infrastructure Setup
Deployment Methods
Docker Deployment
Kubernetes Deployment
Serverless Deployment
Configuration Management
Database Setup and Migration
Security Considerations
Monitoring and Observability
Scaling Strategies
Backup and Disaster Recovery
Continuous Integration/Continuous Deployment
Rollback Procedures
Troubleshooting
Maintenance Procedures

Introduction¶

This document provides comprehensive guidelines for deploying the NeuroCognitive Architecture (NCA) system in various environments. It covers all aspects of deployment, from infrastructure setup to monitoring and maintenance procedures.

The NCA system is designed with a modular architecture that can be deployed in different configurations depending on the specific requirements and constraints of your environment. This guide will help you navigate the deployment process and ensure a successful implementation.

Deployment Environments¶

The NCA system can be deployed in the following environments:

Development Environment¶

Purpose: Local development and testing
Infrastructure: Docker Compose
Configuration: Development-specific settings with debug enabled
Data: Sample datasets or development databases

Staging Environment¶

Purpose: Integration testing and pre-production validation
Infrastructure: Kubernetes cluster or cloud provider staging resources
Configuration: Production-like settings with enhanced logging
Data: Anonymized production-like data

Production Environment¶

Purpose: Live system serving real users
Infrastructure: Kubernetes cluster or cloud provider production resources
Configuration: Optimized settings with security hardening
Data: Production data with proper backup and recovery mechanisms

Prerequisites¶

Before deploying the NCA system, ensure you have the following prerequisites:

General Requirements¶

Python 3.10 or higher
Docker and Docker Compose (for containerized deployments)
Kubernetes CLI (kubectl) and access to a Kubernetes cluster (for Kubernetes deployments)
Access to cloud provider resources (for cloud deployments)
Git for version control
SSL certificates for secure communication

Resource Requirements¶

CPU: Minimum 4 cores recommended (8+ for production)
Memory: Minimum 8GB RAM (16GB+ for production)
Storage: Minimum 50GB (100GB+ for production)
Network: High-bandwidth, low-latency connections for distributed deployments

Access Requirements¶

Database credentials
API keys for external services
Cloud provider credentials
Container registry access

Infrastructure Setup¶

Cloud Provider Setup¶

AWS¶

# Example AWS infrastructure setup using Terraform
cd infrastructure/aws
terraform init
terraform plan -out=tfplan
terraform apply tfplan

Azure¶

# Example Azure infrastructure setup using Terraform
cd infrastructure/azure
terraform init
terraform plan -out=tfplan
terraform apply tfplan

Google Cloud Platform¶

# Example GCP infrastructure setup using Terraform
cd infrastructure/gcp
terraform init
terraform plan -out=tfplan
terraform apply tfplan

On-Premises Setup¶

For on-premises deployments, ensure your infrastructure meets the following requirements: - Kubernetes cluster or Docker Swarm for orchestration - Load balancer for distributing traffic - Storage solution for persistent data - Monitoring infrastructure - Backup systems

Deployment Methods¶

Docker Deployment¶

The NCA system can be deployed using Docker for simpler deployments or development environments.

Building Docker Images¶

# Build the main application image
docker build -t neuroca:latest .

# Build specific component images (if needed)
docker build -t neuroca-api:latest ./api
docker build -t neuroca-worker:latest ./worker

Running with Docker Compose¶

# Start the entire stack
docker-compose up -d

# Start specific services
docker-compose up -d api db redis

# View logs
docker-compose logs -f

Docker Compose Configuration¶

The docker-compose.yml file in the project root defines the services, networks, and volumes required for the NCA system. Customize this file according to your deployment needs.

Kubernetes Deployment¶

For production environments, Kubernetes is the recommended deployment platform.

Deploying with kubectl¶

# Apply Kubernetes manifests
kubectl apply -f infrastructure/kubernetes/namespace.yaml
kubectl apply -f infrastructure/kubernetes/secrets.yaml
kubectl apply -f infrastructure/kubernetes/configmaps.yaml
kubectl apply -f infrastructure/kubernetes/deployments/
kubectl apply -f infrastructure/kubernetes/services/
kubectl apply -f infrastructure/kubernetes/ingress.yaml

# Check deployment status
kubectl get pods -n neuroca
kubectl get services -n neuroca
kubectl get ingress -n neuroca

Deploying with Helm¶

# Add the NCA Helm repository
helm repo add neuroca https://charts.neuroca.io

# Install the NCA Helm chart
helm install neuroca neuroca/neuroca -f values.yaml -n neuroca

# Upgrade an existing deployment
helm upgrade neuroca neuroca/neuroca -f values.yaml -n neuroca

Kubernetes Resource Configuration¶

Kubernetes manifests are located in the infrastructure/kubernetes/ directory. These include: - Deployments for each component - Services for internal and external access - ConfigMaps for configuration - Secrets for sensitive data - Ingress for external access - PersistentVolumeClaims for storage

Serverless Deployment¶

For certain components of the NCA system, serverless deployment options are available.

AWS Lambda¶

# Deploy using AWS SAM
cd infrastructure/serverless/aws
sam build
sam deploy --guided

Azure Functions¶

# Deploy using Azure Functions Core Tools
cd infrastructure/serverless/azure
func azure functionapp publish neuroca-functions

Configuration Management¶

Environment Variables¶

The NCA system uses environment variables for configuration. These can be set in various ways: - .env files for local development - Docker environment variables - Kubernetes ConfigMaps and Secrets - Cloud provider environment configuration

Key Configuration Parameters¶

Core Configuration¶

NEUROCA_ENV=production                # Environment (development, staging, production)
NEUROCA_DEBUG=false                   # Enable debug mode
NEUROCA_LOG_LEVEL=info                # Logging level (debug, info, warning, error)
NEUROCA_SECRET_KEY=your-secret-key    # Secret key for security features

Database Configuration¶

NEUROCA_DB_HOST=db.example.com        # Database host
NEUROCA_DB_PORT=5432                  # Database port
NEUROCA_DB_NAME=neuroca               # Database name
NEUROCA_DB_USER=dbuser                # Database user
NEUROCA_DB_PASSWORD=dbpassword        # Database password

Memory Tier Configuration¶

NEUROCA_MEMORY_SHORT_TERM_SIZE=1000   # Short-term memory capacity
NEUROCA_MEMORY_WORKING_SIZE=100       # Working memory capacity
NEUROCA_MEMORY_LONG_TERM_BACKEND=postgres  # Long-term memory backend

LLM Integration Configuration¶

NEUROCA_LLM_PROVIDER=openai           # LLM provider (openai, anthropic, etc.)
NEUROCA_LLM_API_KEY=your-api-key      # LLM API key
NEUROCA_LLM_MODEL=gpt-4               # LLM model to use

Database Setup and Migration¶

Initial Database Setup¶

# Create database schema
python -m neuroca.db.create_schema

# Run initial migrations
python -m neuroca.db.migrate

Database Migrations¶

# Generate a new migration
python -m neuroca.db.generate_migration "add_user_preferences"

# Apply pending migrations
python -m neuroca.db.migrate

# Rollback the last migration
python -m neuroca.db.rollback

Database Backup and Restore¶

# Backup database
python -m neuroca.db.backup --output=backup.sql

# Restore database
python -m neuroca.db.restore --input=backup.sql

Security Considerations¶

Authentication and Authorization¶

Use OAuth2 or OpenID Connect for authentication
Implement role-based access control (RBAC)
Secure API endpoints with proper authentication
Rotate credentials regularly

Data Protection¶

Encrypt sensitive data at rest and in transit
Use TLS/SSL for all communications
Implement data masking for sensitive information
Follow data retention policies

Network Security¶

Use network segmentation
Implement firewall rules
Use private networks for internal communication
Configure proper ingress and egress rules

Secrets Management¶

Use a secrets management solution (HashiCorp Vault, AWS Secrets Manager, etc.)
Never store secrets in code or configuration files
Rotate secrets regularly
Implement least privilege access

Monitoring and Observability¶

Metrics Collection¶

Use Prometheus for metrics collection
Configure metrics exporters for each component
Set up alerting rules for critical metrics

Logging¶

Use structured logging
Configure log aggregation (ELK stack, Loki, etc.)
Implement log retention policies
Set appropriate log levels

Tracing¶

Implement distributed tracing with OpenTelemetry
Configure sampling rates
Visualize traces with Jaeger or Zipkin

Alerting¶

Configure alerts for critical issues
Set up notification channels (email, Slack, PagerDuty)
Implement escalation policies
Document alert response procedures

Scaling Strategies¶

Horizontal Scaling¶

Scale API servers based on CPU/memory usage
Configure auto-scaling for worker nodes
Use load balancers to distribute traffic

Vertical Scaling¶

Increase resources for database servers
Upgrade instance types for compute-intensive components
Monitor resource usage to determine scaling needs

Database Scaling¶

Implement read replicas for read-heavy workloads
Consider sharding for large datasets
Use connection pooling

Caching Strategies¶

Implement Redis for distributed caching
Configure cache invalidation policies
Monitor cache hit/miss rates

Backup and Disaster Recovery¶

Backup Procedures¶

Schedule regular database backups
Back up configuration and state
Store backups in multiple locations
Test backup integrity regularly

Disaster Recovery Plan¶

Document recovery procedures
Define Recovery Time Objective (RTO) and Recovery Point Objective (RPO)
Implement multi-region redundancy for critical components
Conduct regular disaster recovery drills

High Availability Configuration¶

Deploy components across multiple availability zones
Implement redundancy for critical services
Configure automatic failover
Use stateless design where possible

Continuous Integration/Continuous Deployment¶

CI/CD Pipeline¶

Use GitHub Actions, Jenkins, or GitLab CI for automation
Implement automated testing
Configure deployment approvals for production
Automate infrastructure updates

Deployment Strategies¶

Blue/Green deployment
Canary releases
Feature flags for gradual rollout
A/B testing capabilities

Example CI/CD Workflow¶

# Example GitHub Actions workflow
name: Deploy NCA

on:
  push:
    branches: [main]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Run tests
        run: make test

  build:
    needs: test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Build Docker image
        run: make build

  deploy:
    needs: build
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Deploy to Kubernetes
        run: make deploy

Rollback Procedures¶

Application Rollback¶

# Rollback Kubernetes deployment
kubectl rollout undo deployment/neuroca-api -n neuroca

# Rollback using Helm
helm rollback neuroca 1 -n neuroca

Database Rollback¶

# Rollback database migration
python -m neuroca.db.rollback

# Restore from backup
python -m neuroca.db.restore --input=backup.sql

Configuration Rollback¶

# Revert ConfigMap changes
kubectl apply -f infrastructure/kubernetes/configmaps-previous.yaml

# Restart affected pods
kubectl rollout restart deployment/neuroca-api -n neuroca

Troubleshooting¶

Common Issues and Solutions¶

Application Not Starting¶

Check logs: kubectl logs deployment/neuroca-api -n neuroca
Verify configuration: kubectl describe configmap neuroca-config -n neuroca
Check resource constraints: kubectl describe pod -n neuroca

Database Connection Issues¶

Verify connection string
Check network policies
Ensure database is running
Verify credentials

Performance Issues¶

Check resource usage
Analyze slow queries
Review application logs
Check external service dependencies

Debugging Tools¶

kubectl exec -it pod-name -n neuroca -- bash for shell access
kubectl port-forward service/neuroca-api 8000:8000 -n neuroca for local access
kubectl get events -n neuroca for cluster events
Application health endpoints: /health, /metrics

Maintenance Procedures¶

Routine Maintenance¶

Database optimization
Log rotation and cleanup
Certificate renewal
Security patches

Upgrade Procedures¶

# Update application version
kubectl set image deployment/neuroca-api neuroca-api=neuroca/api:1.2.3 -n neuroca

# Update Helm release
helm upgrade neuroca neuroca/neuroca -f values.yaml -n neuroca

Scheduled Maintenance Windows¶

Plan maintenance during low-traffic periods
Communicate maintenance windows to users
Implement maintenance mode for user-facing components
Document step-by-step procedures for each maintenance task

This deployment guide is a living document and will be updated as the NCA system evolves. For questions or assistance, contact the operations team at ops@neuroca.io.