# SciRS2 Core 1.0 Architecture and Scaling Guide
## Table of Contents
1. [Architecture Overview](#architecture-overview)
2. [Component Architecture](#component-architecture)
3. [Deployment Architectures](#deployment-architectures)
4. [Scaling Patterns](#scaling-patterns)
5. [Performance Architecture](#performance-architecture)
6. [Distributed Computing](#distributed-computing)
7. [Cloud-Native Deployment](#cloud-native-deployment)
8. [Edge Computing](#edge-computing)
9. [Integration Patterns](#integration-patterns)
10. [Migration Strategies](#migration-strategies)
## Architecture Overview
SciRS2 Core 1.0 is designed as a modular, high-performance scientific computing library with enterprise-grade scalability, observability, and reliability features. The architecture supports multiple deployment patterns from single-node setups to large-scale distributed clusters.
### Core Design Principles
1. **Modularity**: Loosely coupled modules with well-defined interfaces
2. **Performance**: SIMD, parallel, and GPU acceleration at all levels
3. **Scalability**: Horizontal and vertical scaling capabilities
4. **Observability**: Built-in metrics, tracing, and monitoring
5. **Reliability**: Fault tolerance and graceful degradation
6. **Security**: Defense in depth with comprehensive audit trails
### High-Level Architecture
```
┌─────────────────────────────────────────────────────────────────┐
│ SciRS2 Core 1.0 Architecture │
├─────────────────────────────────────────────────────────────────┤
│ Application Layer │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │
│ │ Web Services │ │ Batch Jobs │ │ Interactive │ │
│ │ │ │ │ │ Notebooks │ │
│ └─────────────────┘ └─────────────────┘ └─────────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│ SciRS2 Core API Layer │
│ ┌─────────────────────────────────────────────────────────┐ │
│ │ Core APIs │ LinAlg │ Stats │ Signal │ Spatial │ ... │ │
│ └─────────────────────────────────────────────────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│ Execution Engine Layer │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ CPU/SIMD │ │ Multi-Core │ │ GPU/CUDA │ │
│ │ Engine │ │ Parallel │ │ Engine │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│ Storage and Memory Layer │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Memory- │ │ Distributed │ │ Cloud │ │
│ │ Mapped │ │ Storage │ │ Storage │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│ Cross-Cutting Concerns │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Observability│ │ Security │ │ Configuration│ │
│ │ & Monitoring │ │ & Audit │ │ Management │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
└─────────────────────────────────────────────────────────────────┘
```
## Component Architecture
### Core Module Structure
```rust
// Core module architecture
pub mod scirs2_core {
pub mod execution {
pub mod simd; // SIMD acceleration
pub mod parallel; // Multi-core processing
pub mod gpu; // GPU acceleration
pub mod distributed; // Distributed computing
}
pub mod memory {
pub mod efficient; // Memory-efficient operations
pub mod mapped; // Memory-mapped arrays
pub mod pools; // Memory pool management
pub mod compression; // Data compression
}
pub mod observability {
pub mod metrics; // Performance metrics
pub mod tracing; // Distributed tracing
pub mod audit; // Audit logging
pub mod health; // Health monitoring
}
pub mod scaling {
pub mod horizontal; // Horizontal scaling
pub mod vertical; // Vertical scaling
pub mod elastic; // Auto-scaling
pub mod load_balancing; // Load distribution
}
}
```
### Module Dependencies
```
scirs2-core (Foundation)
├── scirs2-linalg (Linear Algebra)
│ ├── scirs2-core
│ └── BLAS/LAPACK bindings
├── scirs2-stats (Statistics)
│ ├── scirs2-core
│ └── scirs2-linalg
├── scirs2-signal (Signal Processing)
│ ├── scirs2-core
│ ├── scirs2-linalg
│ └── scirs2-fft
├── scirs2-spatial (Spatial Operations)
│ ├── scirs2-core
│ └── scirs2-stats
└── scirs2 (Main Integration)
└── All modules via feature flags
```
### Data Flow Architecture
```
Input Data
↓
┌─────────────────┐
│ Data Validation │
│ & Preprocessing │
└─────────────────┘
↓
┌─────────────────┐
│ Memory Management│
│ & Optimization │
└─────────────────┘
↓
┌─────────────────┐
│ Execution Engine│
│ Selection │
└─────────────────┘
↓
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ CPU/SIMD │ OR │ Parallel │ OR │ GPU/Distributed │
│ Processing │ │ Processing │ │ Processing │
└─────────────────┘ └─────────────────┘ └─────────────────┘
↓ ↓ ↓
┌─────────────────────────────────────────────────────────────────┐
│ Result Aggregation │
└─────────────────────────────────────────────────────────────────┘
↓
┌─────────────────┐
│ Output │
│ Serialization │
└─────────────────┘
↓
Output Data
```
## Deployment Architectures
### Single-Node Deployment
```yaml
# docker-compose.yml for single-node deployment
version: '3.8'
services:
scirs2-core:
image: scirs2/core:1.0
ports:
- "8080:8080"
environment:
- SCIRS2_NUM_THREADS=8
- SCIRS2_MEMORY_LIMIT=8192
- SCIRS2_ENABLE_GPU=true
volumes:
- ./data:/var/lib/scirs2/data
- ./config:/etc/scirs2
resource_limits:
cpus: '8'
memory: 16G
prometheus:
image: prom/prometheus
ports:
- "9090:9090"
volumes:
- ./prometheus.yml:/etc/prometheus/prometheus.yml
grafana:
image: grafana/grafana
ports:
- "3000:3000"
environment:
- GF_SECURITY_ADMIN_PASSWORD=admin123
```
#### Single-Node Performance Characteristics
- **CPU**: 8-64 cores optimal
- **Memory**: 16GB-512GB depending on workload
- **Storage**: NVMe SSD recommended for data and temp files
- **Network**: 1-10 Gbps for data transfer
- **Throughput**: 10K-100K operations/second
### Multi-Node Cluster Deployment
```yaml
# kubernetes-cluster.yml
apiVersion: apps/v1
kind: Deployment
metadata:
name: scirs2-core-cluster
spec:
replicas: 5
selector:
matchLabels:
app: scirs2-core
template:
metadata:
labels:
app: scirs2-core
spec:
containers:
- name: scirs2-core
image: scirs2/core:1.0
ports:
- containerPort: 8080
env:
- name: SCIRS2_CLUSTER_MODE
value: "true"
- name: SCIRS2_CLUSTER_SIZE
value: "5"
- name: SCIRS2_DISCOVERY_SERVICE
value: "etcd.scirs2.svc.cluster.local:2379"
resources:
requests:
cpu: "4"
memory: "8Gi"
limits:
cpu: "8"
memory: "16Gi"
---
apiVersion: v1
kind: Service
metadata:
name: scirs2-core-service
spec:
selector:
app: scirs2-core
ports:
- port: 8080
targetPort: 8080
type: LoadBalancer
```
#### Cluster Performance Characteristics
- **Nodes**: 3-100+ nodes
- **Per-Node Resources**: 4-32 cores, 16-128GB RAM
- **Network**: 10-100 Gbps inter-node communication
- **Throughput**: 100K-10M operations/second
- **Latency**: 10-100ms for distributed operations
### High-Availability Deployment
```yaml
# ha-deployment.yml
apiVersion: apps/v1
kind: Deployment
metadata:
name: scirs2-core-ha
spec:
replicas: 3
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
selector:
matchLabels:
app: scirs2-core
tier: production
template:
metadata:
labels:
app: scirs2-core
tier: production
spec:
affinity:
podAntiAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
- labelSelector:
matchExpressions:
- key: app
operator: In
values:
- scirs2-core
topologyKey: kubernetes.io/hostname
containers:
- name: scirs2-core
image: scirs2/core:1.0
ports:
- containerPort: 8080
- containerPort: 9090 # metrics
livenessProbe:
httpGet:
path: /health
port: 8080
initialDelaySeconds: 30
periodSeconds: 10
readinessProbe:
httpGet:
path: /ready
port: 8080
initialDelaySeconds: 5
periodSeconds: 5
env:
- name: SCIRS2_HA_MODE
value: "true"
- name: SCIRS2_REPLICATION_FACTOR
value: "3"
```
## Scaling Patterns
### Horizontal Scaling
#### Auto-Scaling Configuration
```rust
use scirs2_core::scaling::{HorizontalScaler, ScalingPolicy};
// Configure horizontal scaling
let scaling_policy = ScalingPolicy::new()
.with_min_replicas(3)
.with_max_replicas(50)
.with_target_cpu_utilization(70.0)
.with_target_memory_utilization(80.0)
.with_scale_up_threshold(2) // Scale up after 2 measurement periods
.with_scale_down_threshold(5) // Scale down after 5 measurement periods
.with_scale_up_increment(2) // Add 2 replicas at a time
.with_scale_down_increment(1); // Remove 1 replica at a time
let horizontal_scaler = HorizontalScaler::new(scaling_policy);
// Monitor and scale
horizontal_scaler.start_monitoring()?;
```
#### Load-Based Scaling
```rust
use scirs2_core::scaling::{LoadBalancer, LoadMetrics};
// Configure load-based scaling
let load_balancer = LoadBalancer::new()
.with_algorithm(LoadBalancingAlgorithm::WeightedRoundRobin)
.with_health_checks(true)
.with_circuit_breaker(true);
// Custom scaling logic based on queue depth
let load_metrics = LoadMetrics::collect();
if load_metrics.queue_depth > 1000 {
horizontal_scaler.scale_up(2)?;
} else if load_metrics.queue_depth < 100 && load_metrics.avg_cpu < 30.0 {
horizontal_scaler.scale_down(1)?;
}
```
### Vertical Scaling
#### Dynamic Resource Allocation
```rust
use scirs2_core::scaling::{VerticalScaler, ResourceProfile};
// Configure vertical scaling
let resource_profiles = vec![
ResourceProfile::new("small")
.with_cpu_cores(4)
.with_memory_gb(8)
.with_cost_per_hour(0.20),
ResourceProfile::new("medium")
.with_cpu_cores(8)
.with_memory_gb(16)
.with_cost_per_hour(0.40),
ResourceProfile::new("large")
.with_cpu_cores(16)
.with_memory_gb(32)
.with_cost_per_hour(0.80),
ResourceProfile::new("xlarge")
.with_cpu_cores(32)
.with_memory_gb(64)
.with_cost_per_hour(1.60),
];
let vertical_scaler = VerticalScaler::new(resource_profiles);
// Automatic profile selection based on workload
let current_workload = WorkloadAnalyzer::analyze_current_workload()?;
let optimal_profile = vertical_scaler.recommend_profile(¤t_workload)?;
vertical_scaler.apply_profile(&optimal_profile)?;
```
### Elastic Scaling
#### Predictive Scaling
```rust
use scirs2_core::scaling::{PredictiveScaler, WorkloadPredictor};
// Configure predictive scaling
let workload_predictor = WorkloadPredictor::new()
.with_historical_data_days(30)
.with_prediction_horizon_hours(24)
.with_confidence_threshold(0.85);
let predictive_scaler = PredictiveScaler::new(workload_predictor);
// Scale based on predictions
let predicted_load = predictive_scaler.predict_load(
chrono::Utc::now() + chrono::Duration::hours(1)
)?;
if predicted_load.expected_operations_per_second > 50000 {
predictive_scaler.pre_scale_for_load(&predicted_load)?;
}
```
#### Event-Driven Scaling
```rust
use scirs2_core::scaling::{EventDrivenScaler, ScalingEvent};
// Configure event-driven scaling
let event_scaler = EventDrivenScaler::new()
.with_event_source("kafka://events.scirs2.internal:9092")
.with_scaling_rules(vec![
ScalingRule::new("batch_job_submitted")
.scale_up(5)
.with_timeout(Duration::from_secs(3600)),
ScalingRule::new("emergency_computation")
.scale_up(10)
.with_priority(ScalingPriority::High),
]);
// React to scaling events
"large_dataset_upload" => {
// Pre-emptively scale for data processing
Ok(ScalingAction::ScaleUp(3))
},
"peak_hour_start" => {
// Scale for expected load increase
Ok(ScalingAction::ScaleUp(5))
},
_ => Ok(ScalingAction::NoAction)
}
})?;
```
## Performance Architecture
### CPU Optimization Architecture
```rust
use scirs2_core::performance::{CpuOptimizer, CpuTopology};
// Detect and optimize for CPU topology
let cpu_topology = CpuTopology::detect()?;
let cpu_optimizer = CpuOptimizer::new(&cpu_topology);
// Configure NUMA-aware processing
cpu_optimizer.configure_numa_affinity()?;
cpu_optimizer.optimize_thread_placement()?;
// Enable specific CPU features
if cpu_topology.supports_avx512() {
cpu_optimizer.enable_avx512()?;
}
if cpu_topology.supports_tensor_operations() {
cpu_optimizer.enable_tensor_acceleration()?;
}
```
### Memory Architecture
```rust
use scirs2_core::memory::{MemoryArchitect, MemoryTopology};
// Design optimal memory layout
let memory_topology = MemoryTopology::detect()?;
let memory_architect = MemoryArchitect::new(&memory_topology);
// Configure memory pools
let memory_pools = memory_architect.design_memory_pools(
&[
PoolSpec::new("compute_pool")
.with_size_gb(32)
.with_numa_node(0)
.with_huge_pages(true),
PoolSpec::new("io_pool")
.with_size_gb(8)
.with_numa_node(1)
.with_prefault(true),
]
)?;
// Apply memory optimizations
memory_architect.apply_optimizations(&memory_pools)?;
```
### GPU Architecture
```rust
use scirs2_core::gpu::{GpuArchitect, GpuTopology, MultiGpuStrategy};
// Design multi-GPU processing architecture
let gpu_topology = GpuTopology::detect()?;
let gpu_architect = GpuArchitect::new(&gpu_topology);
// Configure multi-GPU strategy
let multi_gpu_strategy = match gpu_topology.gpu_count() {
1 => MultiGpuStrategy::Single,
2..=4 => MultiGpuStrategy::DataParallel,
5..=8 => MultiGpuStrategy::ModelParallel,
_ => MultiGpuStrategy::Hybrid,
};
gpu_architect.configure_multi_gpu_strategy(multi_gpu_strategy)?;
// Optimize GPU memory management
gpu_architect.optimize_memory_management()?;
gpu_architect.enable_peer_to_peer_transfer()?;
```
### Storage Architecture
```rust
use scirs2_core::storage::{StorageArchitect, StorageTier};
// Design tiered storage architecture
let storage_architect = StorageArchitect::new();
let storage_tiers = vec![
StorageTier::new("hot")
.with_type(StorageType::NVMe)
.with_capacity_gb(1024)
.with_iops(100000)
.with_latency_us(100),
StorageTier::new("warm")
.with_type(StorageType::SSD)
.with_capacity_gb(10240)
.with_iops(50000)
.with_latency_us(500),
StorageTier::new("cold")
.with_type(StorageType::HDD)
.with_capacity_gb(102400)
.with_iops(1000)
.with_latency_ms(10),
];
storage_architect.configure_tiered_storage(storage_tiers)?;
// Auto-tier data based on access patterns
storage_architect.enable_auto_tiering()?;
```
## Distributed Computing
### Cluster Architecture
```rust
use scirs2_core::distributed::{ClusterManager, NodeRole, ClusterTopology};
// Initialize cluster management
let cluster_manager = ClusterManager::new()
.with_discovery_service("etcd://cluster.scirs2.internal:2379")
.with_cluster_name("scirs2-production")
.with_encryption(true);
// Define cluster topology
let cluster_topology = ClusterTopology::new()
.with_coordinator_nodes(3)
.with_compute_nodes(20)
.with_storage_nodes(5)
.with_replication_factor(3);
// Join cluster
cluster_manager.join_cluster(NodeRole::Compute, cluster_topology)?;
```
### Distributed Processing
```rust
use scirs2_core::distributed::{DistributedArray, DistributedCompute};
// Create distributed arrays
let distributed_data = DistributedArray::from_local_array(
local_array,
DistributionStrategy::BlockDistribution { block_size: 1_000_000 }
)?;
// Distributed computation
let result = DistributedCompute::new()
.with_fault_tolerance(true)
.with_checkpointing(true)
.map(&distributed_data, |chunk| {
// Process each chunk
chunk.mapv(|x| x * 2.0 + 1.0)
})?
.reduce(|acc, chunk| {
// Reduce results
acc + chunk.sum()
})?;
```
### Fault Tolerance
```rust
use scirs2_core::distributed::{FaultTolerance, CheckpointManager};
// Configure fault tolerance
let fault_tolerance = FaultTolerance::new()
.with_replication_factor(3)
.with_node_failure_detection(Duration::from_secs(30))
.with_automatic_recovery(true);
// Checkpoint management
let checkpoint_manager = CheckpointManager::new()
.with_checkpoint_interval(Duration::from_secs(300)) // 5 minutes
.with_storage_backend("s3://scirs2-checkpoints/")
.with_compression(true);
// Execute fault-tolerant computation
fault_tolerance.execute_with_checkpoints(
&checkpoint_manager,
|| {
// Your computation here
long_running_computation()
}
)?;
```
## Cloud-Native Deployment
### Kubernetes Deployment
```yaml
# Complete Kubernetes deployment
apiVersion: v1
kind: Namespace
metadata:
name: scirs2
---
apiVersion: v1
kind: ConfigMap
metadata:
name: scirs2-config
namespace: scirs2
data:
config.toml: |
[runtime]
num_threads = 8
memory_limit_mb = 8192
[observability]
metrics_endpoint = "http://prometheus.monitoring.svc.cluster.local:9090"
tracing_endpoint = "http://jaeger.monitoring.svc.cluster.local:14268"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: scirs2-core
namespace: scirs2
spec:
replicas: 5
selector:
matchLabels:
app: scirs2-core
template:
metadata:
labels:
app: scirs2-core
spec:
containers:
- name: scirs2-core
image: scirs2/core:1.0
ports:
- containerPort: 8080
- containerPort: 9090
volumeMounts:
- name: config
mountPath: /etc/scirs2
- name: data
mountPath: /var/lib/scirs2
resources:
requests:
cpu: "4"
memory: "8Gi"
nvidia.com/gpu: "1"
limits:
cpu: "8"
memory: "16Gi"
nvidia.com/gpu: "1"
volumes:
- name: config
configMap:
name: scirs2-config
- name: data
persistentVolumeClaim:
claimName: scirs2-data
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: scirs2-data
namespace: scirs2
spec:
accessModes:
- ReadWriteMany
resources:
requests:
storage: 1Ti
storageClassName: fast-ssd
```
### Service Mesh Integration
```yaml
# Istio service mesh configuration
apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
name: scirs2-core
namespace: scirs2
spec:
hosts:
- scirs2-core
http:
- match:
- headers:
priority:
exact: high
route:
- destination:
host: scirs2-core
subset: high-priority
weight: 100
- route:
- destination:
host: scirs2-core
subset: standard
weight: 100
---
apiVersion: networking.istio.io/v1alpha3
kind: DestinationRule
metadata:
name: scirs2-core
namespace: scirs2
spec:
host: scirs2-core
subsets:
- name: high-priority
labels:
tier: high-priority
trafficPolicy:
connectionPool:
tcp:
maxConnections: 100
http:
http1MaxPendingRequests: 10
maxRequestsPerConnection: 2
- name: standard
labels:
tier: standard
trafficPolicy:
connectionPool:
tcp:
maxConnections: 50
```
### Serverless Deployment
```rust
// AWS Lambda function for serverless SciRS2
use scirs2_core::serverless::{LambdaHandler, ServerlessConfig};
use lambda_runtime::{service_fn, Error, LambdaEvent};
// Configure serverless mode
let serverless_config = ServerlessConfig::new()
.with_cold_start_optimization(true)
.with_memory_preallocation(true)
.with_function_timeout(Duration::from_secs(900)); // 15 minutes
// Lambda handler
#[tokio::main]
async fn main() -> Result<(), Error> {
let handler = LambdaHandler::new(serverless_config);
lambda_runtime::run(service_fn(|event: LambdaEvent<serde_json::Value>| async move {
handler.process_event(event).await
})).await
}
// Serverless computation
impl LambdaHandler {
async fn process_event(&self, event: LambdaEvent<serde_json::Value>) -> Result<serde_json::Value, Error> {
// Parse input data
let input_data: ComputationRequest = serde_json::from_value(event.payload)?;
// Execute computation
let result = scirs2_core::compute(&input_data.array, &input_data.operation)?;
// Return result
Ok(serde_json::to_value(ComputationResponse { result })?)
}
}
```
## Edge Computing
### Edge Node Architecture
```rust
use scirs2_core::edge::{EdgeNode, EdgeConfiguration};
// Configure edge computing node
let edge_config = EdgeConfiguration::new()
.with_local_compute_limit(4) // 4 CPU cores
.with_memory_limit_gb(8)
.with_cloud_offload_threshold(0.8) // Offload at 80% utilization
.with_latency_budget_ms(100)
.with_bandwidth_limit_mbps(100);
let edge_node = EdgeNode::new(edge_config);
// Intelligent workload distribution
edge_node.on_computation_request(|request| {
if request.estimated_complexity() > edge_config.local_compute_limit {
// Offload to cloud
EdgeDecision::OffloadToCloud
} else if request.latency_requirement() < edge_config.latency_budget_ms {
// Process locally
EdgeDecision::ProcessLocally
} else {
// Hybrid processing
EdgeDecision::HybridProcessing
}
});
```
### Edge-Cloud Hybrid
```rust
use scirs2_core::hybrid::{HybridOrchestrator, ComputationPartitioner};
// Configure hybrid edge-cloud processing
let orchestrator = HybridOrchestrator::new()
.with_edge_nodes(vec!["edge1", "edge2", "edge3"])
.with_cloud_clusters(vec!["cloud-us-east", "cloud-eu-west"])
.with_cost_optimization(true);
// Partition computation between edge and cloud
let partitioner = ComputationPartitioner::new();
let partition_plan = partitioner.partition_computation(
&computation_graph,
&orchestrator.get_available_resources()?
)?;
// Execute hybrid computation
for partition in partition_plan.partitions {
match partition.target {
ComputeTarget::Edge(node_id) => {
orchestrator.execute_on_edge(&node_id, &partition.computation)?;
},
ComputeTarget::Cloud(cluster_id) => {
orchestrator.execute_on_cloud(&cluster_id, &partition.computation)?;
}
}
}
```
## Integration Patterns
### API Gateway Integration
```rust
use scirs2_core::integration::{ApiGateway, RateLimiter, Authentication};
// Configure API gateway
let api_gateway = ApiGateway::new()
.with_rate_limiter(RateLimiter::new()
.with_requests_per_second(1000)
.with_burst_capacity(5000))
.with_authentication(Authentication::JWT {
secret: "your-jwt-secret".to_string(),
issuer: "scirs2.com".to_string(),
})
.with_request_validation(true)
.with_response_caching(true);
// Define API routes
api_gateway.route("/api/v1/compute", |request| async move {
// Validate request
let computation_request: ComputationRequest = request.validate_json()?;
// Execute computation
let result = scirs2_core::execute_computation(&computation_request).await?;
// Return response
Ok(ApiResponse::success(result))
});
```
### Message Queue Integration
```rust
use scirs2_core::integration::{MessageQueue, QueueConfig};
// Configure message queue processing
let queue_config = QueueConfig::new()
.with_queue_name("scirs2-compute-queue")
.with_batch_size(10)
.with_max_wait_time(Duration::from_secs(30))
.with_retry_policy(RetryPolicy::ExponentialBackoff {
initial_delay: Duration::from_millis(100),
max_delay: Duration::from_secs(60),
max_attempts: 3,
});
let message_queue = MessageQueue::new("kafka://kafka.scirs2.internal:9092", queue_config);
// Process messages
message_queue.consume(|messages| async move {
for message in messages {
let computation_request: ComputationRequest = serde_json::from_slice(&message.payload)?;
// Execute computation
let result = scirs2_core::execute_computation(&computation_request).await?;
// Send result to output queue
message_queue.send_result(&result, &message.reply_to).await?;
}
Ok(())
});
```
### Database Integration
```rust
use scirs2_core::integration::{DatabaseConnector, QueryOptimizer};
// Configure database integration
let db_connector = DatabaseConnector::new("postgresql://scirs2:password@db.scirs2.internal/scirs2")
.with_connection_pool_size(10)
.with_query_timeout(Duration::from_secs(30))
.with_read_replicas(vec!["db-replica-1", "db-replica-2"]);
// Optimized data loading
let query_optimizer = QueryOptimizer::new();
let optimized_query = query_optimizer.optimize_for_computation(
"SELECT * FROM large_dataset WHERE created_at > $1",
&computation_requirements
)?;
// Stream data for processing
let data_stream = db_connector.stream_query_results(&optimized_query)?;
let result = scirs2_core::process_stream(data_stream, |batch| {
// Process each batch
scirs2_core::compute_statistics(&batch)
}).await?;
```
## Migration Strategies
### Legacy System Migration
```rust
use scirs2_core::migration::{LegacyAdapter, MigrationPlan};
// Create adapter for legacy systems
let legacy_adapter = LegacyAdapter::new()
.with_source_system("legacy-matlab-system")
.with_data_format_conversion(true)
.with_api_translation(true);
// Define migration plan
let migration_plan = MigrationPlan::new()
.add_phase(MigrationPhase::new("assessment")
.with_duration(Duration::from_days(7))
.with_tasks(vec![
"Analyze legacy codebase",
"Identify critical functions",
"Map data dependencies",
]))
.add_phase(MigrationPhase::new("parallel_deployment")
.with_duration(Duration::from_days(30))
.with_tasks(vec![
"Deploy SciRS2 alongside legacy system",
"Implement data synchronization",
"Gradual traffic migration",
]))
.add_phase(MigrationPhase::new("validation")
.with_duration(Duration::from_days(14))
.with_tasks(vec![
"Validate computation results",
"Performance benchmarking",
"User acceptance testing",
]))
.add_phase(MigrationPhase::new("cutover")
.with_duration(Duration::from_days(3))
.with_tasks(vec![
"Final data migration",
"DNS switchover",
"Legacy system decommission",
]));
// Execute migration
migration_plan.execute_with_rollback_capability()?;
```
### Zero-Downtime Migration
```rust
use scirs2_core::migration::{ZeroDowntimeMigrator, TrafficSplitter};
// Configure zero-downtime migration
let migrator = ZeroDowntimeMigrator::new()
.with_health_checks(true)
.with_rollback_threshold(0.05) // Rollback if error rate > 5%
.with_canary_percentage(10); // Start with 10% traffic
// Configure traffic splitting
let traffic_splitter = TrafficSplitter::new()
.with_legacy_system("legacy.scirs2.internal")
.with_new_system("new.scirs2.internal")
.with_result_comparison(true);
// Gradual migration with monitoring
migrator.migrate_gradually(
traffic_splitter,
vec![10, 25, 50, 75, 100], // Traffic percentages
Duration::from_hours(24), // Time between increases
)?;
```
### Data Migration
```rust
use scirs2_core::migration::{DataMigrator, DataValidator};
// Configure data migration
let data_migrator = DataMigrator::new()
.with_source("legacy-database")
.with_target("scirs2-database")
.with_batch_size(10000)
.with_validation(true)
.with_checkpoint_interval(Duration::from_minutes(10));
// Validate data integrity
let data_validator = DataValidator::new()
.with_checksum_validation(true)
.with_statistical_validation(true)
.with_sample_validation(0.1); // Validate 10% of records
// Execute migration with validation
let migration_result = data_migrator.migrate_with_validation(
&data_validator,
|progress| {
println!("Migration progress: {:.1}%", progress.percentage_complete);
}
)?;
println!("Migration completed: {} records migrated", migration_result.records_migrated);
println!("Validation errors: {}", migration_result.validation_errors.len());
```
---
**Version**: SciRS2 Core 1.0
**Last Updated**: 2025-06-29
**Authors**: SciRS2 Architecture Team
**License**: See LICENSE file for details