data/aicl/examples/35_multi_cloud_manager.aicl

# AICL Example: Multi-Cloud Manager
# Implements a multi-cloud management platform with cloud abstraction, intelligent workload
# placement, cost optimization, compliance enforcement, and cross-cloud failover.

# Level 1: Architecture
Goal: Provide a unified multi-cloud management platform that abstracts cloud provider differences, enables intelligent workload placement based on cost, performance, and compliance requirements, optimizes spending across providers, enforces regulatory policies, and orchestrates seamless cross-cloud failover.

Constraint: Workload placement decisions must evaluate at least 3 cloud providers before selection
Constraint: Cost data must be refreshed at least every 15 minutes from all cloud providers
Constraint: Compliance policies must be enforced before workload provisioning
Constraint: Cross-cloud failover must complete within 5 minutes RTO
Constraint: Cloud credential rotation must occur every 90 days automatically

Risk: Cloud provider API rate limiting causing management plane degradation
Recovery: Implement exponential backoff with jitter; batch API calls where possible; maintain local cache of cloud state; queue management operations during rate limit windows; use provider-specific SDK retry logic

Risk: Data residency violation from incorrect workload placement
Recovery: Compliance policy engine validates placement before provisioning; geo-fencing tags enforced at cloud account level; automatic migration if violation detected; audit trail for all placement decisions; immediate alert on violation

Risk: Cost overrun from unoptimized resource allocation across clouds
Recovery: Real-time cost monitoring with budget alerts at 80% and 100%; automatic right-sizing recommendations; spot/preemptible instance utilization for fault-tolerant workloads; reserved instance coverage optimization

Risk: Cross-cloud network latency degrading distributed application performance
Recovery: Cloud interconnect awareness in placement decisions; latency-based routing for distributed components; data locality preferences; dedicated interconnect for high-throughput workloads

Risk: Vendor lock-in from provider-specific service dependencies
Recovery: Enforce abstraction layer usage for all cloud services; prohibit direct API calls outside abstraction; regular portability testing across providers; infrastructure-as-code templates parameterized by provider

Risk: Credential compromise across multiple cloud accounts
Recovery: Zero-trust credential management; per-workload scoped credentials; automated rotation every 90 days; anomaly detection on API call patterns; immediate revocation and rotation on suspected compromise

Layer: CloudAbstraction
    SubLayer: ComputeAdapter
    SubLayer: StorageAdapter
    SubLayer: NetworkAdapter
    SubLayer: DatabaseAdapter
Layer: WorkloadOrchestrator
    SubLayer: PlacementEngine
    SubLayer: MigrationController
    SubLayer: FailoverManager
Layer: CostOptimization
    SubLayer: CostAnalyzer
    SubLayer: RightSizer
    SubLayer: ReservationManager
Layer: ComplianceGovernance
    SubLayer: PolicyEngine
    SubLayer: AuditManager
    SubLayer: DataResidencyEnforcer

Validation: Workload placement must pass all compliance checks before provisioning
Validation: Cross-cloud failover must be tested quarterly with documented results
Validation: Cost alerts must trigger within 5 minutes of threshold breach
Validation: All cloud API calls must go through the abstraction layer
Validation: Credential rotation must complete without service interruption
Validation: Compliance audit trail must be retained for 7 years

# Level 2: Entities
Entity CloudProvider
    providerId: string
    providerName: string
    region: string
    apiEndpoint: string
    credentialRef: string
    costData: dict
    availableServices: list
    complianceCertifications: list
    slaUptime: float
    lastHealthCheck: datetime

Entity Workload
    workloadId: string
    workloadName: string
    workloadType: string
    resourceRequirements: dict
    complianceTags: list
    dataResidency: string
    preferredProvider: string
    currentProvider: string
    currentRegion: string
    status: string
    createdAt: datetime

Entity PlacementDecision
    decisionId: string
    workloadId: string
    selectedProvider: string
    selectedRegion: string
    estimatedCost: float
    estimatedLatency: float
    complianceScore: float
    alternatives: list
    decisionReason: string
    timestamp: datetime

Entity CostProfile
    profileId: string
    providerId: string
    computeCostPerHour: dict
    storageCostPerGB: dict
    networkCostPerGB: dict
    reservedInstancePrices: dict
    spotInstancePrices: dict
    lastUpdated: datetime
    currency: string

Entity CompliancePolicy
    policyId: string
    policyName: string
    policyType: string
    constraints: list
    allowedProviders: list
    allowedRegions: list
    dataClassification: string
    enforcementLevel: string
    createdAt: datetime
    lastEvaluated: datetime

Entity FailoverPlan
    planId: string
    workloadId: string
    primaryProvider: string
    secondaryProvider: string
    rtoSeconds: integer
    rpoSeconds: integer
    replicationType: string
    lastTested: datetime
    lastActivated: datetime
    status: string

# Level 3: Behaviors
Behavior PlaceWorkload
    Input: workload: Workload, preferences: dict, constraints: list
    Output: decision: PlacementDecision, provisioned: boolean
    Action:
        Enumerate compatible cloud providers and regions
        Filter by compliance policy constraints (data residency, certifications)
        Score each option on cost, latency, availability, and compliance
        Apply preference weights from workload configuration
        Select highest-scoring placement option
        Validate against all compliance policies before provisioning
        Provision resources through cloud abstraction layer
        Record placement decision with full reasoning

Behavior OptimizeCost
    Input: accountId: string, timeRange: string, budgetLimit: float
    Output: recommendations: list, estimatedSavings: float, actions: list
    Action:
        Aggregate spending data across all cloud providers
        Identify cost anomalies and trend deviations
        Analyze resource utilization vs. allocation
        Generate right-sizing recommendations for over-provisioned resources
        Evaluate reserved instance coverage and recommend purchases
        Identify spot/preemptible opportunities for fault-tolerant workloads
        Calculate estimated savings for each recommendation
        Prioritize by savings magnitude and implementation risk

Behavior MigrateWorkload
    Input: workloadId: string, targetProvider: string, targetRegion: string, strategy: string
    Output: migrationId: string, status: string, dataTransferredGB: float
    Action:
        Validate target provider meets compliance requirements
        Establish cross-cloud data replication channel
        If live migration, sync state incrementally until delta is small
        Switch DNS/traffic routing to new location
        Verify workload health at target before completing migration
        Clean up resources at source provider
        Update placement decision record
        Emit migration metric with duration and data volume

Behavior ExecuteFailover
    Input: workloadId: string, reason: string, automated: boolean
    Output: failoverId: string, activatedAt: datetime, rtoAchieved: float
    Action:
        Detect or receive notification of primary provider failure
        Validate failover plan exists and is current
        If not automated, request human authorization
        Activate secondary provider resources
        Promote replicated data to primary in secondary region
        Update DNS and load balancer routing to secondary
        Verify application health checks pass at secondary
        Measure and record actual RTO achieved
        Emit failover event metric

Behavior EnforceCompliance
    Input: workloadId: string, operation: string, targetProvider: string
    Output: compliant: boolean, violations: list, remediationSteps: list
    Action:
        Load all applicable compliance policies for the workload
        Evaluate each policy constraint against the proposed operation
        Check data residency requirements against target region
        Verify provider certifications match policy requirements
        If violations found, block operation and return violation details
        Suggest remediation steps for each violation
        Log compliance evaluation result for audit trail
        Emit compliance check metric

Behavior RotateCredentials
    Input: providerId: string, credentialType: string
    Output: success: boolean, newCredentialRef: string, rotatedAt: datetime
    Action:
        Generate new credentials via provider API
        Update credential store with new reference
        Propagate new credentials to affected workloads
        Validate workloads continue operating with new credentials
        Mark old credentials for deprecation
        Schedule old credential cleanup after 24-hour overlap
        Audit log the rotation event
        Emit credential rotation metric

# Level 4: Conditions
Condition: ProviderOutage
    When cloud provider health check fails for 3 consecutive intervals (60s total)
    Then activate failover plan for affected workloads; redirect traffic to secondary provider; alert operations team; begin provider status monitoring at 10-second intervals; emit provider-outage metric

Condition: BudgetThresholdExceeded
    When aggregate cloud spending exceeds 80% of monthly budget
    Then emit budget-warning alert; generate cost optimization recommendations; restrict non-essential workload provisioning; notify finance team; if 100% exceeded, block new provisioning except critical workloads

Condition: ComplianceViolationDetected
    When workload placement or operation violates a compliance policy
    Then block the operation immediately; generate violation report with policy details; alert compliance team; if workload already running in violation, initiate migration to compliant provider; emit compliance-violation metric

Condition: CrossCloudLatencyDegraded
    When inter-cloud latency exceeds 100ms for latency-sensitive workloads
    Then evaluate colocation of dependent components; suggest migration to same provider/region; adjust traffic routing; emit latency-degradation metric; consider dedicated interconnect

Condition: CredentialExpiryApproaching
    When cloud credentials are within 14 days of expiration
    Then trigger automated credential rotation; if rotation fails, emit critical alert; queue manual rotation task; block new workload provisioning with expiring credentials; emit credential-expiry-warning metric

# Level 5: Events
Event: OnWorkloadProvisioned
    On workload successfully provisioned on a cloud provider
    Action: Record placement decision, begin cost tracking, start compliance monitoring, configure health checks, establish replication if failover plan exists, emit provisioning-complete metric

Event: OnFailoverActivated
    On workload failover from primary to secondary provider
    Action: Verify secondary is serving traffic, update DNS records, notify stakeholders, begin investigation of primary failure, update failover plan status, emit failover metric with RTO achieved

Event: OnCostAnomalyDetected
    On spending deviates more than 20% from predicted trend
    Action: Identify anomalous cost source, classify as legitimate or waste, generate optimization recommendation, alert finance team, auto-remediate if confidence is high, emit cost-anomaly metric

Event: OnComplianceAuditComplete
    On periodic compliance audit finishes evaluation
    Action: Generate compliance report, record any violations found, update compliance dashboard, notify responsible teams of required actions, archive audit results for retention, emit audit-complete metric

Event: OnCredentialRotated
    On cloud provider credentials successfully rotated
    Action: Validate workloads using new credentials, deprecate old credentials, update credential inventory, schedule next rotation, audit log the rotation, emit rotation-success metric

# Level 6: Concurrency
Parallel:
    Workload placement evaluation across multiple cloud providers
    Cost data aggregation from all connected cloud accounts
    Compliance policy evaluation during workload provisioning
    Cross-cloud data replication for failover readiness
    Credential rotation across multiple providers

# Level 7: Optimization
Optimize: Workload placement cost
    Priority: Real-time price comparison across providers; spot instance utilization for stateless workloads; reserved instance coverage optimization; region selection based on pricing differentials

Optimize: Cross-cloud failover RTO
    Priority: Pre-provisioned standby resources; continuous data replication; automated DNS failover; health-check-driven traffic switching; regular failover testing and drill automation

Optimize: Resource utilization efficiency
    Priority: Right-sizing based on actual usage patterns; auto-scaling policies per workload; idle resource detection and cleanup; multi-cloud load balancing for cost arbitrage

# Level 8: Learning
Learn: Optimal workload placement strategy
    Goal: Minimize total cost while meeting performance and compliance requirements
    Adapt: placementWeights (cost, latency, availability, compliance scoring weights)
    Based: Historical placement outcomes, actual vs. estimated costs, performance metrics, and compliance audit results

Learn: Cost prediction accuracy
    Goal: Accurately forecast monthly cloud spending across providers
    Adapt: costForecastModel parameters
    Based: Historical spending patterns, seasonality, workload growth trends, and pricing change announcements

Learn: Failover readiness assessment
    Goal: Ensure failover plans will achieve target RTO before an actual outage
    Adapt: failoverPreProvisioningLevel per workload
    Based: Historical failover drill results, replication lag measurements, and actual failover performance data

# Level 9: Security
Security:
    Encrypt: All cloud API communication using TLS with provider-specific certificate validation
    Encrypt: Cross-cloud data replication using AES-256 with per-tenant encryption keys
    Encrypt: Credential storage using HSM-backed key management
    Protect: Cloud credentials via scoped IAM roles with least-privilege access
    Protect: Against unauthorized workload placement via compliance policy enforcement
    Protect: Cross-cloud network traffic via VPN tunnels and private interconnects
    Protect: Audit logs against tampering via write-once storage with cryptographic verification

# Level 10: Native
Native: Python
{
import asyncio
from dataclasses import dataclass, field
from typing import Dict, List, Optional
from datetime import datetime, timedelta

@dataclass
class PlacementScore:
    provider: str
    region: str
    cost_score: float
    latency_score: float
    compliance_score: float
    availability_score: float
    total_score: float
    reasons: List[str] = field(default_factory=list)

class MultiCloudOrchestrator:
    def __init__(self, providers: Dict[str, CloudProviderAdapter]):
        self.providers = providers
        self.cost_analyzer = CostAnalyzer(providers)
        self.compliance_engine = ComplianceEngine()
        self.failover_manager = FailoverManager(providers)
        self.credential_manager = CredentialManager(providers)
        self.metrics = MetricsCollector()

    async def place_workload(
        self,
        workload: Workload,
        preferences: Dict
    ) -> PlacementDecision:
        scores = []
        
        for provider_name, adapter in self.providers.items():
            for region in adapter.get_available_regions():
                score = await self._evaluate_placement(
                    workload, provider_name, region, preferences
                )
                scores.append(score)
        
        scores.sort(key=lambda s: s.total_score, reverse=True)
        
        best = scores[0]
        
        compliance_result = self.compliance_engine.evaluate(
            workload, best.provider, best.region
        )
        
        if not compliance_result.compliant:
            for violation in compliance_result.violations:
                best.reasons.append(f"VIOLATION: {violation}")
            best.total_score = 0.0
        
        decision = PlacementDecision(
            decision_id=generate_id(),
            workload_id=workload.workload_id,
            selected_provider=best.provider,
            selected_region=best.region,
            estimated_cost=await self.cost_analyzer.estimate(
                workload, best.provider, best.region
            ),
            estimated_latency=best.latency_score,
            compliance_score=best.compliance_score,
            alternatives=[(s.provider, s.region, s.total_score) for s in scores[1:4]],
            decision_reason="; ".join(best.reasons),
            timestamp=datetime.utcnow(),
        )
        
        if compliance_result.compliant:
            await self._provision(workload, best.provider, best.region)
            self.metrics.record_placement(decision)
        
        return decision

    async def _evaluate_placement(
        self,
        workload: Workload,
        provider: str,
        region: str,
        preferences: Dict
    ) -> PlacementScore:
        reasons = []
        
        cost = await self.cost_analyzer.estimate(workload, provider, region)
        cost_score = 1.0 / (1.0 + cost / 100.0)
        reasons.append(f"Cost: ${cost:.2f}/hr")
        
        latency = await self.providers[provider].measure_latency(region)
        latency_score = 1.0 / (1.0 + latency / 50.0)
        reasons.append(f"Latency: {latency:.1f}ms")
        
        compliance = self.compliance_engine.score(workload, provider, region)
        reasons.append(f"Compliance: {compliance:.0%}")
        
        availability = self.providers[provider].get_sla_uptime(region)
        reasons.append(f"SLA: {availability:.3%}")
        
        weights = preferences.get("weights", {
            "cost": 0.35, "latency": 0.25,
            "compliance": 0.25, "availability": 0.15
        })
        
        total = (
            weights["cost"] * cost_score +
            weights["latency"] * latency_score +
            weights["compliance"] * compliance +
            weights["availability"] * availability
        )
        
        return PlacementScore(
            provider=provider,
            region=region,
            cost_score=cost_score,
            latency_score=latency_score,
            compliance_score=compliance,
            availability_score=availability,
            total_score=total,
            reasons=reasons,
        )

    async def execute_failover(
        self,
        workload_id: str,
        reason: str,
        automated: bool = False
    ) -> FailoverResult:
        plan = await self.failover_manager.get_plan(workload_id)
        if not plan:
            raise FailoverError(f"No failover plan for {workload_id}")
        
        start = datetime.utcnow()
        
        secondary = self.providers[plan.secondary_provider]
        
        await secondary.activate_standby(workload_id, plan.secondary_region)
        
        await self.failover_manager.promote_replica(
            workload_id, plan.secondary_provider, plan.secondary_region
        )
        
        await self.failover_manager.update_routing(
            workload_id, plan.secondary_provider, plan.secondary_region
        )
        
        healthy = await secondary.verify_health(
            workload_id, plan.secondary_region
        )
        
        rto = (datetime.utcnow() - start).total_seconds()
        
        self.metrics.record_failover(
            workload_id, reason, automated, rto, healthy
        )
        
        return FailoverResult(
            workload_id=workload_id,
            activated_at=start,
            rto_achieved=rto,
            secondary_healthy=healthy,
        )