Operational Guide
Version 1.0
User Manual
Step-by-step operational procedures, configuration guides, troubleshooting resources, and best practices for the Helios Adaptive Intelligence System.
System Requirements
| Requirement | Specification |
|---|---|
| Compute | 64+ CPU cores, 256GB+ RAM recommended |
| Storage | 10TB+ SSD for feature store and audit logs |
| Network | 10Gbps+ for real-time data feeds |
| GPU | NVIDIA A100 or equivalent for ML workloads |
| OS | Linux (Ubuntu 22.04 LTS recommended) |
Operational Phases
1
Assessment
- Data Ingestion
- Quadruple Verification
- Feature Engineering
- UUID Lineage
2
Refinement
- Task Decomposition
- Agent Selection
- Compliance Config
- Microservices Setup
3
Computation
- Multi-Agent Analytics
- Contradiction Mgmt
- Consensus Clustering
- Provenance Logging
4
Synthesis
- Report Dissection
- Strategy Formulation
- Scoring & Ranking
- Dashboard Generation
Quick Reference Commands
Start Task
helios-cli task submit --config task.yamlCheck Status
helios-cli task status --id <task_id>View Agents
helios-cli agents list --activeExport Report
helios-cli report export --id <report_id> --format pdfVerify Audit
helios-cli audit verify --chain-id <chain_id>Key Metrics to Monitor
| Metric | Target | Alert Threshold |
|---|---|---|
| Data Freshness | <5 min | >15 min |
| Agent Latency p95 | <30s | >60s |
| Consensus Confidence | >0.85 | <0.75 |
| Hash Chain Integrity | 100% | <100% |
| Source Independence | ≥2 | <2 |
Troubleshooting Guide
Data Ingestion Failure
Symptoms: Missing data points, stale timestamps
Resolution: Check source connectivity, verify credentials, review rate limits
Agent Timeout
Symptoms: Execution exceeds SLO
Resolution: Reduce task complexity, increase compute resources, review agent configuration
Consensus Failure
Symptoms: Low pooled confidence
Resolution: Review agent outputs, check for contradictions, verify source quality
Hash Chain Break
Symptoms: Verification failure
Resolution: Restore from last valid checkpoint, investigate cause, re-process affected data
Best Practices
Data Quality
- Source Diversification: Maintain at least 4 independent sources for critical data
- Freshness Monitoring: Set alerts for data staleness exceeding thresholds
- Validation Rules: Implement domain-specific validation for all data types
- Anomaly Detection: Enable automated anomaly detection on all feeds
Agent Configuration
- EVSI Tuning: Regularly review and adjust EVSI thresholds based on performance
- Agent Specialization: Avoid overloading agents with too many responsibilities
- Timeout Management: Set appropriate timeouts based on task complexity
- Resource Allocation: Monitor and adjust compute resources per agent
Compliance
- Proactive Monitoring: Don't wait for audits; continuously monitor compliance
- Documentation: Maintain comprehensive documentation of all configurations
- Testing: Regularly test audit trail integrity and recovery procedures
- Training: Ensure all operators are trained on compliance procedures