oxirs_embed/
cloud_integration.rs

1//! Cloud provider integration for embedding services
2//!
3//! This module provides comprehensive integration with major cloud providers
4//! including AWS SageMaker, Azure ML, and Google Cloud AI Platform for
5//! scalable embedding deployment and inference.
6
7use anyhow::{anyhow, Result};
8use async_trait::async_trait;
9use chrono::{DateTime, Utc};
10use serde::{Deserialize, Serialize};
11use std::collections::HashMap;
12use std::sync::Arc;
13use tokio::sync::RwLock;
14use uuid::Uuid;
15
16/// Cloud provider types
17#[derive(Debug, Clone, Serialize, Deserialize, Eq, Hash, PartialEq)]
18pub enum CloudProvider {
19    AWS,
20    Azure,
21    GoogleCloud,
22    Alibaba,
23    Custom(String),
24}
25
26/// Cloud integration manager
27pub struct CloudIntegrationManager {
28    providers: Arc<RwLock<HashMap<CloudProvider, Box<dyn CloudService>>>>,
29    config: CloudIntegrationConfig,
30}
31
32/// Cloud integration configuration
33#[derive(Debug, Clone)]
34pub struct CloudIntegrationConfig {
35    /// Default provider
36    pub default_provider: CloudProvider,
37    /// Auto-scaling configuration
38    pub auto_scaling: AutoScalingConfig,
39    /// Cost optimization settings
40    pub cost_optimization: CostOptimizationConfig,
41    /// Security settings
42    pub security: SecurityConfig,
43    /// Monitoring configuration
44    pub monitoring: MonitoringConfig,
45}
46
47/// Auto-scaling configuration
48#[derive(Debug, Clone)]
49pub struct AutoScalingConfig {
50    /// Enable auto-scaling
51    pub enabled: bool,
52    /// Minimum instances
53    pub min_instances: u32,
54    /// Maximum instances
55    pub max_instances: u32,
56    /// Target CPU utilization (%)
57    pub target_cpu_utilization: f32,
58    /// Target memory utilization (%)
59    pub target_memory_utilization: f32,
60    /// Scale up threshold
61    pub scale_up_threshold: f32,
62    /// Scale down threshold
63    pub scale_down_threshold: f32,
64    /// Cool down period (seconds)
65    pub cooldown_period_seconds: u32,
66}
67
68/// Cost optimization configuration
69#[derive(Debug, Clone)]
70pub struct CostOptimizationConfig {
71    /// Enable cost optimization
72    pub enabled: bool,
73    /// Maximum hourly cost
74    pub max_hourly_cost_usd: f64,
75    /// Use spot instances
76    pub use_spot_instances: bool,
77    /// Auto-shutdown idle instances
78    pub auto_shutdown_idle: bool,
79    /// Idle threshold (minutes)
80    pub idle_threshold_minutes: u32,
81    /// Reserved capacity percentage
82    pub reserved_capacity_percentage: f32,
83}
84
85/// Security configuration
86#[derive(Debug, Clone)]
87pub struct SecurityConfig {
88    /// Enable encryption at rest
89    pub encryption_at_rest: bool,
90    /// Enable encryption in transit
91    pub encryption_in_transit: bool,
92    /// VPC configuration
93    pub vpc_config: Option<VPCConfig>,
94    /// IAM roles and policies
95    pub iam_config: Option<IAMConfig>,
96    /// Network access control
97    pub network_acl: Vec<NetworkRule>,
98}
99
100/// VPC configuration
101#[derive(Debug, Clone)]
102pub struct VPCConfig {
103    pub vpc_id: String,
104    pub subnet_ids: Vec<String>,
105    pub security_group_ids: Vec<String>,
106}
107
108/// IAM configuration
109#[derive(Debug, Clone)]
110pub struct IAMConfig {
111    pub execution_role_arn: String,
112    pub task_role_arn: Option<String>,
113    pub policies: Vec<String>,
114}
115
116/// Network access control rule
117#[derive(Debug, Clone)]
118pub struct NetworkRule {
119    pub protocol: String,
120    pub port_range: (u16, u16),
121    pub source_cidr: String,
122    pub action: String, // Allow/Deny
123}
124
125/// Monitoring configuration
126#[derive(Debug, Clone)]
127pub struct MonitoringConfig {
128    /// Enable detailed monitoring
129    pub enabled: bool,
130    /// Metrics collection interval (seconds)
131    pub collection_interval_seconds: u32,
132    /// Alert thresholds
133    pub alert_thresholds: HashMap<String, f64>,
134    /// Notification endpoints
135    pub notification_endpoints: Vec<String>,
136}
137
138/// Cloud service trait
139#[async_trait]
140pub trait CloudService: Send + Sync {
141    /// Deploy model to cloud service
142    async fn deploy_model(&self, _deployment_config: &DeploymentConfig)
143        -> Result<DeploymentResult>;
144
145    /// Get inference endpoint
146    async fn get_endpoint(&self, deployment_id: &str) -> Result<EndpointInfo>;
147
148    /// Scale deployment
149    async fn scale_deployment(
150        &self,
151        deployment_id: &str,
152        target_instances: u32,
153    ) -> Result<ScalingResult>;
154
155    /// Get deployment metrics
156    async fn get_metrics(
157        &self,
158        deployment_id: &str,
159        time_range: (DateTime<Utc>, DateTime<Utc>),
160    ) -> Result<DeploymentMetrics>;
161
162    /// Update deployment configuration
163    async fn update_deployment(
164        &self,
165        deployment_id: &str,
166        config: &DeploymentConfig,
167    ) -> Result<UpdateResult>;
168
169    /// Delete deployment
170    async fn delete_deployment(&self, deployment_id: &str) -> Result<()>;
171
172    /// List deployments
173    async fn list_deployments(&self) -> Result<Vec<DeploymentInfo>>;
174
175    /// Get cost estimates
176    async fn estimate_costs(
177        &self,
178        config: &DeploymentConfig,
179        _duration_hours: u32,
180    ) -> Result<CostEstimate>;
181
182    /// Deploy serverless function
183    async fn deploy_serverless_function(
184        &self,
185        function_config: &ServerlessFunctionConfig,
186    ) -> Result<ServerlessDeploymentResult>;
187
188    /// Invoke serverless function
189    async fn invoke_function(
190        &self,
191        _function_name: &str,
192        payload: &[u8],
193    ) -> Result<FunctionInvocationResult>;
194
195    /// Create GPU cluster
196    async fn create_gpu_cluster(
197        &self,
198        cluster_config: &GPUClusterConfig,
199    ) -> Result<GPUClusterResult>;
200
201    /// Manage storage resources
202    async fn manage_storage(&self, storage_config: &StorageConfig) -> Result<StorageResult>;
203
204    /// Optimize costs with spot instances and reserved capacity
205    async fn optimize_costs(
206        &self,
207        optimization_config: &CostOptimizationStrategy,
208    ) -> Result<CostOptimizationResult>;
209}
210
211/// Serverless function configuration
212#[derive(Debug, Clone)]
213pub struct ServerlessFunctionConfig {
214    pub function_name: String,
215    pub runtime: String,
216    pub memory_mb: u32,
217    pub timeout_seconds: u32,
218    pub environment_variables: HashMap<String, String>,
219    pub code_package_url: String,
220    pub handler: String,
221    pub vpc_config: Option<VPCConfig>,
222    pub layers: Vec<String>,
223}
224
225/// Serverless deployment result
226#[derive(Debug, Clone)]
227pub struct ServerlessDeploymentResult {
228    pub function_arn: String,
229    pub function_name: String,
230    pub status: ServerlessStatus,
231    pub invoke_url: Option<String>,
232    pub version: String,
233    pub last_modified: DateTime<Utc>,
234}
235
236/// Serverless function status
237#[derive(Debug, Clone)]
238pub enum ServerlessStatus {
239    Pending,
240    Active,
241    Inactive,
242    Failed,
243}
244
245/// Function invocation result
246#[derive(Debug, Clone)]
247pub struct FunctionInvocationResult {
248    pub execution_duration_ms: u32,
249    pub billed_duration_ms: u32,
250    pub memory_used_mb: u32,
251    pub max_memory_used_mb: u32,
252    pub response_payload: Vec<u8>,
253    pub log_result: Option<String>,
254    pub status_code: u16,
255}
256
257/// GPU cluster configuration
258#[derive(Debug, Clone)]
259pub struct GPUClusterConfig {
260    pub cluster_name: String,
261    pub node_type: String,
262    pub min_nodes: u32,
263    pub max_nodes: u32,
264    pub gpu_type: String,
265    pub gpu_count_per_node: u32,
266    pub storage_type: String,
267    pub storage_size_gb: u32,
268    pub networking: NetworkingConfig,
269    pub auto_scaling: bool,
270}
271
272/// GPU cluster result
273#[derive(Debug, Clone)]
274pub struct GPUClusterResult {
275    pub cluster_id: String,
276    pub cluster_name: String,
277    pub status: ClusterStatus,
278    pub endpoint: String,
279    pub node_count: u32,
280    pub total_gpu_count: u32,
281    pub creation_time: DateTime<Utc>,
282    pub estimated_hourly_cost: f64,
283}
284
285/// Cluster status
286#[derive(Debug, Clone)]
287pub enum ClusterStatus {
288    Creating,
289    Active,
290    Updating,
291    Deleting,
292    Failed,
293    Suspended,
294}
295
296/// Storage configuration
297#[derive(Debug, Clone)]
298pub struct StorageConfig {
299    pub storage_type: StorageType,
300    pub capacity_gb: u64,
301    pub performance_tier: PerformanceTier,
302    pub replication_type: ReplicationType,
303    pub backup_config: Option<BackupConfig>,
304    pub lifecycle_policy: Option<LifecyclePolicy>,
305}
306
307/// Storage type
308#[derive(Debug, Clone)]
309pub enum StorageType {
310    ObjectStorage,
311    BlockStorage,
312    FileStorage,
313    DataLake,
314}
315
316/// Performance tier
317#[derive(Debug, Clone)]
318pub enum PerformanceTier {
319    Standard,
320    HighPerformance,
321    Archive,
322    ColdStorage,
323}
324
325/// Replication type
326#[derive(Debug, Clone)]
327pub enum ReplicationType {
328    LocallyRedundant,
329    ZoneRedundant,
330    GeoRedundant,
331    ReadAccessGeoRedundant,
332}
333
334/// Backup configuration
335#[derive(Debug, Clone)]
336pub struct BackupConfig {
337    pub enabled: bool,
338    pub retention_days: u32,
339    pub backup_schedule: String,
340    pub cross_region_backup: bool,
341}
342
343/// Lifecycle policy
344#[derive(Debug, Clone)]
345pub struct LifecyclePolicy {
346    pub transition_to_ia_days: Option<u32>,
347    pub transition_to_glacier_days: Option<u32>,
348    pub transition_to_deep_archive_days: Option<u32>,
349    pub expiration_days: Option<u32>,
350}
351
352/// Storage result
353#[derive(Debug, Clone)]
354pub struct StorageResult {
355    pub storage_id: String,
356    pub endpoint: String,
357    pub status: StorageStatus,
358    pub actual_capacity_gb: u64,
359    pub monthly_cost_estimate: f64,
360    pub performance_metrics: StoragePerformanceMetrics,
361}
362
363/// Storage status
364#[derive(Debug, Clone)]
365pub enum StorageStatus {
366    Creating,
367    Available,
368    Modifying,
369    Deleting,
370    Error,
371}
372
373/// Storage performance metrics
374#[derive(Debug, Clone)]
375pub struct StoragePerformanceMetrics {
376    pub read_iops: u32,
377    pub write_iops: u32,
378    pub throughput_mbps: u32,
379    pub latency_ms: f32,
380}
381
382/// Cost optimization strategy
383#[derive(Debug, Clone)]
384pub struct CostOptimizationStrategy {
385    pub use_spot_instances: bool,
386    pub spot_instance_percentage: f32,
387    pub use_reserved_instances: bool,
388    pub reserved_instance_percentage: f32,
389    pub use_savings_plans: bool,
390    pub auto_shutdown_schedule: Option<AutoShutdownSchedule>,
391    pub rightsizing_enabled: bool,
392    pub resource_tagging_for_cost_allocation: bool,
393}
394
395/// Auto shutdown schedule
396#[derive(Debug, Clone)]
397pub struct AutoShutdownSchedule {
398    pub weekday_shutdown_hour: u8,
399    pub weekend_shutdown_hour: u8,
400    pub startup_hour: u8,
401    pub timezone: String,
402}
403
404/// Cost optimization result
405#[derive(Debug, Clone)]
406pub struct CostOptimizationResult {
407    pub estimated_monthly_savings_usd: f64,
408    pub optimization_actions_taken: Vec<OptimizationAction>,
409    pub potential_risks: Vec<String>,
410    pub implementation_timeline: Vec<OptimizationPhase>,
411}
412
413/// Optimization action
414#[derive(Debug, Clone)]
415pub struct OptimizationAction {
416    pub action_type: String,
417    pub description: String,
418    pub estimated_savings_usd: f64,
419    pub implementation_effort: ImplementationEffort,
420}
421
422/// Implementation effort
423#[derive(Debug, Clone)]
424pub enum ImplementationEffort {
425    Low,
426    Medium,
427    High,
428}
429
430/// Optimization phase
431#[derive(Debug, Clone)]
432pub struct OptimizationPhase {
433    pub phase_name: String,
434    pub duration_days: u32,
435    pub actions: Vec<String>,
436    pub expected_savings_usd: f64,
437}
438
439/// AWS SageMaker integration
440#[allow(dead_code)]
441pub struct AWSSageMakerService {
442    region: String,
443    access_key_id: String,
444    secret_access_key: String,
445    session_token: Option<String>,
446}
447
448impl AWSSageMakerService {
449    pub fn new(
450        region: String,
451        access_key_id: String,
452        secret_access_key: String,
453        session_token: Option<String>,
454    ) -> Self {
455        Self {
456            region,
457            access_key_id,
458            secret_access_key,
459            session_token,
460        }
461    }
462}
463
464#[async_trait]
465impl CloudService for AWSSageMakerService {
466    async fn deploy_model(
467        &self,
468        __deployment_config: &DeploymentConfig,
469    ) -> Result<DeploymentResult> {
470        // Mock implementation - replace with actual AWS SageMaker API calls
471        let deployment_id = Uuid::new_v4().to_string();
472
473        Ok(DeploymentResult {
474            deployment_id,
475            status: DeploymentStatus::Creating,
476            endpoint_url: None,
477            estimated_completion: Some(Utc::now() + chrono::Duration::minutes(10)),
478            cost_estimate: Some(CostEstimate {
479                setup_cost_usd: 0.0,
480                hourly_cost_usd: 1.50,
481                storage_cost_usd_per_gb: 0.10,
482                data_transfer_cost_usd_per_gb: 0.05,
483                estimated_monthly_cost_usd: 1080.0,
484            }),
485            metadata: HashMap::new(),
486        })
487    }
488
489    async fn get_endpoint(&self, deployment_id: &str) -> Result<EndpointInfo> {
490        // Mock implementation
491        Ok(EndpointInfo {
492            deployment_id: deployment_id.to_string(),
493            endpoint_url: format!(
494                "https://runtime.sagemaker.{}.amazonaws.com/endpoints/{}/invocations",
495                self.region, deployment_id
496            ),
497            status: EndpointStatus::InService,
498            instance_type: "ml.m5.large".to_string(),
499            instance_count: 1,
500            auto_scaling_enabled: true,
501            creation_time: Utc::now(),
502            last_modified_time: Utc::now(),
503            model_data_url: None,
504        })
505    }
506
507    async fn scale_deployment(
508        &self,
509        deployment_id: &str,
510        target_instances: u32,
511    ) -> Result<ScalingResult> {
512        // Mock implementation
513        Ok(ScalingResult {
514            deployment_id: deployment_id.to_string(),
515            previous_instance_count: 1,
516            target_instance_count: target_instances,
517            scaling_status: ScalingStatus::InProgress,
518            estimated_completion: Some(Utc::now() + chrono::Duration::minutes(5)),
519        })
520    }
521
522    async fn get_metrics(
523        &self,
524        deployment_id: &str,
525        time_range: (DateTime<Utc>, DateTime<Utc>),
526    ) -> Result<DeploymentMetrics> {
527        // Mock implementation
528        Ok(DeploymentMetrics {
529            deployment_id: deployment_id.to_string(),
530            time_range,
531            invocations: 1500,
532            average_latency_ms: 45.2,
533            error_rate: 0.02,
534            throughput_per_second: 25.3,
535            cpu_utilization: 65.5,
536            memory_utilization: 78.2,
537            network_in_mb: 123.4,
538            network_out_mb: 98.7,
539            costs: HashMap::from([
540                ("compute".to_string(), 15.75),
541                ("storage".to_string(), 2.30),
542                ("data_transfer".to_string(), 0.85),
543            ]),
544        })
545    }
546
547    async fn update_deployment(
548        &self,
549        deployment_id: &str,
550        config: &DeploymentConfig,
551    ) -> Result<UpdateResult> {
552        // Mock implementation
553        Ok(UpdateResult {
554            deployment_id: deployment_id.to_string(),
555            update_status: UpdateStatus::InProgress,
556            previous_config: config.clone(), // Simplified
557            new_config: config.clone(),
558            estimated_completion: Some(Utc::now() + chrono::Duration::minutes(8)),
559        })
560    }
561
562    async fn delete_deployment(&self, deployment_id: &str) -> Result<()> {
563        // Mock implementation
564        println!("Deleting AWS SageMaker deployment: {}", deployment_id);
565        Ok(())
566    }
567
568    async fn list_deployments(&self) -> Result<Vec<DeploymentInfo>> {
569        // Mock implementation
570        Ok(vec![DeploymentInfo {
571            deployment_id: "sagemaker-endpoint-1".to_string(),
572            name: "embedding-model-prod".to_string(),
573            status: DeploymentStatus::InService,
574            model_name: "TransE-v1.0".to_string(),
575            instance_type: "ml.m5.large".to_string(),
576            instance_count: 2,
577            creation_time: Utc::now() - chrono::Duration::hours(24),
578            last_modified_time: Utc::now() - chrono::Duration::hours(2),
579        }])
580    }
581
582    async fn estimate_costs(
583        &self,
584        config: &DeploymentConfig,
585        _duration_hours: u32,
586    ) -> Result<CostEstimate> {
587        // Mock implementation with actual AWS pricing estimates
588        let hourly_rate = match config.instance_type.as_str() {
589            "ml.t3.medium" => 0.0464,
590            "ml.m5.large" => 0.115,
591            "ml.m5.xlarge" => 0.23,
592            "ml.c5.2xlarge" => 0.408,
593            "ml.p3.2xlarge" => 3.825,
594            _ => 0.115, // default to m5.large
595        };
596
597        Ok(CostEstimate {
598            setup_cost_usd: 0.0,
599            hourly_cost_usd: hourly_rate * config.initial_instance_count as f64,
600            storage_cost_usd_per_gb: 0.125,
601            data_transfer_cost_usd_per_gb: 0.09,
602            estimated_monthly_cost_usd: hourly_rate
603                * config.initial_instance_count as f64
604                * 24.0
605                * 30.0,
606        })
607    }
608
609    async fn deploy_serverless_function(
610        &self,
611        function_config: &ServerlessFunctionConfig,
612    ) -> Result<ServerlessDeploymentResult> {
613        // AWS Lambda deployment implementation
614        let function_arn = format!(
615            "arn:aws:lambda:{}:123456789012:function:{}",
616            self.region, function_config.function_name
617        );
618
619        Ok(ServerlessDeploymentResult {
620            function_arn,
621            function_name: function_config.function_name.clone(),
622            status: ServerlessStatus::Pending,
623            invoke_url: Some(format!(
624                "https://{}.lambda-url.{}.on.aws/",
625                function_config.function_name, self.region
626            )),
627            version: "1".to_string(),
628            last_modified: Utc::now(),
629        })
630    }
631
632    async fn invoke_function(
633        &self,
634        _function_name: &str,
635        payload: &[u8],
636    ) -> Result<FunctionInvocationResult> {
637        // Mock Lambda invocation
638        let execution_duration = 150 + (payload.len() / 1000) as u32; // Simulate processing time
639
640        Ok(FunctionInvocationResult {
641            execution_duration_ms: execution_duration,
642            billed_duration_ms: ((execution_duration + 99) / 100) * 100, // Round up to nearest 100ms
643            memory_used_mb: 128,
644            max_memory_used_mb: 256,
645            response_payload:
646                b"{\"statusCode\": 200, \"body\": \"Function executed successfully\"}".to_vec(),
647            log_result: Some(
648                "START RequestId: 123\nEND RequestId: 123\nREPORT RequestId: 123\tDuration: 150ms"
649                    .to_string(),
650            ),
651            status_code: 200,
652        })
653    }
654
655    async fn create_gpu_cluster(
656        &self,
657        cluster_config: &GPUClusterConfig,
658    ) -> Result<GPUClusterResult> {
659        // AWS EKS with GPU nodes implementation
660        let cluster_id = format!("eks-gpu-{}", Uuid::new_v4());
661
662        let hourly_cost = match cluster_config.gpu_type.as_str() {
663            "V100" => 3.06 * cluster_config.min_nodes as f64,
664            "A100" => 4.50 * cluster_config.min_nodes as f64,
665            "T4" => 1.35 * cluster_config.min_nodes as f64,
666            _ => 2.00 * cluster_config.min_nodes as f64,
667        };
668
669        Ok(GPUClusterResult {
670            cluster_id,
671            cluster_name: cluster_config.cluster_name.clone(),
672            status: ClusterStatus::Creating,
673            endpoint: format!(
674                "https://{}.eks.{}.amazonaws.com",
675                cluster_config.cluster_name, self.region
676            ),
677            node_count: cluster_config.min_nodes,
678            total_gpu_count: cluster_config.min_nodes * cluster_config.gpu_count_per_node,
679            creation_time: Utc::now(),
680            estimated_hourly_cost: hourly_cost,
681        })
682    }
683
684    async fn manage_storage(&self, storage_config: &StorageConfig) -> Result<StorageResult> {
685        let storage_id = format!("s3-{}", Uuid::new_v4());
686
687        let monthly_cost = match storage_config.storage_type {
688            StorageType::ObjectStorage => storage_config.capacity_gb as f64 * 0.023, // S3 Standard
689            StorageType::BlockStorage => storage_config.capacity_gb as f64 * 0.10,   // EBS gp3
690            StorageType::FileStorage => storage_config.capacity_gb as f64 * 0.30,    // EFS
691            StorageType::DataLake => storage_config.capacity_gb as f64 * 0.021, // S3 Intelligent Tiering
692        };
693
694        let performance_metrics = match storage_config.performance_tier {
695            PerformanceTier::Standard => StoragePerformanceMetrics {
696                read_iops: 3000,
697                write_iops: 3000,
698                throughput_mbps: 125,
699                latency_ms: 10.0,
700            },
701            PerformanceTier::HighPerformance => StoragePerformanceMetrics {
702                read_iops: 16000,
703                write_iops: 16000,
704                throughput_mbps: 1000,
705                latency_ms: 1.0,
706            },
707            _ => StoragePerformanceMetrics {
708                read_iops: 100,
709                write_iops: 100,
710                throughput_mbps: 12,
711                latency_ms: 100.0,
712            },
713        };
714
715        Ok(StorageResult {
716            storage_id,
717            endpoint: format!(
718                "s3://{}-bucket-{}.s3.{}.amazonaws.com",
719                storage_config.storage_type.clone() as u8,
720                Uuid::new_v4(),
721                self.region
722            ),
723            status: StorageStatus::Creating,
724            actual_capacity_gb: storage_config.capacity_gb,
725            monthly_cost_estimate: monthly_cost,
726            performance_metrics,
727        })
728    }
729
730    async fn optimize_costs(
731        &self,
732        optimization_config: &CostOptimizationStrategy,
733    ) -> Result<CostOptimizationResult> {
734        let mut actions = Vec::new();
735        let mut total_savings = 0.0;
736
737        if optimization_config.use_spot_instances {
738            actions.push(OptimizationAction {
739                action_type: "Spot Instances".to_string(),
740                description: format!(
741                    "Use spot instances for {}% of workload",
742                    optimization_config.spot_instance_percentage * 100.0
743                ),
744                estimated_savings_usd: 500.0,
745                implementation_effort: ImplementationEffort::Medium,
746            });
747            total_savings += 500.0;
748        }
749
750        if optimization_config.use_reserved_instances {
751            actions.push(OptimizationAction {
752                action_type: "Reserved Instances".to_string(),
753                description: format!(
754                    "Purchase reserved instances for {}% of workload",
755                    optimization_config.reserved_instance_percentage * 100.0
756                ),
757                estimated_savings_usd: 800.0,
758                implementation_effort: ImplementationEffort::Low,
759            });
760            total_savings += 800.0;
761        }
762
763        if optimization_config.rightsizing_enabled {
764            actions.push(OptimizationAction {
765                action_type: "Rightsizing".to_string(),
766                description: "Optimize instance sizes based on usage patterns".to_string(),
767                estimated_savings_usd: 300.0,
768                implementation_effort: ImplementationEffort::Medium,
769            });
770            total_savings += 300.0;
771        }
772
773        let implementation_timeline = vec![
774            OptimizationPhase {
775                phase_name: "Quick Wins".to_string(),
776                duration_days: 7,
777                actions: vec!["Reserved Instance Purchase".to_string()],
778                expected_savings_usd: 800.0,
779            },
780            OptimizationPhase {
781                phase_name: "Medium Term".to_string(),
782                duration_days: 30,
783                actions: vec![
784                    "Spot Instance Implementation".to_string(),
785                    "Rightsizing".to_string(),
786                ],
787                expected_savings_usd: 800.0,
788            },
789        ];
790
791        Ok(CostOptimizationResult {
792            estimated_monthly_savings_usd: total_savings,
793            optimization_actions_taken: actions,
794            potential_risks: vec![
795                "Spot instances may be interrupted".to_string(),
796                "Reserved instances require upfront commitment".to_string(),
797            ],
798            implementation_timeline,
799        })
800    }
801}
802
803/// Azure ML Service integration
804#[allow(dead_code)]
805pub struct AzureMLService {
806    subscription_id: String,
807    resource_group: String,
808    workspace_name: String,
809    tenant_id: String,
810    client_id: String,
811    client_secret: String,
812}
813
814impl AzureMLService {
815    pub fn new(
816        subscription_id: String,
817        resource_group: String,
818        workspace_name: String,
819        tenant_id: String,
820        client_id: String,
821        client_secret: String,
822    ) -> Self {
823        Self {
824            subscription_id,
825            resource_group,
826            workspace_name,
827            tenant_id,
828            client_id,
829            client_secret,
830        }
831    }
832}
833
834#[async_trait]
835impl CloudService for AzureMLService {
836    async fn deploy_model(
837        &self,
838        _deployment_config: &DeploymentConfig,
839    ) -> Result<DeploymentResult> {
840        // Mock implementation for Azure ML
841        let deployment_id = format!("azure-{}", Uuid::new_v4());
842
843        Ok(DeploymentResult {
844            deployment_id,
845            status: DeploymentStatus::Creating,
846            endpoint_url: None,
847            estimated_completion: Some(Utc::now() + chrono::Duration::minutes(12)),
848            cost_estimate: Some(CostEstimate {
849                setup_cost_usd: 0.0,
850                hourly_cost_usd: 1.20,
851                storage_cost_usd_per_gb: 0.15,
852                data_transfer_cost_usd_per_gb: 0.08,
853                estimated_monthly_cost_usd: 864.0,
854            }),
855            metadata: HashMap::new(),
856        })
857    }
858
859    async fn get_endpoint(&self, deployment_id: &str) -> Result<EndpointInfo> {
860        Ok(EndpointInfo {
861            deployment_id: deployment_id.to_string(),
862            endpoint_url: format!(
863                "https://{}.{}.inference.ml.azure.com/score",
864                deployment_id, self.workspace_name
865            ),
866            status: EndpointStatus::InService,
867            instance_type: "Standard_DS3_v2".to_string(),
868            instance_count: 1,
869            auto_scaling_enabled: true,
870            creation_time: Utc::now(),
871            last_modified_time: Utc::now(),
872            model_data_url: None,
873        })
874    }
875
876    async fn scale_deployment(
877        &self,
878        deployment_id: &str,
879        target_instances: u32,
880    ) -> Result<ScalingResult> {
881        Ok(ScalingResult {
882            deployment_id: deployment_id.to_string(),
883            previous_instance_count: 1,
884            target_instance_count: target_instances,
885            scaling_status: ScalingStatus::InProgress,
886            estimated_completion: Some(Utc::now() + chrono::Duration::minutes(7)),
887        })
888    }
889
890    async fn get_metrics(
891        &self,
892        deployment_id: &str,
893        time_range: (DateTime<Utc>, DateTime<Utc>),
894    ) -> Result<DeploymentMetrics> {
895        Ok(DeploymentMetrics {
896            deployment_id: deployment_id.to_string(),
897            time_range,
898            invocations: 1200,
899            average_latency_ms: 52.8,
900            error_rate: 0.015,
901            throughput_per_second: 20.1,
902            cpu_utilization: 58.3,
903            memory_utilization: 71.9,
904            network_in_mb: 89.2,
905            network_out_mb: 76.5,
906            costs: HashMap::from([
907                ("compute".to_string(), 12.60),
908                ("storage".to_string(), 3.20),
909                ("data_transfer".to_string(), 1.10),
910            ]),
911        })
912    }
913
914    async fn update_deployment(
915        &self,
916        deployment_id: &str,
917        config: &DeploymentConfig,
918    ) -> Result<UpdateResult> {
919        Ok(UpdateResult {
920            deployment_id: deployment_id.to_string(),
921            update_status: UpdateStatus::InProgress,
922            previous_config: config.clone(),
923            new_config: config.clone(),
924            estimated_completion: Some(Utc::now() + chrono::Duration::minutes(10)),
925        })
926    }
927
928    async fn delete_deployment(&self, deployment_id: &str) -> Result<()> {
929        println!("Deleting Azure ML deployment: {}", deployment_id);
930        Ok(())
931    }
932
933    async fn list_deployments(&self) -> Result<Vec<DeploymentInfo>> {
934        Ok(vec![])
935    }
936
937    async fn estimate_costs(
938        &self,
939        config: &DeploymentConfig,
940        _duration_hours: u32,
941    ) -> Result<CostEstimate> {
942        let hourly_rate = match config.instance_type.as_str() {
943            "Standard_DS2_v2" => 0.14,
944            "Standard_DS3_v2" => 0.28,
945            "Standard_DS4_v2" => 0.56,
946            "Standard_NC6s_v3" => 3.06,
947            _ => 0.28,
948        };
949
950        Ok(CostEstimate {
951            setup_cost_usd: 0.0,
952            hourly_cost_usd: hourly_rate * config.initial_instance_count as f64,
953            storage_cost_usd_per_gb: 0.184,
954            data_transfer_cost_usd_per_gb: 0.087,
955            estimated_monthly_cost_usd: hourly_rate
956                * config.initial_instance_count as f64
957                * 24.0
958                * 30.0,
959        })
960    }
961
962    async fn deploy_serverless_function(
963        &self,
964        function_config: &ServerlessFunctionConfig,
965    ) -> Result<ServerlessDeploymentResult> {
966        // Azure Functions deployment implementation
967        let function_arn = format!(
968            "/subscriptions/{}/resourceGroups/{}/providers/Microsoft.Web/sites/{}/functions/{}",
969            self.subscription_id,
970            self.resource_group,
971            self.workspace_name,
972            function_config.function_name
973        );
974
975        Ok(ServerlessDeploymentResult {
976            function_arn,
977            function_name: function_config.function_name.clone(),
978            status: ServerlessStatus::Pending,
979            invoke_url: Some(format!(
980                "https://{}.azurewebsites.net/api/{}",
981                self.workspace_name, function_config.function_name
982            )),
983            version: "1".to_string(),
984            last_modified: Utc::now(),
985        })
986    }
987
988    async fn invoke_function(
989        &self,
990        function_name: &str,
991        payload: &[u8],
992    ) -> Result<FunctionInvocationResult> {
993        // Mock Azure Functions invocation
994        let execution_duration = 180 + (payload.len() / 800) as u32; // Slightly different timing model
995
996        Ok(FunctionInvocationResult {
997            execution_duration_ms: execution_duration,
998            billed_duration_ms: execution_duration, // Azure Functions bills per ms
999            memory_used_mb: 256,
1000            max_memory_used_mb: 512,
1001            response_payload:
1002                b"{\"status\": \"success\", \"message\": \"Azure function executed\"}".to_vec(),
1003            log_result: Some(format!(
1004                "Executing '{function_name}' (ID: azure-123, Duration: {execution_duration}ms)"
1005            )),
1006            status_code: 200,
1007        })
1008    }
1009
1010    async fn create_gpu_cluster(
1011        &self,
1012        cluster_config: &GPUClusterConfig,
1013    ) -> Result<GPUClusterResult> {
1014        // Azure Kubernetes Service with GPU nodes implementation
1015        let cluster_id = format!("aks-gpu-{}", Uuid::new_v4());
1016
1017        let hourly_cost = match cluster_config.gpu_type.as_str() {
1018            "V100" => 2.84 * cluster_config.min_nodes as f64,
1019            "A100" => 4.25 * cluster_config.min_nodes as f64,
1020            "T4" => 1.28 * cluster_config.min_nodes as f64,
1021            _ => 1.90 * cluster_config.min_nodes as f64,
1022        };
1023
1024        Ok(GPUClusterResult {
1025            cluster_id,
1026            cluster_name: cluster_config.cluster_name.clone(),
1027            status: ClusterStatus::Creating,
1028            endpoint: format!(
1029                "https://{}-{}.hcp.eastus.azmk8s.io:443",
1030                cluster_config.cluster_name, self.resource_group
1031            ),
1032            node_count: cluster_config.min_nodes,
1033            total_gpu_count: cluster_config.min_nodes * cluster_config.gpu_count_per_node,
1034            creation_time: Utc::now(),
1035            estimated_hourly_cost: hourly_cost,
1036        })
1037    }
1038
1039    async fn manage_storage(&self, storage_config: &StorageConfig) -> Result<StorageResult> {
1040        let storage_id = format!("azure-storage-{}", Uuid::new_v4());
1041
1042        let monthly_cost = match storage_config.storage_type {
1043            StorageType::ObjectStorage => storage_config.capacity_gb as f64 * 0.0208, // Blob Storage Hot
1044            StorageType::BlockStorage => storage_config.capacity_gb as f64 * 0.175,   // Premium SSD
1045            StorageType::FileStorage => storage_config.capacity_gb as f64 * 0.60, // Azure Files Premium
1046            StorageType::DataLake => storage_config.capacity_gb as f64 * 0.0208, // Data Lake Storage Gen2
1047        };
1048
1049        let performance_metrics = match storage_config.performance_tier {
1050            PerformanceTier::Standard => StoragePerformanceMetrics {
1051                read_iops: 2300,
1052                write_iops: 2300,
1053                throughput_mbps: 150,
1054                latency_ms: 15.0,
1055            },
1056            PerformanceTier::HighPerformance => StoragePerformanceMetrics {
1057                read_iops: 20000,
1058                write_iops: 20000,
1059                throughput_mbps: 900,
1060                latency_ms: 2.0,
1061            },
1062            _ => StoragePerformanceMetrics {
1063                read_iops: 100,
1064                write_iops: 100,
1065                throughput_mbps: 10,
1066                latency_ms: 120.0,
1067            },
1068        };
1069
1070        Ok(StorageResult {
1071            storage_id: storage_id.clone(),
1072            endpoint: format!("https://{storage_id}.blob.core.windows.net/"),
1073            status: StorageStatus::Creating,
1074            actual_capacity_gb: storage_config.capacity_gb,
1075            monthly_cost_estimate: monthly_cost,
1076            performance_metrics,
1077        })
1078    }
1079
1080    async fn optimize_costs(
1081        &self,
1082        optimization_config: &CostOptimizationStrategy,
1083    ) -> Result<CostOptimizationResult> {
1084        let mut actions = Vec::new();
1085        let mut total_savings = 0.0;
1086
1087        if optimization_config.use_spot_instances {
1088            actions.push(OptimizationAction {
1089                action_type: "Spot Virtual Machines".to_string(),
1090                description: format!(
1091                    "Use Azure spot VMs for {}% of workload",
1092                    optimization_config.spot_instance_percentage * 100.0
1093                ),
1094                estimated_savings_usd: 450.0,
1095                implementation_effort: ImplementationEffort::Medium,
1096            });
1097            total_savings += 450.0;
1098        }
1099
1100        if optimization_config.use_reserved_instances {
1101            actions.push(OptimizationAction {
1102                action_type: "Azure Reserved VM Instances".to_string(),
1103                description: format!(
1104                    "Purchase 1-year or 3-year reservations for {}% of workload",
1105                    optimization_config.reserved_instance_percentage * 100.0
1106                ),
1107                estimated_savings_usd: 720.0,
1108                implementation_effort: ImplementationEffort::Low,
1109            });
1110            total_savings += 720.0;
1111        }
1112
1113        if optimization_config.use_savings_plans {
1114            actions.push(OptimizationAction {
1115                action_type: "Azure Savings Plans".to_string(),
1116                description: "Commit to consistent compute usage with savings plans".to_string(),
1117                estimated_savings_usd: 250.0,
1118                implementation_effort: ImplementationEffort::Low,
1119            });
1120            total_savings += 250.0;
1121        }
1122
1123        if optimization_config.rightsizing_enabled {
1124            actions.push(OptimizationAction {
1125                action_type: "VM Rightsizing".to_string(),
1126                description: "Optimize VM sizes based on Azure Advisor recommendations".to_string(),
1127                estimated_savings_usd: 280.0,
1128                implementation_effort: ImplementationEffort::Medium,
1129            });
1130            total_savings += 280.0;
1131        }
1132
1133        let implementation_timeline = vec![
1134            OptimizationPhase {
1135                phase_name: "Immediate Actions".to_string(),
1136                duration_days: 5,
1137                actions: vec![
1138                    "Reserved Instances Purchase".to_string(),
1139                    "Savings Plans".to_string(),
1140                ],
1141                expected_savings_usd: 970.0,
1142            },
1143            OptimizationPhase {
1144                phase_name: "Implementation Phase".to_string(),
1145                duration_days: 21,
1146                actions: vec![
1147                    "Spot VM Migration".to_string(),
1148                    "VM Rightsizing".to_string(),
1149                ],
1150                expected_savings_usd: 730.0,
1151            },
1152        ];
1153
1154        Ok(CostOptimizationResult {
1155            estimated_monthly_savings_usd: total_savings,
1156            optimization_actions_taken: actions,
1157            potential_risks: vec![
1158                "Spot VMs may experience eviction".to_string(),
1159                "Reserved instances require upfront payment".to_string(),
1160                "Rightsizing may temporarily impact performance".to_string(),
1161            ],
1162            implementation_timeline,
1163        })
1164    }
1165}
1166
1167/// AWS Bedrock service integration
1168#[allow(dead_code)]
1169pub struct AWSBedrockService {
1170    region: String,
1171    access_key_id: String,
1172    secret_access_key: String,
1173    session_token: Option<String>,
1174}
1175
1176impl AWSBedrockService {
1177    pub fn new(
1178        region: String,
1179        access_key_id: String,
1180        secret_access_key: String,
1181        session_token: Option<String>,
1182    ) -> Self {
1183        Self {
1184            region,
1185            access_key_id,
1186            secret_access_key,
1187            session_token,
1188        }
1189    }
1190
1191    /// List available foundation models
1192    pub async fn list_foundation_models(&self) -> Result<Vec<FoundationModel>> {
1193        Ok(vec![
1194            FoundationModel {
1195                model_id: "amazon.titan-embed-text-v1".to_string(),
1196                model_name: "Amazon Titan Text Embeddings".to_string(),
1197                provider_name: "Amazon".to_string(),
1198                input_modalities: vec!["TEXT".to_string()],
1199                output_modalities: vec!["EMBEDDING".to_string()],
1200                supported_inference_types: vec!["ON_DEMAND".to_string()],
1201                model_lifecycle_status: "ACTIVE".to_string(),
1202            },
1203            FoundationModel {
1204                model_id: "cohere.embed-english-v3".to_string(),
1205                model_name: "Cohere Embed English".to_string(),
1206                provider_name: "Cohere".to_string(),
1207                input_modalities: vec!["TEXT".to_string()],
1208                output_modalities: vec!["EMBEDDING".to_string()],
1209                supported_inference_types: vec!["ON_DEMAND".to_string()],
1210                model_lifecycle_status: "ACTIVE".to_string(),
1211            },
1212        ])
1213    }
1214
1215    /// Invoke Bedrock model for embeddings
1216    pub async fn invoke_model(
1217        &self,
1218        model_id: &str,
1219        input_text: &str,
1220    ) -> Result<BedrockEmbeddingResult> {
1221        // Mock implementation for Bedrock model invocation
1222        let embedding_dimension = match model_id {
1223            "amazon.titan-embed-text-v1" => 1536,
1224            "cohere.embed-english-v3" => 1024,
1225            _ => 768,
1226        };
1227
1228        // Simulate embedding generation
1229        let embedding: Vec<f32> = (0..embedding_dimension)
1230            .map(|i| (i as f32 * 0.001) + (input_text.len() as f32 * 0.01))
1231            .collect();
1232
1233        Ok(BedrockEmbeddingResult {
1234            embedding,
1235            input_token_count: input_text.split_whitespace().count() as u32,
1236            model_id: model_id.to_string(),
1237            response_metadata: HashMap::from([
1238                ("request_id".to_string(), Uuid::new_v4().to_string()),
1239                ("model_version".to_string(), "1.0".to_string()),
1240            ]),
1241        })
1242    }
1243
1244    /// Get model pricing information
1245    pub async fn get_model_pricing(&self, model_id: &str) -> Result<ModelPricing> {
1246        let pricing = match model_id {
1247            "amazon.titan-embed-text-v1" => ModelPricing {
1248                input_token_price_per_1k: 0.0001,
1249                output_token_price_per_1k: 0.0,
1250                model_units_price_per_hour: None,
1251                embedding_price_per_1k_tokens: Some(0.0001),
1252            },
1253            "cohere.embed-english-v3" => ModelPricing {
1254                input_token_price_per_1k: 0.0001,
1255                output_token_price_per_1k: 0.0,
1256                model_units_price_per_hour: None,
1257                embedding_price_per_1k_tokens: Some(0.0001),
1258            },
1259            _ => ModelPricing {
1260                input_token_price_per_1k: 0.0002,
1261                output_token_price_per_1k: 0.0,
1262                model_units_price_per_hour: None,
1263                embedding_price_per_1k_tokens: Some(0.0002),
1264            },
1265        };
1266
1267        Ok(pricing)
1268    }
1269}
1270
1271/// Azure Cognitive Services integration
1272#[allow(dead_code)]
1273pub struct AzureCognitiveServices {
1274    subscription_key: String,
1275    endpoint: String,
1276    region: String,
1277}
1278
1279impl AzureCognitiveServices {
1280    pub fn new(subscription_key: String, endpoint: String, region: String) -> Self {
1281        Self {
1282            subscription_key,
1283            endpoint,
1284            region,
1285        }
1286    }
1287
1288    /// Generate text embeddings using Azure OpenAI
1289    pub async fn generate_embeddings(
1290        &self,
1291        deployment_name: &str,
1292        input_texts: &[String],
1293    ) -> Result<AzureEmbeddingResult> {
1294        // Mock implementation for Azure OpenAI embeddings
1295        let embeddings = input_texts
1296            .iter()
1297            .enumerate()
1298            .map(|(i, text)| {
1299                let embedding: Vec<f32> = (0..1536)
1300                    .map(|j| (i as f32 * 0.01) + (j as f32 * 0.001) + (text.len() as f32 * 0.001))
1301                    .collect();
1302                embedding
1303            })
1304            .collect();
1305
1306        Ok(AzureEmbeddingResult {
1307            embeddings,
1308            model: deployment_name.to_string(),
1309            usage: TokenUsage {
1310                prompt_tokens: input_texts
1311                    .iter()
1312                    .map(|t| t.split_whitespace().count() as u32)
1313                    .sum(),
1314                total_tokens: input_texts
1315                    .iter()
1316                    .map(|t| t.split_whitespace().count() as u32)
1317                    .sum(),
1318            },
1319        })
1320    }
1321
1322    /// Analyze text sentiment
1323    pub async fn analyze_sentiment(&self, text: &str) -> Result<SentimentResult> {
1324        // Mock sentiment analysis
1325        let score = (text.len() % 100) as f32 / 100.0;
1326        let sentiment = if score > 0.6 {
1327            "positive"
1328        } else if score < 0.4 {
1329            "negative"
1330        } else {
1331            "neutral"
1332        };
1333
1334        Ok(SentimentResult {
1335            sentiment: sentiment.to_string(),
1336            confidence_scores: SentimentScores {
1337                positive: if sentiment == "positive" {
1338                    score
1339                } else {
1340                    1.0 - score
1341                },
1342                neutral: if sentiment == "neutral" {
1343                    score
1344                } else {
1345                    (1.0 - score) / 2.0
1346                },
1347                negative: if sentiment == "negative" {
1348                    score
1349                } else {
1350                    1.0 - score
1351                },
1352            },
1353        })
1354    }
1355
1356    /// Extract key phrases from text
1357    pub async fn extract_key_phrases(&self, text: &str) -> Result<Vec<String>> {
1358        // Mock key phrase extraction
1359        let words: Vec<&str> = text.split_whitespace().collect();
1360        let key_phrases = words
1361            .chunks(2)
1362            .take(5)
1363            .map(|chunk| chunk.join(" "))
1364            .collect();
1365
1366        Ok(key_phrases)
1367    }
1368
1369    /// Detect language
1370    pub async fn detect_language(&self, text: &str) -> Result<LanguageDetectionResult> {
1371        // Mock language detection
1372        let confidence = 0.95;
1373        let language = if text.contains("the") || text.contains("and") {
1374            "en"
1375        } else if text.contains("le") || text.contains("et") {
1376            "fr"
1377        } else {
1378            "en"
1379        };
1380
1381        Ok(LanguageDetectionResult {
1382            language: language.to_string(),
1383            confidence,
1384            is_translation_supported: true,
1385            is_transliteration_supported: false,
1386        })
1387    }
1388}
1389
1390/// Azure Container Instances integration
1391#[allow(dead_code)]
1392pub struct AzureContainerInstances {
1393    subscription_id: String,
1394    resource_group: String,
1395    tenant_id: String,
1396    client_id: String,
1397    client_secret: String,
1398}
1399
1400impl AzureContainerInstances {
1401    pub fn new(
1402        subscription_id: String,
1403        resource_group: String,
1404        tenant_id: String,
1405        client_id: String,
1406        client_secret: String,
1407    ) -> Self {
1408        Self {
1409            subscription_id,
1410            resource_group,
1411            tenant_id,
1412            client_id,
1413            client_secret,
1414        }
1415    }
1416
1417    /// Create container group
1418    pub async fn create_container_group(
1419        &self,
1420        config: &ContainerGroupConfig,
1421    ) -> Result<ContainerGroupResult> {
1422        let container_group_id = format!("aci-{}", Uuid::new_v4());
1423
1424        let estimated_cost = config.containers.iter().fold(0.0, |acc, container| {
1425            acc + match container.cpu_cores {
1426                cores if cores <= 1.0 => 0.0012, // $0.0012 per vCPU-second
1427                cores if cores <= 2.0 => 0.0024,
1428                _ => 0.0048,
1429            } * 3600.0 // Per hour
1430        });
1431
1432        Ok(ContainerGroupResult {
1433            container_group_id,
1434            name: config.name.clone(),
1435            status: ContainerGroupStatus::Creating,
1436            fqdn: Some(format!(
1437                "{}.{}.azurecontainer.io",
1438                config.name, config.location
1439            )),
1440            ip_address: Some("20.1.2.3".to_string()),
1441            containers: config
1442                .containers
1443                .iter()
1444                .map(|c| ContainerStatus {
1445                    name: c.name.clone(),
1446                    status: "Creating".to_string(),
1447                    restart_count: 0,
1448                    current_state: "Waiting".to_string(),
1449                })
1450                .collect(),
1451            creation_time: Utc::now(),
1452            estimated_hourly_cost: estimated_cost,
1453        })
1454    }
1455
1456    /// Get container group status
1457    pub async fn get_container_group_status(
1458        &self,
1459        _container_group_name: &str,
1460    ) -> Result<ContainerGroupStatus> {
1461        // Mock status check
1462        Ok(ContainerGroupStatus::Running)
1463    }
1464
1465    /// Delete container group
1466    pub async fn delete_container_group(&self, container_group_name: &str) -> Result<()> {
1467        println!("Deleting Azure Container Group: {container_group_name}");
1468        Ok(())
1469    }
1470
1471    /// Get container logs
1472    pub async fn get_container_logs(
1473        &self,
1474        container_group_name: &str,
1475        container_name: &str,
1476    ) -> Result<String> {
1477        Ok(format!(
1478            "[2025-06-30 10:00:00] Container {container_name} in group {container_group_name} started successfully\n[2025-06-30 10:00:01] Application initialized\n[2025-06-30 10:00:02] Ready to accept requests"
1479        ))
1480    }
1481}
1482
1483/// Foundation model information
1484#[derive(Debug, Clone)]
1485pub struct FoundationModel {
1486    pub model_id: String,
1487    pub model_name: String,
1488    pub provider_name: String,
1489    pub input_modalities: Vec<String>,
1490    pub output_modalities: Vec<String>,
1491    pub supported_inference_types: Vec<String>,
1492    pub model_lifecycle_status: String,
1493}
1494
1495/// Bedrock embedding result
1496#[derive(Debug, Clone)]
1497pub struct BedrockEmbeddingResult {
1498    pub embedding: Vec<f32>,
1499    pub input_token_count: u32,
1500    pub model_id: String,
1501    pub response_metadata: HashMap<String, String>,
1502}
1503
1504/// Model pricing information
1505#[derive(Debug, Clone)]
1506pub struct ModelPricing {
1507    pub input_token_price_per_1k: f64,
1508    pub output_token_price_per_1k: f64,
1509    pub model_units_price_per_hour: Option<f64>,
1510    pub embedding_price_per_1k_tokens: Option<f64>,
1511}
1512
1513/// Azure embedding result
1514#[derive(Debug, Clone)]
1515pub struct AzureEmbeddingResult {
1516    pub embeddings: Vec<Vec<f32>>,
1517    pub model: String,
1518    pub usage: TokenUsage,
1519}
1520
1521/// Token usage information
1522#[derive(Debug, Clone)]
1523pub struct TokenUsage {
1524    pub prompt_tokens: u32,
1525    pub total_tokens: u32,
1526}
1527
1528/// Sentiment analysis result
1529#[derive(Debug, Clone)]
1530pub struct SentimentResult {
1531    pub sentiment: String,
1532    pub confidence_scores: SentimentScores,
1533}
1534
1535/// Sentiment confidence scores
1536#[derive(Debug, Clone)]
1537pub struct SentimentScores {
1538    pub positive: f32,
1539    pub neutral: f32,
1540    pub negative: f32,
1541}
1542
1543/// Language detection result
1544#[derive(Debug, Clone)]
1545pub struct LanguageDetectionResult {
1546    pub language: String,
1547    pub confidence: f32,
1548    pub is_translation_supported: bool,
1549    pub is_transliteration_supported: bool,
1550}
1551
1552/// Container group configuration
1553#[derive(Debug, Clone)]
1554pub struct ContainerGroupConfig {
1555    pub name: String,
1556    pub location: String,
1557    pub os_type: String,
1558    pub restart_policy: String,
1559    pub containers: Vec<ContainerConfig>,
1560    pub ip_address_type: String,
1561    pub dns_name_label: Option<String>,
1562}
1563
1564/// Container configuration
1565#[derive(Debug, Clone)]
1566pub struct ContainerConfig {
1567    pub name: String,
1568    pub image: String,
1569    pub cpu_cores: f32,
1570    pub memory_gb: f32,
1571    pub ports: Vec<ContainerPort>,
1572    pub environment_variables: HashMap<String, String>,
1573    pub command: Option<Vec<String>>,
1574}
1575
1576/// Container port configuration
1577#[derive(Debug, Clone)]
1578pub struct ContainerPort {
1579    pub port: u16,
1580    pub protocol: String,
1581}
1582
1583/// Container group result
1584#[derive(Debug, Clone)]
1585pub struct ContainerGroupResult {
1586    pub container_group_id: String,
1587    pub name: String,
1588    pub status: ContainerGroupStatus,
1589    pub fqdn: Option<String>,
1590    pub ip_address: Option<String>,
1591    pub containers: Vec<ContainerStatus>,
1592    pub creation_time: DateTime<Utc>,
1593    pub estimated_hourly_cost: f64,
1594}
1595
1596/// Container group status
1597#[derive(Debug, Clone)]
1598pub enum ContainerGroupStatus {
1599    Creating,
1600    Running,
1601    Succeeded,
1602    Failed,
1603    Terminated,
1604}
1605
1606/// Container status
1607#[derive(Debug, Clone)]
1608pub struct ContainerStatus {
1609    pub name: String,
1610    pub status: String,
1611    pub restart_count: u32,
1612    pub current_state: String,
1613}
1614
1615/// Deployment configuration
1616#[derive(Debug, Clone)]
1617pub struct DeploymentConfig {
1618    pub model_name: String,
1619    pub model_version: String,
1620    pub instance_type: String,
1621    pub initial_instance_count: u32,
1622    pub auto_scaling_enabled: bool,
1623    pub environment_variables: HashMap<String, String>,
1624    pub resource_requirements: ResourceRequirements,
1625    pub networking: NetworkingConfig,
1626    pub data_capture: Option<DataCaptureConfig>,
1627}
1628
1629/// Resource requirements
1630#[derive(Debug, Clone)]
1631pub struct ResourceRequirements {
1632    pub cpu_cores: f32,
1633    pub memory_gb: f32,
1634    pub gpu_count: u32,
1635    pub storage_gb: u32,
1636}
1637
1638/// Networking configuration
1639#[derive(Debug, Clone)]
1640pub struct NetworkingConfig {
1641    pub vpc_config: Option<VPCConfig>,
1642    pub enable_network_isolation: bool,
1643    pub custom_security_groups: Vec<String>,
1644}
1645
1646/// Data capture configuration
1647#[derive(Debug, Clone)]
1648pub struct DataCaptureConfig {
1649    pub enabled: bool,
1650    pub initial_sampling_percentage: f32,
1651    pub destination_s3_uri: String,
1652    pub kms_key_id: Option<String>,
1653}
1654
1655/// Deployment result
1656#[derive(Debug, Clone)]
1657pub struct DeploymentResult {
1658    pub deployment_id: String,
1659    pub status: DeploymentStatus,
1660    pub endpoint_url: Option<String>,
1661    pub estimated_completion: Option<DateTime<Utc>>,
1662    pub cost_estimate: Option<CostEstimate>,
1663    pub metadata: HashMap<String, String>,
1664}
1665
1666/// Deployment status
1667#[derive(Debug, Clone, Serialize, Deserialize)]
1668pub enum DeploymentStatus {
1669    Creating,
1670    InService,
1671    Updating,
1672    Failed,
1673    Deleting,
1674    OutOfService,
1675}
1676
1677/// Endpoint information
1678#[derive(Debug, Clone)]
1679pub struct EndpointInfo {
1680    pub deployment_id: String,
1681    pub endpoint_url: String,
1682    pub status: EndpointStatus,
1683    pub instance_type: String,
1684    pub instance_count: u32,
1685    pub auto_scaling_enabled: bool,
1686    pub creation_time: DateTime<Utc>,
1687    pub last_modified_time: DateTime<Utc>,
1688    pub model_data_url: Option<String>,
1689}
1690
1691/// Endpoint status
1692#[derive(Debug, Clone)]
1693pub enum EndpointStatus {
1694    OutOfService,
1695    Creating,
1696    Updating,
1697    SystemUpdating,
1698    RollingBack,
1699    InService,
1700    Deleting,
1701    Failed,
1702}
1703
1704/// Scaling result
1705#[derive(Debug, Clone)]
1706pub struct ScalingResult {
1707    pub deployment_id: String,
1708    pub previous_instance_count: u32,
1709    pub target_instance_count: u32,
1710    pub scaling_status: ScalingStatus,
1711    pub estimated_completion: Option<DateTime<Utc>>,
1712}
1713
1714/// Scaling status
1715#[derive(Debug, Clone)]
1716pub enum ScalingStatus {
1717    InProgress,
1718    Completed,
1719    Failed,
1720}
1721
1722/// Deployment metrics
1723#[derive(Debug, Clone)]
1724pub struct DeploymentMetrics {
1725    pub deployment_id: String,
1726    pub time_range: (DateTime<Utc>, DateTime<Utc>),
1727    pub invocations: u64,
1728    pub average_latency_ms: f64,
1729    pub error_rate: f64,
1730    pub throughput_per_second: f64,
1731    pub cpu_utilization: f64,
1732    pub memory_utilization: f64,
1733    pub network_in_mb: f64,
1734    pub network_out_mb: f64,
1735    pub costs: HashMap<String, f64>,
1736}
1737
1738/// Update result
1739#[derive(Debug, Clone)]
1740pub struct UpdateResult {
1741    pub deployment_id: String,
1742    pub update_status: UpdateStatus,
1743    pub previous_config: DeploymentConfig,
1744    pub new_config: DeploymentConfig,
1745    pub estimated_completion: Option<DateTime<Utc>>,
1746}
1747
1748/// Update status
1749#[derive(Debug, Clone)]
1750pub enum UpdateStatus {
1751    InProgress,
1752    Completed,
1753    Failed,
1754    RollingBack,
1755}
1756
1757/// Deployment information
1758#[derive(Debug, Clone)]
1759pub struct DeploymentInfo {
1760    pub deployment_id: String,
1761    pub name: String,
1762    pub status: DeploymentStatus,
1763    pub model_name: String,
1764    pub instance_type: String,
1765    pub instance_count: u32,
1766    pub creation_time: DateTime<Utc>,
1767    pub last_modified_time: DateTime<Utc>,
1768}
1769
1770/// Cost estimate
1771#[derive(Debug, Clone)]
1772pub struct CostEstimate {
1773    pub setup_cost_usd: f64,
1774    pub hourly_cost_usd: f64,
1775    pub storage_cost_usd_per_gb: f64,
1776    pub data_transfer_cost_usd_per_gb: f64,
1777    pub estimated_monthly_cost_usd: f64,
1778}
1779
1780impl CloudIntegrationManager {
1781    /// Create new cloud integration manager
1782    pub fn new(config: CloudIntegrationConfig) -> Self {
1783        Self {
1784            providers: Arc::new(RwLock::new(HashMap::new())),
1785            config,
1786        }
1787    }
1788
1789    /// Register cloud provider
1790    pub async fn register_provider(
1791        &self,
1792        provider_type: CloudProvider,
1793        service: Box<dyn CloudService>,
1794    ) -> Result<()> {
1795        let mut providers = self.providers.write().await;
1796        providers.insert(provider_type, service);
1797        Ok(())
1798    }
1799
1800    /// Deploy model to cloud
1801    pub async fn deploy_model(
1802        &self,
1803        provider: Option<CloudProvider>,
1804        config: &DeploymentConfig,
1805    ) -> Result<DeploymentResult> {
1806        let provider_type = provider.unwrap_or_else(|| self.config.default_provider.clone());
1807        let providers = self.providers.read().await;
1808
1809        let service = providers
1810            .get(&provider_type)
1811            .ok_or_else(|| anyhow!("Provider not registered: {:?}", provider_type))?;
1812
1813        service.deploy_model(config).await
1814    }
1815
1816    /// Get multi-cloud cost comparison
1817    pub async fn compare_costs(
1818        &self,
1819        config: &DeploymentConfig,
1820        duration_hours: u32,
1821    ) -> Result<HashMap<CloudProvider, CostEstimate>> {
1822        let providers = self.providers.read().await;
1823        let mut cost_comparison = HashMap::new();
1824
1825        for (provider_type, service) in providers.iter() {
1826            if let Ok(estimate) = service.estimate_costs(config, duration_hours).await {
1827                cost_comparison.insert(provider_type.clone(), estimate);
1828            }
1829        }
1830
1831        Ok(cost_comparison)
1832    }
1833
1834    /// Optimize deployment across providers
1835    pub async fn optimize_deployment(
1836        &self,
1837        config: &DeploymentConfig,
1838    ) -> Result<OptimizationRecommendation> {
1839        let cost_comparison = self.compare_costs(config, 24 * 30).await?; // Monthly comparison
1840
1841        let cheapest_provider = cost_comparison
1842            .iter()
1843            .min_by(|a, b| {
1844                a.1.estimated_monthly_cost_usd
1845                    .partial_cmp(&b.1.estimated_monthly_cost_usd)
1846                    .unwrap()
1847            })
1848            .map(|(provider, _)| provider.clone());
1849
1850        Ok(OptimizationRecommendation {
1851            recommended_provider: cheapest_provider,
1852            cost_savings: cost_comparison,
1853            performance_considerations: vec![
1854                "Consider network latency to your primary data sources".to_string(),
1855                "Evaluate regional availability and compliance requirements".to_string(),
1856            ],
1857            risk_assessment: "Low risk for cost optimization, medium risk for performance changes"
1858                .to_string(),
1859        })
1860    }
1861}
1862
1863/// Optimization recommendation
1864#[derive(Debug, Clone)]
1865pub struct OptimizationRecommendation {
1866    pub recommended_provider: Option<CloudProvider>,
1867    pub cost_savings: HashMap<CloudProvider, CostEstimate>,
1868    pub performance_considerations: Vec<String>,
1869    pub risk_assessment: String,
1870}
1871
1872impl Default for CloudIntegrationConfig {
1873    fn default() -> Self {
1874        Self {
1875            default_provider: CloudProvider::AWS,
1876            auto_scaling: AutoScalingConfig {
1877                enabled: true,
1878                min_instances: 1,
1879                max_instances: 10,
1880                target_cpu_utilization: 70.0,
1881                target_memory_utilization: 80.0,
1882                scale_up_threshold: 80.0,
1883                scale_down_threshold: 30.0,
1884                cooldown_period_seconds: 300,
1885            },
1886            cost_optimization: CostOptimizationConfig {
1887                enabled: true,
1888                max_hourly_cost_usd: 50.0,
1889                use_spot_instances: false,
1890                auto_shutdown_idle: true,
1891                idle_threshold_minutes: 30,
1892                reserved_capacity_percentage: 20.0,
1893            },
1894            security: SecurityConfig {
1895                encryption_at_rest: true,
1896                encryption_in_transit: true,
1897                vpc_config: None,
1898                iam_config: None,
1899                network_acl: vec![],
1900            },
1901            monitoring: MonitoringConfig {
1902                enabled: true,
1903                collection_interval_seconds: 60,
1904                alert_thresholds: HashMap::from([
1905                    ("cpu_utilization".to_string(), 85.0),
1906                    ("memory_utilization".to_string(), 90.0),
1907                    ("error_rate".to_string(), 0.05),
1908                ]),
1909                notification_endpoints: vec![],
1910            },
1911        }
1912    }
1913}
1914
1915#[cfg(test)]
1916mod tests {
1917    use super::*;
1918
1919    #[tokio::test]
1920    async fn test_cloud_integration_manager_creation() {
1921        let config = CloudIntegrationConfig::default();
1922        let manager = CloudIntegrationManager::new(config);
1923
1924        let providers = manager.providers.read().await;
1925        assert!(providers.is_empty());
1926    }
1927
1928    #[tokio::test]
1929    async fn test_aws_sagemaker_service() {
1930        let service = AWSSageMakerService::new(
1931            "us-east-1".to_string(),
1932            "test_key".to_string(),
1933            "test_secret".to_string(),
1934            None,
1935        );
1936
1937        let config = DeploymentConfig {
1938            model_name: "test-model".to_string(),
1939            model_version: "1.0".to_string(),
1940            instance_type: "ml.m5.large".to_string(),
1941            initial_instance_count: 1,
1942            auto_scaling_enabled: true,
1943            environment_variables: HashMap::new(),
1944            resource_requirements: ResourceRequirements {
1945                cpu_cores: 2.0,
1946                memory_gb: 8.0,
1947                gpu_count: 0,
1948                storage_gb: 50,
1949            },
1950            networking: NetworkingConfig {
1951                vpc_config: None,
1952                enable_network_isolation: false,
1953                custom_security_groups: vec![],
1954            },
1955            data_capture: None,
1956        };
1957
1958        let result = service.deploy_model(&config).await.unwrap();
1959        assert!(matches!(result.status, DeploymentStatus::Creating));
1960        assert!(result.cost_estimate.is_some());
1961    }
1962
1963    #[tokio::test]
1964    async fn test_cost_estimation() {
1965        let service = AWSSageMakerService::new(
1966            "us-east-1".to_string(),
1967            "test_key".to_string(),
1968            "test_secret".to_string(),
1969            None,
1970        );
1971
1972        let config = DeploymentConfig {
1973            model_name: "test-model".to_string(),
1974            model_version: "1.0".to_string(),
1975            instance_type: "ml.m5.large".to_string(),
1976            initial_instance_count: 2,
1977            auto_scaling_enabled: true,
1978            environment_variables: HashMap::new(),
1979            resource_requirements: ResourceRequirements {
1980                cpu_cores: 2.0,
1981                memory_gb: 8.0,
1982                gpu_count: 0,
1983                storage_gb: 50,
1984            },
1985            networking: NetworkingConfig {
1986                vpc_config: None,
1987                enable_network_isolation: false,
1988                custom_security_groups: vec![],
1989            },
1990            data_capture: None,
1991        };
1992
1993        let estimate = service.estimate_costs(&config, 24).await.unwrap();
1994        assert!(estimate.hourly_cost_usd > 0.0);
1995        assert!(estimate.estimated_monthly_cost_usd > 0.0);
1996    }
1997}
oxirs_embed/cloud_integration.rs

oxirs_embed/
cloud_integration.rs
