1use anyhow::Result;
12use async_trait::async_trait;
13use chrono::{DateTime, Utc};
14use std::collections::HashMap;
15use uuid::Uuid;
16
17use super::types::{
18 AzureMLService, CloudService, ClusterStatus, CostEstimate, CostOptimizationResult,
19 CostOptimizationStrategy, DeploymentConfig, DeploymentInfo, DeploymentMetrics,
20 DeploymentResult, DeploymentStatus, EndpointInfo, EndpointStatus, FunctionInvocationResult,
21 GPUClusterConfig, GPUClusterResult, ImplementationEffort, OptimizationAction,
22 OptimizationPhase, PerformanceTier, ScalingResult, ScalingStatus, ServerlessDeploymentResult,
23 ServerlessFunctionConfig, ServerlessStatus, StorageConfig, StoragePerformanceMetrics,
24 StorageResult, StorageStatus, StorageType, UpdateResult, UpdateStatus,
25};
26
27#[async_trait]
28impl CloudService for AzureMLService {
29 async fn deploy_model(
30 &self,
31 _deployment_config: &DeploymentConfig,
32 ) -> Result<DeploymentResult> {
33 let deployment_id = format!("azure-{}", Uuid::new_v4());
34 Ok(DeploymentResult {
35 deployment_id,
36 status: DeploymentStatus::Creating,
37 endpoint_url: None,
38 estimated_completion: Some(Utc::now() + chrono::Duration::minutes(12)),
39 cost_estimate: Some(CostEstimate {
40 setup_cost_usd: 0.0,
41 hourly_cost_usd: 1.20,
42 storage_cost_usd_per_gb: 0.15,
43 data_transfer_cost_usd_per_gb: 0.08,
44 estimated_monthly_cost_usd: 864.0,
45 }),
46 metadata: HashMap::new(),
47 })
48 }
49 async fn get_endpoint(&self, deployment_id: &str) -> Result<EndpointInfo> {
50 Ok(EndpointInfo {
51 deployment_id: deployment_id.to_string(),
52 endpoint_url: format!(
53 "https://{}.{}.inference.ml.azure.com/score",
54 deployment_id, self.workspace_name
55 ),
56 status: EndpointStatus::InService,
57 instance_type: "Standard_DS3_v2".to_string(),
58 instance_count: 1,
59 auto_scaling_enabled: true,
60 creation_time: Utc::now(),
61 last_modified_time: Utc::now(),
62 model_data_url: None,
63 })
64 }
65 async fn scale_deployment(
66 &self,
67 deployment_id: &str,
68 target_instances: u32,
69 ) -> Result<ScalingResult> {
70 Ok(ScalingResult {
71 deployment_id: deployment_id.to_string(),
72 previous_instance_count: 1,
73 target_instance_count: target_instances,
74 scaling_status: ScalingStatus::InProgress,
75 estimated_completion: Some(Utc::now() + chrono::Duration::minutes(7)),
76 })
77 }
78 async fn get_metrics(
79 &self,
80 deployment_id: &str,
81 time_range: (DateTime<Utc>, DateTime<Utc>),
82 ) -> Result<DeploymentMetrics> {
83 Ok(DeploymentMetrics {
84 deployment_id: deployment_id.to_string(),
85 time_range,
86 invocations: 1200,
87 average_latency_ms: 52.8,
88 error_rate: 0.015,
89 throughput_per_second: 20.1,
90 cpu_utilization: 58.3,
91 memory_utilization: 71.9,
92 network_in_mb: 89.2,
93 network_out_mb: 76.5,
94 costs: HashMap::from([
95 ("compute".to_string(), 12.60),
96 ("storage".to_string(), 3.20),
97 ("data_transfer".to_string(), 1.10),
98 ]),
99 })
100 }
101 async fn update_deployment(
102 &self,
103 deployment_id: &str,
104 config: &DeploymentConfig,
105 ) -> Result<UpdateResult> {
106 Ok(UpdateResult {
107 deployment_id: deployment_id.to_string(),
108 update_status: UpdateStatus::InProgress,
109 previous_config: config.clone(),
110 new_config: config.clone(),
111 estimated_completion: Some(Utc::now() + chrono::Duration::minutes(10)),
112 })
113 }
114 async fn delete_deployment(&self, deployment_id: &str) -> Result<()> {
115 println!("Deleting Azure ML deployment: {}", deployment_id);
116 Ok(())
117 }
118 async fn list_deployments(&self) -> Result<Vec<DeploymentInfo>> {
119 Ok(vec![])
120 }
121 async fn estimate_costs(
122 &self,
123 config: &DeploymentConfig,
124 _duration_hours: u32,
125 ) -> Result<CostEstimate> {
126 let hourly_rate = match config.instance_type.as_str() {
127 "Standard_DS2_v2" => 0.14,
128 "Standard_DS3_v2" => 0.28,
129 "Standard_DS4_v2" => 0.56,
130 "Standard_NC6s_v3" => 3.06,
131 _ => 0.28,
132 };
133 Ok(CostEstimate {
134 setup_cost_usd: 0.0,
135 hourly_cost_usd: hourly_rate * config.initial_instance_count as f64,
136 storage_cost_usd_per_gb: 0.184,
137 data_transfer_cost_usd_per_gb: 0.087,
138 estimated_monthly_cost_usd: hourly_rate
139 * config.initial_instance_count as f64
140 * 24.0
141 * 30.0,
142 })
143 }
144 async fn deploy_serverless_function(
145 &self,
146 function_config: &ServerlessFunctionConfig,
147 ) -> Result<ServerlessDeploymentResult> {
148 let function_arn = format!(
149 "/subscriptions/{}/resourceGroups/{}/providers/Microsoft.Web/sites/{}/functions/{}",
150 self.subscription_id,
151 self.resource_group,
152 self.workspace_name,
153 function_config.function_name
154 );
155 Ok(ServerlessDeploymentResult {
156 function_arn,
157 function_name: function_config.function_name.clone(),
158 status: ServerlessStatus::Pending,
159 invoke_url: Some(format!(
160 "https://{}.azurewebsites.net/api/{}",
161 self.workspace_name, function_config.function_name
162 )),
163 version: "1".to_string(),
164 last_modified: Utc::now(),
165 })
166 }
167 async fn invoke_function(
168 &self,
169 function_name: &str,
170 payload: &[u8],
171 ) -> Result<FunctionInvocationResult> {
172 let execution_duration = 180 + (payload.len() / 800) as u32;
173 Ok(FunctionInvocationResult {
174 execution_duration_ms: execution_duration,
175 billed_duration_ms: execution_duration,
176 memory_used_mb: 256,
177 max_memory_used_mb: 512,
178 response_payload:
179 b"{\"status\": \"success\", \"message\": \"Azure function executed\"}".to_vec(),
180 log_result: Some(format!(
181 "Executing '{function_name}' (ID: azure-123, Duration: {execution_duration}ms)"
182 )),
183 status_code: 200,
184 })
185 }
186 async fn create_gpu_cluster(
187 &self,
188 cluster_config: &GPUClusterConfig,
189 ) -> Result<GPUClusterResult> {
190 let cluster_id = format!("aks-gpu-{}", Uuid::new_v4());
191 let hourly_cost = match cluster_config.gpu_type.as_str() {
192 "V100" => 2.84 * cluster_config.min_nodes as f64,
193 "A100" => 4.25 * cluster_config.min_nodes as f64,
194 "T4" => 1.28 * cluster_config.min_nodes as f64,
195 _ => 1.90 * cluster_config.min_nodes as f64,
196 };
197 Ok(GPUClusterResult {
198 cluster_id,
199 cluster_name: cluster_config.cluster_name.clone(),
200 status: ClusterStatus::Creating,
201 endpoint: format!(
202 "https://{}-{}.hcp.eastus.azmk8s.io:443",
203 cluster_config.cluster_name, self.resource_group
204 ),
205 node_count: cluster_config.min_nodes,
206 total_gpu_count: cluster_config.min_nodes * cluster_config.gpu_count_per_node,
207 creation_time: Utc::now(),
208 estimated_hourly_cost: hourly_cost,
209 })
210 }
211 async fn manage_storage(&self, storage_config: &StorageConfig) -> Result<StorageResult> {
212 let storage_id = format!("azure-storage-{}", Uuid::new_v4());
213 let monthly_cost = match storage_config.storage_type {
214 StorageType::ObjectStorage => storage_config.capacity_gb as f64 * 0.0208,
215 StorageType::BlockStorage => storage_config.capacity_gb as f64 * 0.175,
216 StorageType::FileStorage => storage_config.capacity_gb as f64 * 0.60,
217 StorageType::DataLake => storage_config.capacity_gb as f64 * 0.0208,
218 };
219 let performance_metrics = match storage_config.performance_tier {
220 PerformanceTier::Standard => StoragePerformanceMetrics {
221 read_iops: 2300,
222 write_iops: 2300,
223 throughput_mbps: 150,
224 latency_ms: 15.0,
225 },
226 PerformanceTier::HighPerformance => StoragePerformanceMetrics {
227 read_iops: 20000,
228 write_iops: 20000,
229 throughput_mbps: 900,
230 latency_ms: 2.0,
231 },
232 _ => StoragePerformanceMetrics {
233 read_iops: 100,
234 write_iops: 100,
235 throughput_mbps: 10,
236 latency_ms: 120.0,
237 },
238 };
239 Ok(StorageResult {
240 storage_id: storage_id.clone(),
241 endpoint: format!("https://{storage_id}.blob.core.windows.net/"),
242 status: StorageStatus::Creating,
243 actual_capacity_gb: storage_config.capacity_gb,
244 monthly_cost_estimate: monthly_cost,
245 performance_metrics,
246 })
247 }
248 async fn optimize_costs(
249 &self,
250 optimization_config: &CostOptimizationStrategy,
251 ) -> Result<CostOptimizationResult> {
252 let mut actions = Vec::new();
253 let mut total_savings = 0.0;
254 if optimization_config.use_spot_instances {
255 actions.push(OptimizationAction {
256 action_type: "Spot Virtual Machines".to_string(),
257 description: format!(
258 "Use Azure spot VMs for {}% of workload",
259 optimization_config.spot_instance_percentage * 100.0
260 ),
261 estimated_savings_usd: 450.0,
262 implementation_effort: ImplementationEffort::Medium,
263 });
264 total_savings += 450.0;
265 }
266 if optimization_config.use_reserved_instances {
267 actions.push(OptimizationAction {
268 action_type: "Azure Reserved VM Instances".to_string(),
269 description: format!(
270 "Purchase 1-year or 3-year reservations for {}% of workload",
271 optimization_config.reserved_instance_percentage * 100.0
272 ),
273 estimated_savings_usd: 720.0,
274 implementation_effort: ImplementationEffort::Low,
275 });
276 total_savings += 720.0;
277 }
278 if optimization_config.use_savings_plans {
279 actions.push(OptimizationAction {
280 action_type: "Azure Savings Plans".to_string(),
281 description: "Commit to consistent compute usage with savings plans".to_string(),
282 estimated_savings_usd: 250.0,
283 implementation_effort: ImplementationEffort::Low,
284 });
285 total_savings += 250.0;
286 }
287 if optimization_config.rightsizing_enabled {
288 actions.push(OptimizationAction {
289 action_type: "VM Rightsizing".to_string(),
290 description: "Optimize VM sizes based on Azure Advisor recommendations".to_string(),
291 estimated_savings_usd: 280.0,
292 implementation_effort: ImplementationEffort::Medium,
293 });
294 total_savings += 280.0;
295 }
296 let implementation_timeline = vec![
297 OptimizationPhase {
298 phase_name: "Immediate Actions".to_string(),
299 duration_days: 5,
300 actions: vec![
301 "Reserved Instances Purchase".to_string(),
302 "Savings Plans".to_string(),
303 ],
304 expected_savings_usd: 970.0,
305 },
306 OptimizationPhase {
307 phase_name: "Implementation Phase".to_string(),
308 duration_days: 21,
309 actions: vec![
310 "Spot VM Migration".to_string(),
311 "VM Rightsizing".to_string(),
312 ],
313 expected_savings_usd: 730.0,
314 },
315 ];
316 Ok(CostOptimizationResult {
317 estimated_monthly_savings_usd: total_savings,
318 optimization_actions_taken: actions,
319 potential_risks: vec![
320 "Spot VMs may experience eviction".to_string(),
321 "Reserved instances require upfront payment".to_string(),
322 "Rightsizing may temporarily impact performance".to_string(),
323 ],
324 implementation_timeline,
325 })
326 }
327}