60. Distributed Disaster Recovery and Self-Healing System¶
Overview¶
The Distributed Disaster Recovery and Self-Healing System provides comprehensive fault tolerance and automatic recovery capabilities for the entire quantitative trading platform. The system implements distributed deployment with redundant service replicas, automatic fault detection, seamless failover mechanisms, and state synchronization to ensure continuous operation even during hardware failures, network issues, or service disruptions.
Core Capabilities¶
- Distributed Deployment: Active/Active and Active/Standby redundancy across all critical services
- Automatic Fault Detection: Real-time heartbeat monitoring and health checking
- Seamless Failover: Automatic traffic redirection to healthy nodes
- Self-Healing: Automatic service restart and recovery mechanisms
- State Synchronization: Real-time state replication across redundant nodes
- Cross-Region Recovery: Geographic redundancy and disaster recovery
- Chaos Engineering: Automated fault injection and resilience testing
- Recovery Reporting: Comprehensive post-incident analysis and reporting
System Architecture¶
Microservice: disaster-recovery-center¶
services/disaster-recovery-center/
├── src/
│ ├── main.py
│ ├── monitor/
│ │ ├── heartbeat_monitor.py
│ │ ├── health_probe.py
│ │ └── service_monitor.py
│ ├── detector/
│ │ ├── failure_detector.py
│ │ ├── anomaly_detector.py
│ │ └── performance_monitor.py
│ ├── controller/
│ │ ├── failover_controller.py
│ │ ├── self_healing_scheduler.py
│ │ └── load_balancer.py
│ ├── synchronizer/
│ │ ├── state_synchronizer.py
│ │ ├── data_replicator.py
│ │ └── consistency_manager.py
│ ├── api/
│ │ ├── recovery_api.py
│ │ ├── config.py
│ │ └── requirements.txt
│ ├── Dockerfile
│ └── tests/
Core Components¶
1. Heartbeat Monitor¶
Real-time service health monitoring:
class HeartbeatMonitor:
def __init__(self, service_monitor):
self.service_monitor = service_monitor
self.heartbeat_interval = 5 # seconds
self.timeout_threshold = 15 # seconds
self.heartbeat_history = {}
self.active_monitors = {}
async def start_monitoring(self):
"""Start heartbeat monitoring for all services"""
# Get all registered services
services = await self.get_registered_services()
for service in services:
await self.start_service_monitoring(service)
async def start_service_monitoring(self, service: Dict):
"""Start monitoring a specific service"""
service_name = service["name"]
service_endpoints = service["endpoints"]
# Create heartbeat monitor for service
monitor = ServiceHeartbeatMonitor(
service_name=service_name,
endpoints=service_endpoints,
interval=self.heartbeat_interval,
timeout=self.timeout_threshold
)
self.active_monitors[service_name] = monitor
# Start monitoring task
asyncio.create_task(self.monitor_service_heartbeat(monitor))
async def monitor_service_heartbeat(self, monitor):
"""Monitor heartbeat for a specific service"""
while True:
try:
# Send heartbeat ping
heartbeat_result = await monitor.send_heartbeat()
# Record heartbeat result
await self.record_heartbeat_result(monitor.service_name, heartbeat_result)
# Check for failures
if not heartbeat_result["alive"]:
await self.handle_service_failure(monitor.service_name, heartbeat_result)
# Wait for next heartbeat
await asyncio.sleep(self.heartbeat_interval)
except Exception as e:
print(f"Error monitoring heartbeat for {monitor.service_name}: {e}")
await asyncio.sleep(1)
async def send_heartbeat(self, service_name: str, endpoint: str) -> Dict:
"""Send heartbeat ping to service endpoint"""
try:
start_time = time.time()
# Send HTTP ping
async with aiohttp.ClientSession() as session:
async with session.get(f"{endpoint}/health/heartbeat", timeout=5) as response:
response_time = time.time() - start_time
if response.status == 200:
return {
"alive": True,
"response_time": response_time,
"status_code": response.status,
"timestamp": datetime.now().isoformat()
}
else:
return {
"alive": False,
"response_time": response_time,
"status_code": response.status,
"error": f"HTTP {response.status}",
"timestamp": datetime.now().isoformat()
}
except asyncio.TimeoutError:
return {
"alive": False,
"response_time": 5.0,
"error": "timeout",
"timestamp": datetime.now().isoformat()
}
except Exception as e:
return {
"alive": False,
"response_time": 0.0,
"error": str(e),
"timestamp": datetime.now().isoformat()
}
async def record_heartbeat_result(self, service_name: str, result: Dict):
"""Record heartbeat result"""
if service_name not in self.heartbeat_history:
self.heartbeat_history[service_name] = []
self.heartbeat_history[service_name].append(result)
# Keep history manageable
if len(self.heartbeat_history[service_name]) > 1000:
self.heartbeat_history[service_name] = self.heartbeat_history[service_name][-1000:]
async def handle_service_failure(self, service_name: str, heartbeat_result: Dict):
"""Handle service failure detected by heartbeat"""
failure_event = {
"service_name": service_name,
"failure_type": "heartbeat_failure",
"heartbeat_result": heartbeat_result,
"timestamp": datetime.now().isoformat()
}
# Trigger failure detection
await self.trigger_failure_detection(failure_event)
async def get_service_heartbeat_status(self, service_name: str) -> Dict:
"""Get heartbeat status for a service"""
if service_name not in self.heartbeat_history:
return {"status": "unknown", "last_check": None}
history = self.heartbeat_history[service_name]
if not history:
return {"status": "unknown", "last_check": None}
latest = history[-1]
return {
"service_name": service_name,
"status": "alive" if latest["alive"] else "dead",
"last_check": latest["timestamp"],
"response_time": latest.get("response_time", 0),
"error": latest.get("error", None)
}
async def get_all_heartbeat_status(self) -> Dict:
"""Get heartbeat status for all services"""
status = {}
for service_name in self.active_monitors.keys():
status[service_name] = await self.get_service_heartbeat_status(service_name)
return {
"services": status,
"total_services": len(status),
"alive_services": len([s for s in status.values() if s["status"] == "alive"]),
"dead_services": len([s for s in status.values() if s["status"] == "dead"]),
"timestamp": datetime.now().isoformat()
}
2. Health Probe¶
Comprehensive service health checking:
class HealthProbe:
def __init__(self):
self.health_checks = {}
self.probe_interval = 30 # seconds
self.health_history = {}
async def start_health_probing(self):
"""Start health probing for all services"""
services = await self.get_registered_services()
for service in services:
await self.start_service_probing(service)
async def start_service_probing(self, service: Dict):
"""Start health probing for a specific service"""
service_name = service["name"]
health_endpoints = service.get("health_endpoints", [])
# Create health check configuration
health_config = {
"service_name": service_name,
"endpoints": health_endpoints,
"checks": service.get("health_checks", []),
"interval": self.probe_interval
}
self.health_checks[service_name] = health_config
# Start probing task
asyncio.create_task(self.probe_service_health(health_config))
async def probe_service_health(self, config: Dict):
"""Probe health for a specific service"""
while True:
try:
# Perform health checks
health_result = await self.perform_health_checks(config)
# Record health result
await self.record_health_result(config["service_name"], health_result)
# Check for health issues
if not health_result["healthy"]:
await self.handle_health_issue(config["service_name"], health_result)
# Wait for next probe
await asyncio.sleep(config["interval"])
except Exception as e:
print(f"Error probing health for {config['service_name']}: {e}")
await asyncio.sleep(5)
async def perform_health_checks(self, config: Dict) -> Dict:
"""Perform comprehensive health checks"""
service_name = config["service_name"]
endpoints = config["endpoints"]
checks = config["checks"]
health_results = {}
# Check each endpoint
for endpoint in endpoints:
endpoint_result = await self.check_endpoint_health(endpoint)
health_results[endpoint] = endpoint_result
# Perform custom health checks
for check in checks:
check_result = await self.perform_custom_check(service_name, check)
health_results[check["name"]] = check_result
# Determine overall health
all_healthy = all(result["healthy"] for result in health_results.values())
return {
"service_name": service_name,
"healthy": all_healthy,
"checks": health_results,
"timestamp": datetime.now().isoformat()
}
async def check_endpoint_health(self, endpoint: str) -> Dict:
"""Check health of a specific endpoint"""
try:
start_time = time.time()
async with aiohttp.ClientSession() as session:
async with session.get(f"{endpoint}/health", timeout=10) as response:
response_time = time.time() - start_time
if response.status == 200:
health_data = await response.json()
return {
"healthy": True,
"response_time": response_time,
"status_code": response.status,
"health_data": health_data
}
else:
return {
"healthy": False,
"response_time": response_time,
"status_code": response.status,
"error": f"HTTP {response.status}"
}
except Exception as e:
return {
"healthy": False,
"response_time": 0.0,
"error": str(e)
}
async def perform_custom_check(self, service_name: str, check: Dict) -> Dict:
"""Perform custom health check"""
check_type = check["type"]
check_config = check.get("config", {})
try:
if check_type == "database":
return await self.check_database_health(service_name, check_config)
elif check_type == "cache":
return await self.check_cache_health(service_name, check_config)
elif check_type == "queue":
return await self.check_queue_health(service_name, check_config)
elif check_type == "api":
return await self.check_api_health(service_name, check_config)
else:
return {
"healthy": False,
"error": f"Unknown check type: {check_type}"
}
except Exception as e:
return {
"healthy": False,
"error": str(e)
}
async def check_database_health(self, service_name: str, config: Dict) -> Dict:
"""Check database health"""
try:
# This would integrate with database connection
# For now, return placeholder
return {
"healthy": True,
"connection_pool": "ok",
"query_time": 0.001
}
except Exception as e:
return {
"healthy": False,
"error": str(e)
}
async def check_cache_health(self, service_name: str, config: Dict) -> Dict:
"""Check cache health"""
try:
# This would integrate with cache system
# For now, return placeholder
return {
"healthy": True,
"cache_hit_rate": 0.95,
"memory_usage": "75%"
}
except Exception as e:
return {
"healthy": False,
"error": str(e)
}
async def record_health_result(self, service_name: str, result: Dict):
"""Record health check result"""
if service_name not in self.health_history:
self.health_history[service_name] = []
self.health_history[service_name].append(result)
# Keep history manageable
if len(self.health_history[service_name]) > 100:
self.health_history[service_name] = self.health_history[service_name][-100:]
async def get_service_health_status(self, service_name: str) -> Dict:
"""Get health status for a service"""
if service_name not in self.health_history:
return {"status": "unknown", "last_check": None}
history = self.health_history[service_name]
if not history:
return {"status": "unknown", "last_check": None}
latest = history[-1]
return {
"service_name": service_name,
"status": "healthy" if latest["healthy"] else "unhealthy",
"last_check": latest["timestamp"],
"checks": latest["checks"]
}
3. Failure Detector¶
Intelligent failure detection and analysis:
class FailureDetector:
def __init__(self, anomaly_detector, performance_monitor):
self.anomaly_detector = anomaly_detector
self.performance_monitor = performance_monitor
self.failure_history = []
self.detection_rules = self.load_detection_rules()
async def detect_failures(self, heartbeat_status: Dict, health_status: Dict) -> List[Dict]:
"""Detect failures based on heartbeat and health status"""
failures = []
# Check each service
for service_name in heartbeat_status["services"]:
heartbeat = heartbeat_status["services"][service_name]
health = health_status.get("services", {}).get(service_name, {})
# Detect failures
service_failures = await self.detect_service_failures(service_name, heartbeat, health)
failures.extend(service_failures)
# Detect system-wide failures
system_failures = await self.detect_system_failures(heartbeat_status, health_status)
failures.extend(system_failures)
# Record failures
for failure in failures:
await self.record_failure(failure)
return failures
async def detect_service_failures(self, service_name: str, heartbeat: Dict, health: Dict) -> List[Dict]:
"""Detect failures for a specific service"""
failures = []
# Check heartbeat failure
if heartbeat["status"] == "dead":
failures.append({
"type": "heartbeat_failure",
"service_name": service_name,
"severity": "critical",
"description": f"Service {service_name} is not responding to heartbeat",
"heartbeat_status": heartbeat,
"timestamp": datetime.now().isoformat()
})
# Check health failure
if health.get("status") == "unhealthy":
failures.append({
"type": "health_failure",
"service_name": service_name,
"severity": "high",
"description": f"Service {service_name} is unhealthy",
"health_status": health,
"timestamp": datetime.now().isoformat()
})
# Check performance degradation
performance_issues = await self.detect_performance_issues(service_name, heartbeat, health)
failures.extend(performance_issues)
return failures
async def detect_performance_issues(self, service_name: str, heartbeat: Dict, health: Dict) -> List[Dict]:
"""Detect performance degradation"""
issues = []
# Check response time
response_time = heartbeat.get("response_time", 0)
if response_time > self.detection_rules["max_response_time"]:
issues.append({
"type": "performance_degradation",
"service_name": service_name,
"severity": "medium",
"description": f"Service {service_name} response time {response_time}s exceeds threshold",
"metric": "response_time",
"value": response_time,
"threshold": self.detection_rules["max_response_time"],
"timestamp": datetime.now().isoformat()
})
# Check error rate
if "error" in heartbeat:
issues.append({
"type": "error_rate_increase",
"service_name": service_name,
"severity": "high",
"description": f"Service {service_name} is returning errors",
"error": heartbeat["error"],
"timestamp": datetime.now().isoformat()
})
return issues
async def detect_system_failures(self, heartbeat_status: Dict, health_status: Dict) -> List[Dict]:
"""Detect system-wide failures"""
failures = []
total_services = heartbeat_status["total_services"]
dead_services = heartbeat_status["dead_services"]
# Check if too many services are down
failure_rate = dead_services / total_services if total_services > 0 else 0
if failure_rate > self.detection_rules["max_failure_rate"]:
failures.append({
"type": "system_failure",
"severity": "critical",
"description": f"System failure rate {failure_rate:.2%} exceeds threshold",
"failure_rate": failure_rate,
"dead_services": dead_services,
"total_services": total_services,
"timestamp": datetime.now().isoformat()
})
# Check for cascade failures
cascade_failures = await self.detect_cascade_failures(heartbeat_status)
failures.extend(cascade_failures)
return failures
async def detect_cascade_failures(self, heartbeat_status: Dict) -> List[Dict]:
"""Detect cascade failures"""
failures = []
# Check for related service failures
failed_services = [
name for name, status in heartbeat_status["services"].items()
if status["status"] == "dead"
]
# Group by service type
service_groups = self.group_services_by_type(failed_services)
for group_name, services in service_groups.items():
if len(services) > 1:
failures.append({
"type": "cascade_failure",
"severity": "high",
"description": f"Cascade failure detected in {group_name} services",
"affected_services": services,
"group": group_name,
"timestamp": datetime.now().isoformat()
})
return failures
def group_services_by_type(self, services: List[str]) -> Dict[str, List[str]]:
"""Group services by type"""
groups = {}
for service in services:
# Extract service type from name
if "trading" in service:
group = "trading"
elif "risk" in service:
group = "risk"
elif "data" in service:
group = "data"
elif "api" in service:
group = "api"
else:
group = "other"
if group not in groups:
groups[group] = []
groups[group].append(service)
return groups
async def record_failure(self, failure: Dict):
"""Record failure event"""
self.failure_history.append(failure)
# Keep history manageable
if len(self.failure_history) > 1000:
self.failure_history = self.failure_history[-1000:]
def load_detection_rules(self) -> Dict:
"""Load failure detection rules"""
return {
"max_response_time": 5.0, # 5 seconds
"max_failure_rate": 0.3, # 30% failure rate
"heartbeat_timeout": 15, # 15 seconds
"health_check_interval": 30, # 30 seconds
"failure_threshold": 3 # 3 consecutive failures
}
API Design¶
Disaster Recovery API¶
@router.get("/recovery/status")
async def get_recovery_status():
"""Get overall recovery system status"""
heartbeat_status = await heartbeat_monitor.get_all_heartbeat_status()
health_status = await health_probe.get_all_health_status()
failures = await failure_detector.detect_failures(heartbeat_status, health_status)
return {
"heartbeat_status": heartbeat_status,
"health_status": health_status,
"failures": failures,
"system_health": "healthy" if not failures else "degraded",
"timestamp": datetime.now().isoformat()
}
@router.get("/recovery/services")
async def get_services_status():
"""Get status of all services"""
services = await get_all_services_status()
return {
"services": services,
"total_services": len(services),
"healthy_services": len([s for s in services if s["status"] == "healthy"]),
"timestamp": datetime.now().isoformat()
}
@router.get("/recovery/failures")
async def get_recent_failures(hours: int = 24):
"""Get recent failures"""
cutoff_time = datetime.now() - timedelta(hours=hours)
recent_failures = [
failure for failure in failure_detector.failure_history
if datetime.fromisoformat(failure["timestamp"]) > cutoff_time
]
return {
"failures": recent_failures,
"total_count": len(recent_failures),
"critical_count": len([f for f in recent_failures if f["severity"] == "critical"]),
"time_period_hours": hours,
"timestamp": datetime.now().isoformat()
}
@router.post("/recovery/failover/{service_name}")
async def trigger_failover(service_name: str):
"""Manually trigger failover for a service"""
result = await failover_controller.trigger_failover(service_name)
return {
"service_name": service_name,
"failover_result": result,
"timestamp": datetime.now().isoformat()
}
@router.post("/recovery/restart/{service_name}")
async def restart_service(service_name: str):
"""Manually restart a service"""
result = await self_healing_scheduler.restart_service(service_name)
return {
"service_name": service_name,
"restart_result": result,
"timestamp": datetime.now().isoformat()
}
@router.get("/recovery/synchronization")
async def get_synchronization_status():
"""Get state synchronization status"""
sync_status = await state_synchronizer.get_synchronization_status()
return {
"synchronization": sync_status,
"timestamp": datetime.now().isoformat()
}
Frontend Integration¶
Disaster Recovery Dashboard¶
const DisasterRecoveryView: React.FC = () => {
const [recoveryStatus, setRecoveryStatus] = useState<RecoveryStatus | null>(null);
const [servicesStatus, setServicesStatus] = useState<ServiceStatus[]>([]);
const [recentFailures, setRecentFailures] = useState<Failure[]>([]);
const [syncStatus, setSyncStatus] = useState<SynchronizationStatus | null>(null);
return (
<div className="disaster-recovery-dashboard">
{/* System Health Overview */}
<SystemHealthPanel
status={recoveryStatus}
/>
{/* Service Status Grid */}
<ServiceStatusGrid
services={servicesStatus}
onServiceSelect={handleServiceSelect}
/>
{/* Recent Failures */}
<RecentFailuresPanel
failures={recentFailures}
onFailureSelect={handleFailureSelect}
/>
{/* Failover Controls */}
<FailoverControlsPanel
onFailoverTrigger={handleFailoverTrigger}
onServiceRestart={handleServiceRestart}
/>
{/* Synchronization Status */}
<SynchronizationPanel
status={syncStatus}
/>
{/* Recovery History */}
<RecoveryHistoryPanel
history={recoveryHistory}
/>
{/* Performance Metrics */}
<PerformanceMetricsPanel
metrics={performanceMetrics}
/>
{/* Manual Controls */}
<ManualControlsPanel
onManualAction={handleManualAction}
/>
</div>
);
};
Implementation Roadmap¶
Phase 1: Core Monitoring (Weeks 1-2)¶
- Implement heartbeat monitoring
- Set up health checking framework
- Create basic failure detection
Phase 2: Failover & Recovery (Weeks 3-4)¶
- Implement automatic failover mechanisms
- Develop self-healing capabilities
- Build state synchronization
Phase 3: Advanced Features (Weeks 5-6)¶
- Implement cross-region recovery
- Develop chaos engineering capabilities
- Build comprehensive reporting
Phase 4: Optimization & Testing (Weeks 7-8)¶
- Performance optimization
- Extensive testing and validation
- Production deployment and monitoring
Business Value¶
Strategic Benefits¶
- High Availability: 99.99%+ uptime through automatic failover
- Fault Tolerance: Continuous operation during hardware/network failures
- Zero Downtime: Seamless service transitions without interruption
- Disaster Recovery: Geographic redundancy and recovery capabilities
Operational Benefits¶
- Automated Recovery: No manual intervention required for most failures
- Real-Time Monitoring: Continuous visibility into system health
- Proactive Detection: Early identification of potential issues
- Comprehensive Reporting: Complete audit trail of all recovery events
Technical Specifications¶
Performance Requirements¶
- Heartbeat Interval: < 5 seconds for service monitoring
- Failover Time: < 30 seconds for automatic failover
- Recovery Time: < 60 seconds for service restart
- State Sync: < 100ms for critical state synchronization
Reliability Requirements¶
- Availability: 99.99% uptime target
- Data Loss: Zero data loss during failover
- Consistency: Strong consistency across redundant nodes
- Recovery: Automatic recovery from any single point of failure
Integration Requirements¶
- Load Balancing: Integration with load balancers and traffic managers
- Service Discovery: Dynamic service registration and discovery
- Configuration Management: Centralized configuration and deployment
- Monitoring: Integration with monitoring and alerting systems
This Distributed Disaster Recovery and Self-Healing System provides mission-critical fault tolerance and automatic recovery capabilities, ensuring continuous operation of the quantitative trading platform even during severe infrastructure failures, similar to the systems used by major exchanges and financial institutions.