TINAA Enterprise Guide

Enterprise-Grade Deployment and Management

Complete guide for deploying, scaling, and managing TINAA in enterprise environments.

---

Table of Contents

1. Enterprise Architecture
2. Production Deployment
3. Security & Compliance
4. Scaling & Performance
5. Monitoring & Observability
6. Team Management
7. Integration Patterns
8. Governance & Best Practices
9. Support & Maintenance

---

Enterprise Architecture

Reference Architecture

graph TB
    subgraph "Load Balancing Layer"
        LB[Load Balancer<br/>NGINX/HAProxy]
        CDN[CDN/WAF<br/>CloudFlare/AWS CloudFront]
    end

    subgraph "API Gateway Layer"
        AG[API Gateway<br/>Kong/AWS API Gateway]
        AUTH[Authentication<br/>OAuth2/SAML]
    end

    subgraph "Application Layer"
        TINAA1[TINAA Instance 1]
        TINAA2[TINAA Instance 2]
        TINAA3[TINAA Instance 3]
    end

    subgraph "Data Layer"
        REDIS[Redis Cache<br/>Session/Results]
        POSTGRES[PostgreSQL<br/>Metadata/Audit]
        S3[Object Storage<br/>Screenshots/Reports]
    end

    subgraph "Monitoring Layer"
        PROM[Prometheus<br/>Metrics]
        GRAF[Grafana<br/>Dashboards]
        ELK[ELK Stack<br/>Logging]
    end

    CDN --> LB
    LB --> AG
    AG --> AUTH
    AUTH --> TINAA1
    AUTH --> TINAA2
    AUTH --> TINAA3

    TINAA1 --> REDIS
    TINAA1 --> POSTGRES
    TINAA1 --> S3

    TINAA1 --> PROM
    PROM --> GRAF
    TINAA1 --> ELK

Component Specifications

Component	Purpose	Recommended Technology
Load Balancer	Traffic distribution	NGINX Plus, HAProxy, AWS ALB
API Gateway	Rate limiting, auth	Kong, AWS API Gateway, Zuul
Container Orchestration	Service management	Kubernetes, Docker Swarm
Cache Layer	Performance optimization	Redis Cluster, Memcached
Database	Persistent storage	PostgreSQL, MySQL
Object Storage	File storage	AWS S3, Azure Blob, MinIO
Monitoring	Observability	Prometheus + Grafana
Logging	Audit and debugging	ELK Stack, Splunk

---

Production Deployment

Kubernetes Deployment

1. Namespace and ConfigMap

# k8s/namespace.yaml
apiVersion: v1
kind: Namespace
metadata:
  name: tinaa-production
  labels:
    app: tinaa
    environment: production

---
# k8s/configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: tinaa-config
  namespace: tinaa-production
data:
  TINAA_MODE: "http"
  LOG_LEVEL: "INFO"
  REDIS_URL: "redis://redis-service:6379"
  POSTGRES_URL: "postgresql://tinaa:password@postgres-service:5432/tinaa"
  MAX_CONCURRENT_TESTS: "10"
  DEFAULT_TIMEOUT: "60000"
  SCREENSHOT_STORAGE: "s3"
  S3_BUCKET: "tinaa-screenshots"

2. Deployment Configuration

# k8s/deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: tinaa-deployment
  namespace: tinaa-production
  labels:
    app: tinaa
    version: v1.0.0
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  selector:
    matchLabels:
      app: tinaa
  template:
    metadata:
      labels:
        app: tinaa
        version: v1.0.0
    spec:
      containers:
      - name: tinaa
        image: tinaa-playwright-msp:1.0.0
        ports:
        - containerPort: 8765
          name: http
        env:
        - name: TINAA_MODE
          valueFrom:
            configMapKeyRef:
              name: tinaa-config
              key: TINAA_MODE
        envFrom:
        - configMapRef:
            name: tinaa-config
        resources:
          requests:
            memory: "2Gi"
            cpu: "500m"
          limits:
            memory: "4Gi"
            cpu: "2000m"
        livenessProbe:
          httpGet:
            path: /health
            port: 8765
          initialDelaySeconds: 30
          periodSeconds: 10
          timeoutSeconds: 5
        readinessProbe:
          httpGet:
            path: /health
            port: 8765
          initialDelaySeconds: 5
          periodSeconds: 5
          timeoutSeconds: 3
        volumeMounts:
        - name: browser-cache
          mountPath: /ms-playwright
        - name: tmp-storage
          mountPath: /tmp
      volumes:
      - name: browser-cache
        emptyDir:
          sizeLimit: 2Gi
      - name: tmp-storage
        emptyDir:
          sizeLimit: 1Gi
      securityContext:
        runAsNonRoot: true
        runAsUser: 1000
        fsGroup: 1000

3. Service and Ingress

# k8s/service.yaml
apiVersion: v1
kind: Service
metadata:
  name: tinaa-service
  namespace: tinaa-production
  labels:
    app: tinaa
spec:
  type: ClusterIP
  ports:
  - port: 80
    targetPort: 8765
    protocol: TCP
    name: http
  selector:
    app: tinaa

---
# k8s/ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: tinaa-ingress
  namespace: tinaa-production
  annotations:
    nginx.ingress.kubernetes.io/rewrite-target: /
    nginx.ingress.kubernetes.io/rate-limit: "100"
    nginx.ingress.kubernetes.io/rate-limit-window: "1m"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
spec:
  tls:
  - hosts:
    - tinaa.yourcompany.com
    secretName: tinaa-tls
  rules:
  - host: tinaa.yourcompany.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: tinaa-service
            port:
              number: 80

4. Horizontal Pod Autoscaler

# k8s/hpa.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: tinaa-hpa
  namespace: tinaa-production
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: tinaa-deployment
  minReplicas: 3
  maxReplicas: 20
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80
  behavior:
    scaleUp:
      stabilizationWindowSeconds: 60
      policies:
      - type: Percent
        value: 50
        periodSeconds: 60
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
      - type: Percent
        value: 25
        periodSeconds: 60

Docker Swarm Deployment

# docker-compose.prod.yml
version: '3.8'

services:
  tinaa:
    image: tinaa-playwright-msp:1.0.0
    networks:
      - tinaa-network
    environment:
      - TINAA_MODE=http
      - LOG_LEVEL=INFO
      - REDIS_URL=redis://redis:6379
      - POSTGRES_URL=postgresql://tinaa:${POSTGRES_PASSWORD}@postgres:5432/tinaa
    deploy:
      replicas: 3
      update_config:
        parallelism: 1
        delay: 10s
        order: start-first
      restart_policy:
        condition: on-failure
        delay: 5s
        max_attempts: 3
      resources:
        limits:
          memory: 4G
          cpus: '2'
        reservations:
          memory: 2G
          cpus: '0.5'
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8765/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

  nginx:
    image: nginx:alpine
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - ./nginx.conf:/etc/nginx/nginx.conf:ro
      - ./ssl:/etc/nginx/ssl:ro
    networks:
      - tinaa-network
    deploy:
      replicas: 2
      update_config:
        parallelism: 1
        delay: 10s

  redis:
    image: redis:7-alpine
    networks:
      - tinaa-network
    volumes:
      - redis_data:/data
    deploy:
      replicas: 1
      restart_policy:
        condition: on-failure

  postgres:
    image: postgres:15
    environment:
      POSTGRES_DB: tinaa
      POSTGRES_USER: tinaa
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
    volumes:
      - postgres_data:/var/lib/postgresql/data
    networks:
      - tinaa-network
    deploy:
      replicas: 1
      restart_policy:
        condition: on-failure

networks:
  tinaa-network:
    driver: overlay
    attachable: true

volumes:
  redis_data:
  postgres_data:

---

Security & Compliance

Authentication & Authorization

1. OAuth2 Integration

# app/auth/oauth2.py
from authlib.integrations.fastapi_oauth2 import AuthorizationServer
from authlib.integrations.sqla_oauth2 import (
    OAuth2ClientMixin,
    OAuth2TokenMixin,
)
from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
import jwt
from datetime import datetime, timedelta

class EnterpriseAuth:
    def __init__(self, config):
        self.config = config
        self.oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

    async def authenticate_user(self, token: str = Depends(oauth2_scheme)):
        """Authenticate user with OAuth2 token."""
        try:
            payload = jwt.decode(
                token,
                self.config.JWT_SECRET,
                algorithms=[self.config.JWT_ALGORITHM]
            )

            username = payload.get("sub")
            if username is None:
                raise HTTPException(
                    status_code=status.HTTP_401_UNAUTHORIZED,
                    detail="Invalid authentication credentials"
                )

            # Verify user exists and has required permissions
            user = await self.get_user(username)
            if not user or not user.is_active:
                raise HTTPException(
                    status_code=status.HTTP_401_UNAUTHORIZED,
                    detail="User not found or inactive"
                )

            return user

        except jwt.PyJWTError:
            raise HTTPException(
                status_code=status.HTTP_401_UNAUTHORIZED,
                detail="Could not validate credentials"
            )

    async def check_permissions(self, user, required_permissions: list):
        """Check if user has required permissions."""
        user_permissions = await self.get_user_permissions(user.id)

        if not all(perm in user_permissions for perm in required_permissions):
            raise HTTPException(
                status_code=status.HTTP_403_FORBIDDEN,
                detail="Insufficient permissions"
            )

        return True

# Role-based access control
class Permission:
    READ_TESTS = "tests:read"
    WRITE_TESTS = "tests:write"
    EXECUTE_TESTS = "tests:execute"
    ADMIN_ACCESS = "admin:access"
    MANAGE_USERS = "users:manage"

# Protected endpoints
@app.post("/test/exploratory")
async def exploratory_test(
    request: TestRequest,
    user = Depends(auth.authenticate_user)
):
    await auth.check_permissions(user, [Permission.EXECUTE_TESTS])
    # Implementation
    pass

2. SAML SSO Integration

# app/auth/saml.py
from saml2 import BINDING_HTTP_POST, BINDING_HTTP_REDIRECT
from saml2.client import Saml2Client
from saml2.config import Config as Saml2Config

class SAMLAuth:
    def __init__(self, config):
        self.saml_config = Saml2Config()
        self.saml_config.load({
            'entityid': config.SAML_ENTITY_ID,
            'service': {
                'sp': {
                    'endpoints': {
                        'assertion_consumer_service': [
                            (config.SAML_ACS_URL, BINDING_HTTP_POST),
                        ],
                    },
                    'allow_unsolicited': True,
                    'authn_requests_signed': False,
                    'logout_requests_signed': True,
                    'want_assertions_signed': True,
                    'want_response_signed': False,
                },
            },
            'metadata': {
                'remote': [
                    {
                        'url': config.SAML_METADATA_URL,
                    },
                ],
            },
        })

        self.saml_client = Saml2Client(config=self.saml_config)

    async def initiate_login(self):
        """Initiate SAML login process."""
        reqid, info = self.saml_client.prepare_for_authenticate()

        redirect_url = None
        for key, value in info['headers']:
            if key == 'Location':
                redirect_url = value
                break

        return redirect_url, reqid

    async def process_response(self, saml_response, request_id):
        """Process SAML response and create user session."""
        authn_response = self.saml_client.parse_authn_request_response(
            saml_response,
            BINDING_HTTP_POST,
            outstanding_queries={request_id: "/"}
        )

        if authn_response is None:
            raise ValueError("Invalid SAML response")

        # Extract user attributes
        user_info = authn_response.get_identity()

        return {
            "username": user_info.get("username", [None])[0],
            "email": user_info.get("email", [None])[0],
            "groups": user_info.get("groups", []),
        }

Data Protection & Privacy

1. Data Encryption

# app/security/encryption.py
from cryptography.fernet import Fernet
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
import base64
import os

class DataEncryption:
    def __init__(self, master_key: str = None):
        if master_key:
            self.key = self._derive_key(master_key)
        else:
            self.key = Fernet.generate_key()
        self.cipher_suite = Fernet(self.key)

    def _derive_key(self, password: str) -> bytes:
        """Derive encryption key from password."""
        salt = os.environ.get('ENCRYPTION_SALT', 'default_salt').encode()
        kdf = PBKDF2HMAC(
            algorithm=hashes.SHA256(),
            length=32,
            salt=salt,
            iterations=100000,
        )
        key = base64.urlsafe_b64encode(kdf.derive(password.encode()))
        return key

    def encrypt(self, data: str) -> str:
        """Encrypt sensitive data."""
        encrypted_data = self.cipher_suite.encrypt(data.encode())
        return base64.urlsafe_b64encode(encrypted_data).decode()

    def decrypt(self, encrypted_data: str) -> str:
        """Decrypt sensitive data."""
        decoded_data = base64.urlsafe_b64decode(encrypted_data.encode())
        decrypted_data = self.cipher_suite.decrypt(decoded_data)
        return decrypted_data.decode()

# Usage for sensitive test data
encryption = DataEncryption(os.environ.get('MASTER_KEY'))

async def store_test_credentials(username: str, password: str):
    """Store test credentials securely."""
    encrypted_username = encryption.encrypt(username)
    encrypted_password = encryption.encrypt(password)

    # Store in database
    await db.store_credentials(encrypted_username, encrypted_password)

async def get_test_credentials(credential_id: str):
    """Retrieve and decrypt test credentials."""
    encrypted_creds = await db.get_credentials(credential_id)

    return {
        "username": encryption.decrypt(encrypted_creds.username),
        "password": encryption.decrypt(encrypted_creds.password)
    }

2. Audit Logging

# app/security/audit.py
import json
import asyncio
from datetime import datetime
from typing import Dict, Any
import structlog

class AuditLogger:
    def __init__(self, config):
        self.config = config
        self.logger = structlog.get_logger("audit")

    async def log_action(
        self,
        user_id: str,
        action: str,
        resource: str,
        result: str,
        details: Dict[str, Any] = None
    ):
        """Log user action for audit trail."""
        audit_record = {
            "timestamp": datetime.utcnow().isoformat(),
            "user_id": user_id,
            "action": action,
            "resource": resource,
            "result": result,
            "details": details or {},
            "session_id": getattr(self, 'current_session_id', None),
            "ip_address": getattr(self, 'current_ip', None),
            "user_agent": getattr(self, 'current_user_agent', None)
        }

        # Log to structured logging
        self.logger.info(
            "audit_event",
            **audit_record
        )

        # Store in audit database
        await self._store_audit_record(audit_record)

    async def _store_audit_record(self, record: Dict[str, Any]):
        """Store audit record in database."""
        # Implementation depends on your database choice
        pass

# Audit middleware
async def audit_middleware(request: Request, call_next):
    """Middleware to capture audit information."""
    start_time = time.time()

    # Extract request information
    user_id = getattr(request.state, 'user_id', 'anonymous')
    action = f"{request.method} {request.url.path}"

    try:
        response = await call_next(request)

        # Log successful action
        await audit_logger.log_action(
            user_id=user_id,
            action=action,
            resource=str(request.url),
            result="success",
            details={
                "status_code": response.status_code,
                "duration_ms": round((time.time() - start_time) * 1000, 2)
            }
        )

        return response

    except Exception as e:
        # Log failed action
        await audit_logger.log_action(
            user_id=user_id,
            action=action,
            resource=str(request.url),
            result="error",
            details={
                "error": str(e),
                "duration_ms": round((time.time() - start_time) * 1000, 2)
            }
        )
        raise

app.middleware("http")(audit_middleware)

Compliance Features

GDPR Compliance

# app/compliance/gdpr.py
from datetime import datetime, timedelta
from typing import List, Dict

class GDPRCompliance:
    def __init__(self, config):
        self.config = config
        self.data_retention_days = config.DATA_RETENTION_DAYS

    async def anonymize_user_data(self, user_id: str):
        """Anonymize user data for GDPR compliance."""
        # Replace personally identifiable information
        anonymized_data = {
            "user_id": f"anon_{hash(user_id)}",
            "anonymized_at": datetime.utcnow(),
            "original_user_id": None  # Remove reference
        }

        # Update all related records
        await self._anonymize_test_results(user_id, anonymized_data["user_id"])
        await self._anonymize_audit_logs(user_id, anonymized_data["user_id"])

        return anonymized_data

    async def export_user_data(self, user_id: str) -> Dict:
        """Export all user data for GDPR data portability."""
        user_data = {
            "user_info": await self._get_user_info(user_id),
            "test_results": await self._get_user_test_results(user_id),
            "audit_logs": await self._get_user_audit_logs(user_id),
            "exported_at": datetime.utcnow().isoformat()
        }

        return user_data

    async def delete_expired_data(self):
        """Delete data older than retention period."""
        cutoff_date = datetime.utcnow() - timedelta(days=self.data_retention_days)

        # Delete old test results
        deleted_count = await self._delete_old_test_results(cutoff_date)

        return {
            "deleted_records": deleted_count,
            "cutoff_date": cutoff_date.isoformat()
        }

---

Scaling & Performance

Horizontal Scaling Strategy

1. Load Balancer Configuration

# nginx.conf
upstream tinaa_backend {
    least_conn;
    server tinaa-1:8765 max_fails=3 fail_timeout=30s;
    server tinaa-2:8765 max_fails=3 fail_timeout=30s;
    server tinaa-3:8765 max_fails=3 fail_timeout=30s;

    # Health check
    keepalive 32;
}

server {
    listen 80;
    listen 443 ssl http2;
    server_name tinaa.yourcompany.com;

    # SSL configuration
    ssl_certificate /etc/ssl/certs/tinaa.crt;
    ssl_certificate_key /etc/ssl/private/tinaa.key;
    ssl_protocols TLSv1.2 TLSv1.3;
    ssl_ciphers ECDHE+AESGCM:ECDHE+CHACHA20:DHE+AESGCM:DHE+CHACHA20:!aNULL:!MD5:!DSS;

    # Rate limiting
    limit_req_zone $binary_remote_addr zone=api:10m rate=10r/s;
    limit_req zone=api burst=20 nodelay;

    # Compression
    gzip on;
    gzip_types application/json text/plain text/css application/javascript;

    location / {
        proxy_pass http://tinaa_backend;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;

        # Timeouts
        proxy_connect_timeout 60s;
        proxy_send_timeout 60s;
        proxy_read_timeout 300s;

        # Buffer settings
        proxy_buffering on;
        proxy_buffer_size 8k;
        proxy_buffers 16 8k;
    }

    # WebSocket support
    location /ws/ {
        proxy_pass http://tinaa_backend;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_read_timeout 300s;
        proxy_send_timeout 300s;
    }

    # Health check endpoint
    location /health {
        access_log off;
        proxy_pass http://tinaa_backend;
    }
}

2. Redis Cluster Setup

# redis-cluster.yml
version: '3.8'

services:
  redis-node-1:
    image: redis:7-alpine
    command: redis-server /usr/local/etc/redis/redis.conf
    volumes:
      - ./redis-cluster.conf:/usr/local/etc/redis/redis.conf
      - redis-1-data:/data
    networks:
      - redis-cluster

  redis-node-2:
    image: redis:7-alpine
    command: redis-server /usr/local/etc/redis/redis.conf
    volumes:
      - ./redis-cluster.conf:/usr/local/etc/redis/redis.conf
      - redis-2-data:/data
    networks:
      - redis-cluster

  redis-node-3:
    image: redis:7-alpine
    command: redis-server /usr/local/etc/redis/redis.conf
    volumes:
      - ./redis-cluster.conf:/usr/local/etc/redis/redis.conf
      - redis-3-data:/data
    networks:
      - redis-cluster

networks:
  redis-cluster:
    driver: overlay

volumes:
  redis-1-data:
  redis-2-data:
  redis-3-data:

# redis-cluster.conf
port 6379
cluster-enabled yes
cluster-config-file nodes.conf
cluster-node-timeout 5000
appendonly yes

Performance Optimization

1. Caching Strategy

# app/cache/distributed.py
import aioredis
import json
import pickle
from typing import Any, Optional
import hashlib

class DistributedCache:
    def __init__(self, redis_url: str):
        self.redis_url = redis_url
        self.redis = None

    async def connect(self):
        self.redis = aioredis.from_url(
            self.redis_url,
            encoding="utf-8",
            decode_responses=False,
            max_connections=20
        )

    async def get(self, key: str) -> Optional[Any]:
        """Get cached value."""
        try:
            cached_data = await self.redis.get(key)
            if cached_data:
                return pickle.loads(cached_data)
        except Exception as e:
            logger.error(f"Cache get error: {e}")
        return None

    async def set(self, key: str, value: Any, ttl: int = 300):
        """Set cached value with TTL."""
        try:
            serialized_data = pickle.dumps(value)
            await self.redis.setex(key, ttl, serialized_data)
        except Exception as e:
            logger.error(f"Cache set error: {e}")

    async def invalidate_pattern(self, pattern: str):
        """Invalidate all keys matching pattern."""
        try:
            keys = await self.redis.keys(pattern)
            if keys:
                await self.redis.delete(*keys)
        except Exception as e:
            logger.error(f"Cache invalidation error: {e}")

# Cache usage in services
cache = DistributedCache("redis://redis-cluster:6379")

async def cached_test_execution(test_config: dict):
    """Cache test execution results."""
    # Generate cache key from test configuration
    config_hash = hashlib.md5(
        json.dumps(test_config, sort_keys=True).encode()
    ).hexdigest()
    cache_key = f"test_result:{config_hash}"

    # Try to get from cache first
    cached_result = await cache.get(cache_key)
    if cached_result:
        return cached_result

    # Execute test and cache result
    result = await execute_test(test_config)
    await cache.set(cache_key, result, ttl=3600)  # Cache for 1 hour

    return result

2. Connection Pool Management

# app/database/pool.py
import asyncpg
import aioredis
from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
from sqlalchemy.orm import sessionmaker

class DatabasePool:
    def __init__(self, config):
        self.config = config
        self.postgres_engine = None
        self.redis_pool = None

    async def initialize(self):
        """Initialize database connections."""
        # PostgreSQL connection pool
        self.postgres_engine = create_async_engine(
            self.config.POSTGRES_URL,
            pool_size=20,
            max_overflow=0,
            pool_pre_ping=True,
            pool_recycle=3600
        )

        # Redis connection pool
        self.redis_pool = aioredis.ConnectionPool.from_url(
            self.config.REDIS_URL,
            max_connections=50,
            retry_on_timeout=True
        )

    async def get_postgres_session(self) -> AsyncSession:
        """Get PostgreSQL session."""
        async_session = sessionmaker(
            self.postgres_engine,
            class_=AsyncSession,
            expire_on_commit=False
        )
        return async_session()

    async def get_redis_connection(self):
        """Get Redis connection."""
        return aioredis.Redis(connection_pool=self.redis_pool)

    async def close(self):
        """Close all connections."""
        if self.postgres_engine:
            await self.postgres_engine.dispose()
        if self.redis_pool:
            await self.redis_pool.disconnect()

---

Monitoring & Observability

Prometheus Metrics

# app/monitoring/metrics.py
from prometheus_client import Counter, Histogram, Gauge, generate_latest
import time
from functools import wraps

# Define metrics
REQUEST_COUNT = Counter('tinaa_requests_total', 'Total requests', ['method', 'endpoint', 'status'])
REQUEST_DURATION = Histogram('tinaa_request_duration_seconds', 'Request duration')
ACTIVE_TESTS = Gauge('tinaa_active_tests', 'Number of active tests')
BROWSER_INSTANCES = Gauge('tinaa_browser_instances', 'Number of browser instances')
TEST_RESULTS = Counter('tinaa_test_results_total', 'Test results', ['test_type', 'result'])

def track_metrics(func):
    """Decorator to track function execution metrics."""
    @wraps(func)
    async def wrapper(*args, **kwargs):
        start_time = time.time()
        ACTIVE_TESTS.inc()

        try:
            result = await func(*args, **kwargs)
            TEST_RESULTS.labels(test_type=func.__name__, result='success').inc()
            return result
        except Exception as e:
            TEST_RESULTS.labels(test_type=func.__name__, result='error').inc()
            raise
        finally:
            ACTIVE_TESTS.dec()
            REQUEST_DURATION.observe(time.time() - start_time)

    return wrapper

# Metrics endpoint
@app.get("/metrics")
async def get_metrics():
    """Prometheus metrics endpoint."""
    return Response(generate_latest(), media_type="text/plain")

# Usage
@track_metrics
async def run_exploratory_test(url: str):
    """Tracked exploratory test execution."""
    # Implementation
    pass

Grafana Dashboard Configuration

{
  "dashboard": {
    "title": "TINAA Production Dashboard",
    "panels": [
      {
        "title": "Request Rate",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(tinaa_requests_total[5m])",
            "legendFormat": "{{method}} {{endpoint}}"
          }
        ]
      },
      {
        "title": "Response Time",
        "type": "graph",
        "targets": [
          {
            "expr": "histogram_quantile(0.95, rate(tinaa_request_duration_seconds_bucket[5m]))",
            "legendFormat": "95th percentile"
          }
        ]
      },
      {
        "title": "Active Tests",
        "type": "singlestat",
        "targets": [
          {
            "expr": "tinaa_active_tests"
          }
        ]
      },
      {
        "title": "Error Rate",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(tinaa_test_results_total{result=\"error\"}[5m])",
            "legendFormat": "Error Rate"
          }
        ]
      }
    ]
  }
}

Logging Strategy

# app/logging/structured.py
import structlog
import logging.config
from pythonjsonlogger import jsonlogger

def configure_logging(config):
    """Configure structured logging."""

    LOGGING_CONFIG = {
        "version": 1,
        "disable_existing_loggers": False,
        "formatters": {
            "json": {
                "()": jsonlogger.JsonFormatter,
                "format": "%(asctime)s %(name)s %(levelname)s %(message)s"
            }
        },
        "handlers": {
            "console": {
                "class": "logging.StreamHandler",
                "formatter": "json",
                "level": config.LOG_LEVEL
            },
            "file": {
                "class": "logging.FileHandler",
                "filename": "logs/tinaa.json",
                "formatter": "json",
                "level": config.LOG_LEVEL
            }
        },
        "loggers": {
            "tinaa": {
                "handlers": ["console", "file"],
                "level": config.LOG_LEVEL,
                "propagate": False
            }
        }
    }

    logging.config.dictConfig(LOGGING_CONFIG)

    # Configure structlog
    structlog.configure(
        processors=[
            structlog.stdlib.filter_by_level,
            structlog.stdlib.add_logger_name,
            structlog.stdlib.add_log_level,
            structlog.stdlib.PositionalArgumentsFormatter(),
            structlog.processors.TimeStamper(fmt="iso"),
            structlog.processors.StackInfoRenderer(),
            structlog.processors.format_exc_info,
            structlog.processors.UnicodeDecoder(),
            structlog.processors.JSONRenderer()
        ],
        context_class=dict,
        logger_factory=structlog.stdlib.LoggerFactory(),
        cache_logger_on_first_use=True,
    )

# Usage throughout application
logger = structlog.get_logger("tinaa.app")

async def process_test_request(request):
    logger.info(
        "test_request_started",
        url=request.url,
        test_type=request.test_type,
        user_id=request.user_id
    )

    try:
        result = await execute_test(request)
        logger.info(
            "test_request_completed",
            url=request.url,
            success=result.success,
            duration=result.duration
        )
        return result
    except Exception as e:
        logger.error(
            "test_request_failed",
            url=request.url,
            error=str(e),
            exc_info=True
        )
        raise

---

Team Management

User Roles and Permissions

Configure role-based access control for your teams:

# config/roles.yaml
roles:
  admin:
    permissions: ['*']
    description: 'Full system access'

  test_engineer:
    permissions:
      - 'tests:create'
      - 'tests:read'
      - 'tests:execute'
      - 'reports:read'
    description: 'Create and run tests'

  viewer:
    permissions:
      - 'tests:read'
      - 'reports:read'
    description: 'Read-only access'

Team Collaboration Features

• Shared test suites and resources
• Real-time collaboration on test creation
• Version control integration
• Code review workflows

---

Integration Patterns

CI/CD Integration

# .github/workflows/test.yml
name: TINAA Tests
on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Run TINAA Tests
        uses: tinaa/action@v1
        with:
          api-key: ${{ secrets.TINAA_API_KEY }}
          test-suite: 'regression'

Third-Party Integrations

• Slack notifications
• Jira issue creation
• PagerDuty alerts
• Confluence reports

---

Governance & Best Practices

Testing Standards

1. Test Naming Conventions
2. Use descriptive names
3. Include feature/component prefix

4. Version test suites

5. Code Review Process

6. All tests must be reviewed
7. Automated quality checks

8. Performance benchmarks

9. Documentation Requirements

10. Test purpose and scope
11. Prerequisites and dependencies
12. Expected outcomes

Compliance Frameworks

• SOC 2 Type II compliance
• GDPR data protection
• HIPAA for healthcare
• PCI DSS for payments

---

Support & Maintenance

Support Channels

1. Enterprise Support
2. 24/7 phone support
3. Dedicated account manager
4. Priority issue resolution

5. Custom SLAs

6. Community Support

7. GitHub discussions
8. Discord community
9. Stack Overflow

Maintenance Best Practices

• Regular dependency updates
• Security patch management
• Performance monitoring
• Capacity planning

---

This enterprise guide provides comprehensive coverage of production deployment, security, scaling, and monitoring for TINAA in enterprise environments. Each section includes practical implementation examples and enterprise-grade configurations.