Error Handling
Proper error handling is essential for building robust applications that can gracefully handle authentication failures and provide meaningful feedback to users. This guide covers common authentication errors, response formats, and troubleshooting strategies.
Overview
Effective error handling is crucial for building robust authentication systems that can gracefully handle failures and provide meaningful feedback. This section covers comprehensive error handling strategies and best practices.
Effective error handling for authentication includes several key components that work together to create a robust system:
- Error Detection: Identifying and categorizing different types of errors
- User Feedback: Providing clear, actionable error messages
- Recovery Strategies: Implementing automatic retry and fallback mechanisms
- Logging and Monitoring: Tracking errors for debugging and analysis
Common Authentication Errors
Understanding common authentication errors helps you implement appropriate error handling and recovery mechanisms. This section covers HTTP status codes, authentication-specific errors, and their causes and solutions.
HTTP Status Codes
Nexla uses standard HTTP status codes to indicate authentication results:
200 OK
Successful authentication responses indicate that the request was processed successfully:
- Meaning: Request successful, authentication valid
- Action: Continue with normal operation
- Example: Successful token refresh, successful logout
400 Bad Request
Client-side errors occur when the request format or parameters are invalid:
- Meaning: Invalid request format or parameters
- Common Causes: Malformed JSON, missing required fields, invalid parameter values
- Action: Review request format and parameters
- Example: Invalid email format, missing organization ID
401 Unauthorized
Authentication failures indicate that the provided credentials are invalid or expired:
- Meaning: Authentication failed or credentials invalid
- Common Causes: Expired tokens, invalid credentials, missing authentication headers
- Action: Re-authenticate or refresh tokens
- Example: Expired access token, invalid service key
403 Forbidden
Permission errors occur when credentials are valid but access is denied:
- Meaning: Valid credentials but insufficient permissions
- Common Causes: User lacks required permissions, organization access denied
- Action: Verify permissions or contact administrator
- Example: User cannot access specific organization resources
404 Not Found
Resource not found errors indicate that the requested resource doesn't exist:
- Meaning: Resource not found
- Common Causes: Invalid endpoint, resource doesn't exist
- Action: Verify endpoint URL and resource existence
- Example: Invalid service key ID, non-existent user
429 Too Many Requests
Rate limiting errors occur when too many requests are made in a short time period:
- Meaning: Rate limit exceeded
- Common Causes: Too many requests in short time period
- Action: Implement rate limiting, wait before retrying
- Example: Exceeded API request limits
500 Internal Server Error
Server-side errors indicate problems with the Nexla platform or services:
- Meaning: Server-side error
- Common Causes: Platform issues, temporary service unavailability
- Action: Wait and retry, contact support if persistent
- Example: Authentication service temporarily unavailable
Authentication-Specific Errors
Authentication-specific errors provide detailed information about what went wrong during the authentication process.
Token Expiration
Token expiration is a common authentication issue that occurs when access tokens reach their end of life:
- Error: 401 Unauthorized with token expiration message
- Cause: Access token has expired
- Solution: Refresh token or re-authenticate
Invalid Credentials
Invalid credentials occur when the provided authentication information is incorrect or has been revoked:
- Error: 401 Unauthorized with invalid credentials message
- Cause: Service key or password is incorrect
- Solution: Verify credentials and re-authenticate
Organization Access Denied
Organization access issues occur when users attempt to access resources outside their permitted scope:
- Error: 403 Forbidden with organization access message
- Cause: User lacks access to specified organization
- Solution: Verify organization membership and permissions
Rate Limiting
Rate limiting errors occur when applications exceed the allowed request frequency:
- Error: 429 Too Many Requests
- Cause: Exceeded rate limits
- Solution: Implement client-side rate limiting
Error Response Format
Nexla provides structured error responses that include detailed information for troubleshooting and programmatic handling. This section explains the standard error response format and common error types.
Standard Error Response
Authentication errors typically include detailed information to help with troubleshooting:
{
"error": "unauthorized",
"error_description": "Invalid or expired access token",
"error_code": "AUTH_001",
"timestamp": "2024-01-15T10:30:00Z",
"request_id": "req_1234567890abcdef",
"details": {
"token_expires_at": "2024-01-15T09:30:00Z",
"current_time": "2024-01-15T10:30:00Z"
}
}
Error Response Fields
Each error response includes specific fields that provide structured information for handling and debugging:
error: Machine-readable error typeerror_description: Human-readable error descriptionerror_code: Specific error code for programmatic handlingtimestamp: When the error occurredrequest_id: Unique identifier for tracking the requestdetails: Additional context-specific information
Common Error Types
Understanding the specific types of authentication errors helps you implement targeted error handling and recovery mechanisms. This section covers the most common error scenarios and their specific characteristics.
Authentication Errors
Authentication errors occur when credentials are invalid, tokens are expired, or users lack sufficient permissions.
{
"error": "invalid_credentials",
"error_description": "Service key is invalid or has been revoked",
"error_code": "AUTH_002"
}
{
"error": "token_expired",
"error_description": "Access token has expired",
"error_code": "AUTH_003"
}
{
"error": "insufficient_permissions",
"error_description": "User lacks required permissions for this operation",
"error_code": "AUTH_004"
}
Rate Limiting Errors
Rate limiting errors occur when applications exceed the allowed number of requests within a specified time window.
{
"error": "rate_limit_exceeded",
"error_description": "Too many requests in the specified time period",
"error_code": "RATE_001",
"details": {
"limit": 100,
"window": "1 minute",
"retry_after": "2024-01-15T10:31:00Z"
}
}
Validation Errors
Validation errors occur when request parameters or data formats don't meet the required specifications.
{
"error": "validation_failed",
"error_description": "Request validation failed",
"error_code": "VAL_001",
"details": {
"field": "email",
"message": "Invalid email format",
"value": "invalid-email"
}
}
Error Handling Strategies
Implementing effective error handling strategies ensures your applications can recover from authentication failures and provide a good user experience. This section covers client-side error handling, retry logic, and circuit breaker patterns.
Client-Side Error Handling
Implementing comprehensive client-side error handling ensures your applications can gracefully recover from authentication failures and provide meaningful feedback to users. The following example demonstrates a robust client-side error handling system that categorizes different error types, provides actionable responses, and includes proper logging for debugging.
This implementation covers:
- Error categorization by HTTP status codes and error types
- Actionable responses that tell your application what to do next
- Retry logic for recoverable errors
- Comprehensive logging for debugging and monitoring
- Fallback handling for unexpected error formats
import requests
import logging
from typing import Optional, Dict, Any
from datetime import datetime
class NexlaErrorHandler:
def __init__(self):
self.logger = logging.getLogger(__name__)
def handle_response(self, response: requests.Response) -> Dict[str, Any]:
"""Handle API response and extract error information"""
if response.status_code < 400:
return response.json()
# Handle error responses
try:
error_data = response.json()
except ValueError:
# Fallback for non-JSON error responses
error_data = {
'error': 'unknown_error',
'error_description': response.text or 'Unknown error occurred',
'error_code': f'HTTP_{response.status_code}'
}
# Log error for debugging
self.logger.error(f"API Error: {error_data}")
# Handle specific error types
return self._process_error(error_data, response.status_code)
def _process_error(self, error_data: Dict[str, Any], status_code: int) -> Dict[str, Any]:
"""Process error data and provide actionable information"""
error_type = error_data.get('error', 'unknown_error')
if status_code == 401:
return self._handle_authentication_error(error_data)
elif status_code == 403:
return self._handle_permission_error(error_data)
elif status_code == 429:
return self._handle_rate_limit_error(error_data)
elif status_code == 500:
return self._handle_server_error(error_data)
else:
return self._handle_generic_error(error_data, status_code)
def _handle_authentication_error(self, error_data: Dict[str, Any]) -> Dict[str, Any]:
"""Handle authentication-specific errors"""
error_code = error_data.get('error_code', 'AUTH_UNKNOWN')
if error_code == 'AUTH_003': # Token expired
return {
'action': 'refresh_token',
'message': 'Token has expired. Please refresh your authentication token.',
'retryable': True,
'error_data': error_data
}
elif error_code == 'AUTH_002': # Invalid credentials
return {
'action': 're_authenticate',
'message': 'Invalid credentials. Please verify your service key or credentials.',
'retryable': False,
'error_data': error_data
}
else:
return {
'action': 'contact_support',
'message': 'Authentication error occurred. Please contact support.',
'retryable': False,
'error_data': error_data
}
def _handle_permission_error(self, error_data: Dict[str, Any]) -> Dict[str, Any]:
"""Handle permission-related errors"""
return {
'action': 'verify_permissions',
'message': 'Insufficient permissions for this operation.',
'retryable': False,
'error_data': error_data
}
def _handle_rate_limit_error(self, error_data: Dict[str, Any]) -> Dict[str, Any]:
"""Handle rate limiting errors"""
retry_after = error_data.get('details', {}).get('retry_after')
return {
'action': 'wait_and_retry',
'message': 'Rate limit exceeded. Please wait before making additional requests.',
'retryable': True,
'retry_after': retry_after,
'error_data': error_data
}
def _handle_server_error(self, error_data: Dict[str, Any]) -> Dict[str, Any]:
"""Handle server-side errors"""
return {
'action': 'retry_later',
'message': 'Server error occurred. Please try again later.',
'retryable': True,
'error_data': error_data
}
def _handle_generic_error(self, error_data: Dict[str, Any], status_code: int) -> Dict[str, Any]:
"""Handle generic HTTP errors"""
return {
'action': 'review_request',
'message': f'HTTP {status_code} error occurred. Please review your request.',
'retryable': status_code < 500, # Retry client errors, not server errors
'error_data': error_data
}
Retry Logic
Implementing intelligent retry logic is essential for handling transient authentication failures and network issues. The following example demonstrates a robust retry system that uses exponential backoff, jitter, and intelligent error detection to maximize the chances of successful recovery while preventing overwhelming the server.
This retry implementation includes:
- Exponential backoff to gradually increase delay between retries
- Jitter to prevent thundering herd problems when multiple clients retry simultaneously
- Intelligent error detection to distinguish between retryable and non-retryable errors
- Configurable retry limits to prevent infinite retry loops
- Decorator pattern for easy integration with existing authentication functions
import time
from typing import Callable, Any, Optional
from functools import wraps
class RetryHandler:
def __init__(self, max_retries: int = 3, base_delay: float = 1.0):
self.max_retries = max_retries
self.base_delay = base_delay
def retry_on_error(self, retryable_errors: list = None):
"""Decorator for retrying operations on specific errors"""
if retryable_errors is None:
retryable_errors = [401, 429, 500, 502, 503, 504]
def decorator(func: Callable) -> Callable:
@wraps(func)
def wrapper(*args, **kwargs):
last_exception = None
for attempt in range(self.max_retries + 1):
try:
return func(*args, **kwargs)
except Exception as e:
last_exception = e
# Check if this is a retryable error
if not self._is_retryable_error(e, retryable_errors):
raise e
# Don't retry on the last attempt
if attempt == self.max_retries:
break
# Calculate delay with exponential backoff
delay = self.base_delay * (2 ** attempt)
# Add jitter to prevent thundering herd
jitter = random.uniform(0, 0.1 * delay)
total_delay = delay + jitter
time.sleep(total_delay)
# If we get here, all retries failed
raise last_exception
return wrapper
return decorator
def _is_retryable_error(self, error: Exception, retryable_errors: list) -> bool:
"""Check if an error is retryable"""
# Check HTTP status codes
if hasattr(error, 'response') and hasattr(error.response, 'status_code'):
return error.response.status_code in retryable_errors
# Check for specific error types
error_str = str(error).lower()
retryable_keywords = ['timeout', 'connection', 'temporary', 'unavailable']
return any(keyword in error_str for keyword in retryable_keywords)
# Usage example
retry_handler = RetryHandler(max_retries=3, base_delay=1.0)
@retry_handler.retry_on_error()
def make_authenticated_request(endpoint: str, token: str) -> Dict[str, Any]:
"""Make an authenticated API request with automatic retry"""
headers = {
'Authorization': f'Bearer {token}',
'Accept': 'application/vnd.nexla.api.v1+json'
}
response = requests.get(endpoint, headers=headers)
response.raise_for_status()
return response.json()
Circuit Breaker Pattern
The circuit breaker pattern prevents cascading failures by temporarily stopping requests when a service is experiencing problems. This implementation monitors authentication failures and automatically opens the circuit when the failure threshold is reached, then attempts to close it once the service appears to be recovered.
This circuit breaker implementation provides:
- Failure threshold monitoring to detect when authentication is consistently failing
- Automatic circuit opening to prevent overwhelming failing services
- Recovery timeout to allow services time to recover before testing
- Half-open state to safely test if the service has recovered
- State management to track circuit status and failure counts
- Graceful degradation by failing fast when the circuit is open
from enum import Enum
from datetime import datetime, timedelta
from typing import Optional, Callable, Any
class CircuitState(Enum):
CLOSED = "closed" # Normal operation
OPEN = "open" # Failing, reject requests
HALF_OPEN = "half_open" # Testing if service is recovered
class CircuitBreaker:
def __init__(self, failure_threshold: int = 5, recovery_timeout: int = 60,
expected_exception: type = Exception):
self.failure_threshold = failure_threshold
self.recovery_timeout = recovery_timeout
self.expected_exception = expected_exception
self.state = CircuitState.CLOSED
self.failure_count = 0
self.last_failure_time: Optional[datetime] = None
def call(self, func: Callable, *args, **kwargs) -> Any:
"""Execute function with circuit breaker protection"""
if self.state == CircuitState.OPEN:
if self._should_attempt_reset():
self.state = CircuitState.HALF_OPEN
else:
raise Exception("Circuit breaker is OPEN")
try:
result = func(*args, **kwargs)
self._on_success()
return result
except self.expected_exception as e:
self._on_failure()
raise e
def _should_attempt_reset(self) -> bool:
"""Check if enough time has passed to attempt reset"""
if not self.last_failure_time:
return False
return datetime.now() - self.last_failure_time > timedelta(seconds=self.recovery_timeout)
def _on_success(self):
"""Handle successful operation"""
self.failure_count = 0
self.state = CircuitState.CLOSED
def _on_failure(self):
"""Handle failed operation"""
self.failure_count += 1
self.last_failure_time = datetime.now()
if self.failure_count >= self.failure_threshold:
self.state = CircuitState.OPEN
if self.state == CircuitState.HALF_OPEN:
self.state = CircuitState.OPEN
# Usage example
circuit_breaker = CircuitBreaker(failure_threshold=3, recovery_timeout=30)
def authenticate_with_nexla(service_key: str) -> Dict[str, Any]:
"""Authenticate with Nexla API"""
headers = {
'Authorization': f'Basic {service_key}',
'Accept': 'application/vnd.nexla.api.v1+json'
}
response = requests.post('https://api.nexla.io/token', headers=headers)
response.raise_for_status()
return response.json()
# Use circuit breaker
try:
token_data = circuit_breaker.call(authenticate_with_nexla, "your-service-key")
print("Authentication successful:", token_data)
except Exception as e:
print("Authentication failed:", e)
User Experience
Providing a good user experience during authentication errors is essential for maintaining user confidence and reducing support requests. This section covers user-friendly error messages and automatic error recovery mechanisms.
Error Messages
Providing clear, actionable error messages is crucial for maintaining user confidence and reducing support requests. The following example demonstrates how to transform technical error codes into user-friendly messages that explain what went wrong and guide users toward resolution.
This error message system includes:
- User-friendly titles that clearly identify the problem
- Clear descriptions that explain what happened in non-technical terms
- Actionable guidance that tells users exactly what to do next
- Help links that provide additional resources for resolution
- Fallback handling for unknown error codes
- Structured formatting for consistent UI display
class UserFriendlyErrorHandler:
def __init__(self):
self.error_messages = {
'AUTH_001': {
'title': 'Authentication Failed',
'message': 'Your login credentials are invalid or have expired.',
'action': 'Please check your username and password, then try again.',
'help_link': '/help/authentication'
},
'AUTH_002': {
'title': 'Invalid Service Key',
'message': 'The service key you provided is not valid.',
'action': 'Please verify your service key or contact your administrator.',
'help_link': '/help/service-keys'
},
'AUTH_003': {
'title': 'Session Expired',
'message': 'Your session has expired due to inactivity.',
'action': 'Please log in again to continue.',
'help_link': '/help/sessions'
},
'RATE_001': {
'title': 'Too Many Requests',
'message': 'You have exceeded the allowed number of requests.',
'action': 'Please wait a moment before trying again.',
'help_link': '/help/rate-limits'
}
}
def get_user_friendly_error(self, error_code: str) -> Dict[str, str]:
"""Get user-friendly error information"""
return self.error_messages.get(error_code, {
'title': 'An Error Occurred',
'message': 'Something went wrong while processing your request.',
'action': 'Please try again or contact support if the problem persists.',
'help_link': '/help/support'
})
def format_error_for_ui(self, error_data: Dict[str, Any]) -> Dict[str, str]:
"""Format error data for user interface display"""
error_code = error_data.get('error_code', 'UNKNOWN')
error_info = self.get_user_friendly_error(error_code)
return {
'title': error_info['title'],
'message': error_info['message'],
'action': error_info['action'],
'help_link': error_info['help_link'],
'technical_details': error_data.get('error_description', ''),
'timestamp': error_data.get('timestamp', ''),
'request_id': error_data.get('request_id', '')
}
Error Recovery
Implementing automatic error recovery mechanisms can significantly improve user experience by handling common authentication issues transparently. The following example demonstrates how to automatically attempt recovery from different types of authentication errors, reducing the need for manual intervention.
This error recovery system provides:
- Automatic token refresh when tokens expire
- Re-authentication attempts when credentials are invalid
- Rate limit handling with automatic waiting and retry
- Recovery success tracking to monitor effectiveness
- Graceful fallback when automatic recovery fails
- Logging and monitoring for recovery attempt tracking
class AuthenticationRecovery:
def __init__(self, error_handler: NexlaErrorHandler):
self.error_handler = error_handler
def attempt_recovery(self, error_data: Dict[str, Any]) -> bool:
"""Attempt to recover from authentication errors"""
action = error_data.get('action', '')
if action == 'refresh_token':
return self._refresh_token()
elif action == 're_authenticate':
return self._re_authenticate()
elif action == 'wait_and_retry':
return self._wait_and_retry(error_data)
else:
return False
def _refresh_token(self) -> bool:
"""Attempt to refresh the current token"""
try:
# Implementation depends on your token management
# This is a placeholder for the actual refresh logic
return True
except Exception as e:
logging.error(f"Token refresh failed: {e}")
return False
def _re_authenticate(self) -> bool:
"""Attempt to re-authenticate"""
try:
# Implementation depends on your authentication flow
# This is a placeholder for the actual re-authentication logic
return True
except Exception as e:
logging.error(f"Re-authentication failed: {e}")
return False
def _wait_and_retry(self, error_data: Dict[str, Any]) -> bool:
"""Wait and retry for rate limiting errors"""
retry_after = error_data.get('retry_after')
if retry_after:
try:
retry_time = datetime.fromisoformat(retry_after.replace('Z', '+00:00'))
wait_seconds = (retry_time - datetime.now().replace(tzinfo=retry_time.tzinfo)).total_seconds()
if wait_seconds > 0:
time.sleep(wait_seconds)
return True
except Exception as e:
logging.error(f"Error parsing retry time: {e}")
return False
Logging and Monitoring
Comprehensive logging and monitoring are essential for debugging authentication issues and maintaining system health. This section covers error logging strategies, monitoring approaches, and alerting mechanisms.
Error Logging
Implementing comprehensive error logging is essential for debugging authentication issues and maintaining security audit trails. The following example demonstrates how to log authentication errors with appropriate context, severity levels, and structured data for effective troubleshooting and compliance.
This error logging system provides:
- Structured log entries with consistent JSON formatting for easy parsing
- Contextual information including user, organization, endpoint, and request details
- Severity-based logging to distinguish between critical, security, and warning-level errors
- Security audit trails for compliance and security incident investigation
- Timestamp tracking for chronological error analysis
- Request correlation using request IDs for tracing error patterns
import logging
import json
from datetime import datetime
class AuthenticationLogger:
def __init__(self, logger_name: str = 'nexla.auth'):
self.logger = logging.getLogger(logger_name)
def log_authentication_error(self, error_data: Dict[str, Any],
context: Dict[str, Any] = None):
"""Log authentication errors with context"""
log_entry = {
'timestamp': datetime.now().isoformat(),
'error_type': 'authentication_error',
'error_code': error_data.get('error_code'),
'error_description': error_data.get('error_description'),
'http_status': context.get('status_code') if context else None,
'endpoint': context.get('endpoint') if context else None,
'user_id': context.get('user_id') if context else None,
'organization_id': context.get('organization_id') if context else None,
'request_id': error_data.get('request_id'),
'ip_address': context.get('ip_address') if context else None,
'user_agent': context.get('user_agent') if context else None
}
# Log at appropriate level based on error severity
if self._is_critical_error(error_data):
self.logger.critical(f"Critical authentication error: {json.dumps(log_entry)}")
elif self._is_security_error(error_data):
self.logger.error(f"Security-related authentication error: {json.dumps(log_entry)}")
else:
self.logger.warning(f"Authentication error: {json.dumps(log_entry)}")
def _is_critical_error(self, error_data: Dict[str, Any]) -> bool:
"""Check if error is critical"""
critical_codes = ['AUTH_CRITICAL', 'SYSTEM_FAILURE']
return error_data.get('error_code') in critical_codes
def _is_security_error(self, error_data: Dict[str, Any]) -> bool:
"""Check if error is security-related"""
security_codes = ['AUTH_002', 'AUTH_004', 'SECURITY_VIOLATION']
return error_data.get('error_code') in security_codes
Error Monitoring
Setting up proactive error monitoring helps identify authentication issues before they become critical problems. The following example demonstrates how to track error rates, set thresholds, and generate alerts when authentication problems exceed acceptable levels.
This error monitoring system includes:
- Error rate calculation to track frequency of different error types over time
- Threshold-based alerting to notify when error rates exceed acceptable limits
- Time-based analysis to identify patterns and trends in authentication failures
- Severity classification to prioritize alerts based on error impact
- Historical tracking to maintain error history for trend analysis
- Automated alerting to notify teams when intervention is needed
class AuthenticationMonitor:
def __init__(self):
self.error_counts = {}
self.error_timestamps = {}
def record_error(self, error_code: str):
"""Record an authentication error"""
now = datetime.now()
if error_code not in self.error_counts:
self.error_counts[error_code] = 0
self.error_timestamps[error_code] = []
self.error_counts[error_code] += 1
self.error_timestamps[error_code].append(now)
# Keep only recent timestamps (last hour)
cutoff = now - timedelta(hours=1)
self.error_timestamps[error_code] = [
ts for ts in self.error_timestamps[error_code] if ts > cutoff
]
def get_error_rate(self, error_code: str, minutes: int = 5) -> float:
"""Calculate error rate for a specific error code"""
if error_code not in self.error_timestamps:
return 0.0
cutoff = datetime.now() - timedelta(minutes=minutes)
recent_errors = [
ts for ts in self.error_timestamps[error_code] if ts > cutoff
]
return len(recent_errors) / (minutes / 60) # errors per hour
def check_error_thresholds(self) -> list:
"""Check if any error rates exceed thresholds"""
alerts = []
thresholds = {
'AUTH_002': 10, # 10 invalid credential errors per hour
'AUTH_003': 50, # 50 expired token errors per hour
'RATE_001': 20 # 20 rate limit errors per hour
}
for error_code, threshold in thresholds.items():
rate = self.get_error_rate(error_code, 60) # Check last hour
if rate > threshold:
alerts.append({
'error_code': error_code,
'current_rate': rate,
'threshold': threshold,
'severity': 'high' if rate > threshold * 2 else 'medium'
})
return alerts
Troubleshooting
When authentication errors persist, systematic troubleshooting helps identify root causes and implement effective solutions. This section covers common issues, their solutions, and debugging strategies.
Common Issues and Solutions
When authentication errors persist, understanding the root causes and implementing appropriate solutions is essential. This section covers common authentication issues, their solutions, and prevention strategies.
Token Expiration Issues
Token expiration is one of the most common authentication problems that can cause frequent failures.
- Problem: Frequent 401 errors with token expiration
- Solution: Implement automatic token refresh before expiration
- Prevention: Monitor token expiration times and refresh proactively
Rate Limiting Issues
Rate limiting can affect normal application operation when request patterns exceed platform thresholds. These issues often occur during bulk operations, automated workflows, or when multiple clients share the same rate limit quota.
- Problem: 429 errors during normal operation
- Solution: Implement client-side rate limiting and request batching
- Prevention: Monitor request patterns and optimize API usage
Permission Issues
Permission changes can cause previously working operations to fail unexpectedly.
- Problem: 403 errors for previously working operations
- Solution: Verify user permissions and organization membership
- Prevention: Regular permission audits and access reviews
Network Issues
Network connectivity problems can cause intermittent authentication failures due to packet loss, DNS resolution issues, or temporary service unavailability. These failures are often transient and require resilient handling strategies.
- Problem: Connection timeouts and network errors
- Solution: Implement retry logic with exponential backoff
- Prevention: Monitor network connectivity and use circuit breakers
Debugging Steps
When authentication errors occur, following a systematic debugging approach helps isolate the root cause and implement targeted solutions. These steps are designed to be followed in order, as each step builds upon the information gathered from previous steps:
- Check Error Response: Examine the complete error response for details
- Verify Credentials: Ensure credentials are valid and not expired
- Check Permissions: Verify user has necessary permissions
- Review Logs: Check application and authentication logs
- Test Endpoints: Verify endpoints are accessible and working
- Contact Support: Reach out with specific error details
Next Steps
- Security Best Practices: Follow comprehensive security guidelines
- Rate Limiting: Understand rate limiting and throttling
- Connector Authentication: Handle connector-specific authentication
- Advanced Features: Explore organization context and impersonation
For comprehensive authentication information, return to the Authentication Overview.