Best Practices and Troubleshooting

Performance Optimization

Connection Pool Tuning

yaml

Minimum Size: 5

Maximum Size: 20

Timeout: 30 seconds

Idle Timeout: 10 minutes

Batch Processing

Optimal batch size: 1000-5000 records
Adjust based on record size
Monitor memory usage
Use parallel processing for large datasets

Query Optimization

Select only required fields
Apply filters at source
Use appropriate indexes
Avoid complex joins in virtual mode

Network Optimization

Enable compression
Use persistent connections
Configure appropriate timeouts
Place Gateway Agent close to data source

Error Handling

Common Error Patterns

Error Type	Troubleshooting Steps
Connection Errors	Verify network connectivity Check firewall rules Validate credentials Review SSL certificates
Data Errors	Type mismatches Constraint violations Missing required fields Format inconsistencies
Performance Errors	Query timeouts Memory exhaustion API rate limits Lock contentions

Error Recovery Strategies

Strategy Type	Implementation
Automatic Retry	Exponential backoff Maximum retry limit Error classification
Manual Intervention	Error queue review Data correction Process restart
Fallback Options	Switch to full load Reduce batch size Off-peak scheduling

Security Considerations

Security Considerations	Best Practices
Authentication	Use service accounts Implement key rotation Store credentials securely Monitor access logs
Data Protection	Enable SSL/TLS Encrypt sensitive data Implement field-level security Audit data access
Network Security	Whitelist IP addresses Use VPN for sensitive data Configure firewall rules Regular security reviews
Compliance Requirements	Data residency rules Privacy regulations (GDPR, CCPA) Industry standards (SOX, HIPAA) Internal policies

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