Volume Operations¶

# Example: Volume operations integration
from netapp_mcp_client import NetAppMCPClient
from apim_client import APIMClient
from datetime import datetime, timedelta

class VolumeManager:
    def __init__(self):
        self.apim = APIMClient()
        self.mcp_client = NetAppMCPClient()

    async def create_volume(self, volume_config: dict):
        """Create a new volume with specified configuration"""
        provisioning_request = {
            "workflow": "volume_provisioning",
            "parameters": {
                "svm_id": volume_config["svm_id"],
                "volume_name": volume_config["name"],
                "size": volume_config["size"],
                "aggregate": volume_config.get("aggregate", "auto_select"),
                "security_style": volume_config.get("security_style", "unix"),
                "qos_policy": volume_config.get("qos_policy", "default"),
                "data_protection": volume_config.get("data_protection", True)
            }
        }

        response = await self.apim.execute_temporal_workflow(provisioning_request)
        return response.volume_details

    async def get_volume_performance(self, volume_id: str, timeframe_hours: int = 24):
        """Get comprehensive volume performance metrics"""
        performance_request = {
            "workflow": "volume_performance_analysis",
            "parameters": {
                "volume_id": volume_id,
                "analysis_period": f"{timeframe_hours}_hours",
                "metrics": ["iops", "throughput", "latency", "cache_hits"],
                "include_trends": True,
                "include_predictions": True,
                "workload_analysis": True
            }
        }

        response = await self.apim.execute_temporal_workflow(performance_request)
        return response.performance_data

    async def resize_volume(self, volume_id: str, new_size: str, resize_type: str = "auto"):
        """Resize volume with optional auto-shrink capability"""
        resize_request = {
            "workflow": "volume_resize",
            "parameters": {
                "volume_id": volume_id,
                "new_size": new_size,
                "resize_type": resize_type,  # manual, auto, auto_grow
                "validate_space": True,
                "backup_before_resize": True
            }
        }

        return await self.apim.execute_temporal_workflow(resize_request)

class AutomatedVolumeOperations:
    async def setup_volume_automation(self):
        """Configure automated volume management"""

        # Automated volume resizing
        await self.apim.register_volume_handler({
            "trigger_type": "volume_space_threshold",
            "threshold": "85%_full",
            "action": "auto_volume_resize",
            "resize_increment": "20%",
            "max_size": "1TB",
            "approval_required": False,
            "notification_channels": ["slack", "email"]
        })

        # Automated snapshot management
        await self.apim.register_volume_handler({
            "trigger_type": "snapshot_schedule",
            "schedule": "hourly_daily_weekly",
            "action": "create_snapshots",
            "retention_policy": "7_daily_4_weekly_12_monthly",
            "auto_execute": True,
            "cleanup_old_snapshots": True
        })

        # Automated performance optimization
        await self.apim.register_volume_handler({
            "trigger_type": "performance_degradation",
            "threshold": "latency_increase_30%",
            "action": "volume_performance_optimization",
            "auto_execute": False,
            "approval_required": True,
            "approver_role": "storage_admin"
        })

    async def execute_volume_migration(self, migration_plan):
        """Execute volume migration workflow"""
        migration_workflow = {
            "workflow": "volume_migration",
            "parameters": {
                "source_volume": migration_plan["source_volume_id"],
                "target_aggregate": migration_plan["target_aggregate"],
                "migration_method": migration_plan.get("method", "vol_move"),
                "cutover_window": migration_plan.get("cutover_window", "maintenance"),
                "validation_checks": True,
                "rollback_plan": migration_plan.get("rollback_plan")
            }
        }

        return await self.apim.execute_temporal_workflow(migration_workflow)

class AIVolumeAnalytics:
    async def optimize_volume_performance(self, volume_metrics):
        """AI-driven volume performance optimization"""

        # Analyze current volume performance
        performance_analysis = await self.ai_assistant.analyze_volume_performance(
            volume_metrics=volume_metrics,
            historical_data="30_days",
            include_workload_patterns=True
        )

        # Generate optimization recommendations
        optimizations = await self.ai_assistant.generate_volume_optimizations(
            performance_analysis=performance_analysis,
            application_requirements=await self.get_application_requirements(),
            storage_constraints=await self.get_storage_constraints()
        )

        # Execute approved optimizations
        for optimization in optimizations.approved_recommendations:
            await self.apim.execute_temporal_workflow({
                "workflow": optimization.workflow,
                "parameters": optimization.parameters,
                "ai_confidence": optimization.confidence_score
            })

        return optimizations

    async def predict_volume_capacity_needs(self, volume_metrics):
        """Predict volume capacity requirements"""
        capacity_prediction = await self.ai_assistant.predict_capacity_needs(
            current_metrics=volume_metrics,
            growth_patterns=await self.get_growth_patterns(),
            business_forecasts=await self.get_business_forecasts()
        )

        # Proactive capacity management for high-confidence predictions
        for prediction in capacity_prediction.high_confidence_predictions:
            if prediction.confidence_score > 0.85:
                await self.apim.execute_temporal_workflow({
                    "workflow": "proactive_volume_expansion",
                    "parameters": {
                        "volume_id": prediction.volume_id,
                        "expansion_size": prediction.recommended_size,
                        "timing": prediction.optimal_timing
                    }
                })

        return capacity_prediction

class VolumePerformanceMonitor:
    async def monitor_volume_performance(self, volume_id: str):
        """Monitor comprehensive volume performance metrics"""
        monitoring_request = {
            "workflow": "volume_performance_monitoring",
            "parameters": {
                "volume_id": volume_id,
                "metrics": ["iops", "throughput", "latency", "queue_depth"],
                "sampling_frequency": "1_minute",
                "alert_thresholds": {
                    "latency_warning": "10_ms",
                    "latency_critical": "50_ms",
                    "iops_utilization": "90%",
                    "throughput_utilization": "85%"
                }
            }
        }

        response = await self.apim.execute_temporal_workflow(monitoring_request)
        return response.performance_metrics

    async def analyze_workload_patterns(self, volume_id: str, analysis_period: str = "7_days"):
        """Analyze volume workload patterns for optimization"""
        analysis_request = {
            "workflow": "workload_pattern_analysis",
            "parameters": {
                "volume_id": volume_id,
                "analysis_period": analysis_period,
                "pattern_types": ["io_size", "access_patterns", "temporal_patterns"],
                "correlation_analysis": True,
                "optimization_suggestions": True
            }
        }

        return await self.apim.execute_temporal_workflow(analysis_request)

class VolumeBackupManager:
    async def create_snapshot(self, volume_id: str, snapshot_name: str = None):
        """Create manual snapshot of volume"""
        snapshot_request = {
            "workflow": "create_volume_snapshot",
            "parameters": {
                "volume_id": volume_id,
                "snapshot_name": snapshot_name or f"manual_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
                "validate_consistency": True,
                "update_catalog": True
            }
        }

        return await self.apim.execute_temporal_workflow(snapshot_request)

    async def restore_from_snapshot(self, volume_id: str, snapshot_name: str, restore_type: str = "in_place"):
        """Restore volume from snapshot"""
        restore_request = {
            "workflow": "volume_snapshot_restore",
            "parameters": {
                "volume_id": volume_id,
                "snapshot_name": snapshot_name,
                "restore_type": restore_type,  # in_place, clone, new_volume
                "validation_checks": True,
                "backup_current_state": True
            }
        }

        return await self.apim.execute_temporal_workflow(restore_request)

    async def setup_replication(self, source_volume: str, destination_cluster: str, policy: str = "MirrorAndVault"):
        """Setup SnapMirror replication for volume"""
        replication_request = {
            "workflow": "setup_volume_replication",
            "parameters": {
                "source_volume": source_volume,
                "destination_cluster": destination_cluster,
                "policy": policy,
                "schedule": "hourly",
                "initialize_immediately": True
            }
        }

        return await self.apim.execute_temporal_workflow(replication_request)

class VolumeEfficiencyManager:
    async def optimize_volume_efficiency(self, volume_id: str):
        """Optimize volume storage efficiency"""
        efficiency_request = {
            "workflow": "volume_efficiency_optimization",
            "parameters": {
                "volume_id": volume_id,
                "efficiency_features": ["deduplication", "compression", "compaction"],
                "performance_impact_threshold": "5%_latency_increase",
                "space_savings_target": "20%",
                "schedule_optimization": "low_usage_hours"
            }
        }

        return await self.apim.execute_temporal_workflow(efficiency_request)

    async def analyze_efficiency_opportunities(self, cluster_id: str):
        """Analyze storage efficiency opportunities across volumes"""
        analysis_request = {
            "workflow": "cluster_efficiency_analysis",
            "parameters": {
                "cluster_id": cluster_id,
                "analysis_scope": "all_volumes",
                "efficiency_metrics": ["dedup_ratio", "compression_ratio", "space_savings"],
                "recommendations": True,
                "cost_benefit_analysis": True
            }
        }

        return await self.apim.execute_temporal_workflow(analysis_request)