orchestration-design.md

Orchestration Service - Design Document

Version: 1.0 Date: 2025-12-30 Status: Implementation in Progress

Overview

The Orchestration Service is the central coordinator for concurrent operations in DotNetDevMCP. It manages parallel task execution, resource allocation, and complex multi-step workflows while ensuring optimal performance and preventing resource exhaustion.

Architecture

Component Hierarchy

OrchestrationService (Main Coordinator)
├── ResourceManager (Resource Allocation & Throttling)
├── ConcurrentExecutor (Parallel Task Execution)
└── WorkflowEngine (Multi-Step Workflow Management)

Components

1. ResourceManager

Responsibility: Manage system resources and prevent exhaustion

Features:

• Configurable concurrency limits
• Semaphore-based throttling
• Resource pooling (e.g., Roslyn workspaces)
• Metrics collection

Interface:

public interface IResourceManager
{
    int MaxConcurrency { get; set; }
    int CurrentlyExecuting { get; }
    int QueuedOperations { get; }

    Task<T> ExecuteWithThrottlingAsync<T>(
        Func<Task<T>> operation,
        CancellationToken cancellationToken = default);

    Task<IEnumerable<T>> ExecuteBatchWithThrottlingAsync<T>(
        IEnumerable<Func<Task<T>>> operations,
        CancellationToken cancellationToken = default);

    ResourceMetrics GetMetrics();
}

public record ResourceMetrics(
    int MaxConcurrency,
    int CurrentlyExecuting,
    int TotalExecuted,
    int TotalFailed,
    TimeSpan AverageExecutionTime);

Implementation Strategy:

• Use SemaphoreSlim for throttling
• Track execution metrics
• Support dynamic concurrency adjustment
• Graceful degradation under load

2. ConcurrentExecutor

Responsibility: Execute multiple operations in parallel

Features:

• Parallel task execution with Task.WhenAll
• Configurable degree of parallelism
• Error aggregation
• Partial success handling
• Progress reporting

Interface:

public interface IConcurrentExecutor
{
    Task<ConcurrentExecutionResult<T>> ExecuteAsync<T>(
        IEnumerable<Func<CancellationToken, Task<T>>> operations,
        ConcurrentExecutionOptions options,
        CancellationToken cancellationToken = default);

    Task<ConcurrentExecutionResult<T>> ExecuteAsync<T>(
        IEnumerable<Func<CancellationToken, Task<T>>> operations,
        IProgress<ExecutionProgress>? progress = null,
        CancellationToken cancellationToken = default);
}

public record ConcurrentExecutionOptions(
    int? MaxDegreeOfParallelism = null,
    bool ContinueOnError = true,
    TimeSpan? OperationTimeout = null);

public record ConcurrentExecutionResult<T>(
    IEnumerable<T> SuccessfulResults,
    IEnumerable<ExecutionError> Errors,
    int TotalOperations,
    int SuccessfulOperations,
    TimeSpan Duration);

public record ExecutionError(
    int OperationIndex,
    Exception Exception,
    string Message);

public record ExecutionProgress(
    int TotalOperations,
    int CompletedOperations,
    int FailedOperations,
    double PercentComplete);

Implementation Strategy:

• Use Parallel.ForEachAsync for CPU-bound operations
• Use Task.WhenAll for I/O-bound operations
• Collect errors without stopping execution (if ContinueOnError = true)
• Report progress via IProgress<T>

3. WorkflowEngine

Responsibility: Execute complex multi-step workflows with dependencies

Features:

• Sequential and parallel step execution
• Step dependency management
• Conditional execution
• Workflow state management
• Rollback support

Interface:

public interface IWorkflowEngine
{
    Task<WorkflowExecutionResult> ExecuteAsync(
        IWorkflow workflow,
        CancellationToken cancellationToken = default);

    Task<WorkflowExecutionResult> ExecuteAsync(
        IWorkflow workflow,
        IProgress<WorkflowProgress>? progress = null,
        CancellationToken cancellationToken = default);
}

public interface IWorkflow
{
    string Name { get; }
    IEnumerable<IWorkflowStep> Steps { get; }
}

public interface IWorkflowStep
{
    string Name { get; }
    bool CanExecuteInParallel { get; }
    IEnumerable<string> DependsOn { get; } // Step names this depends on

    Task<StepResult> ExecuteAsync(
        WorkflowContext context,
        CancellationToken cancellationToken = default);
}

public class WorkflowContext
{
    public Dictionary<string, object> State { get; } = new();

    public void Set<T>(string key, T value);
    public T? Get<T>(string key);
    public bool TryGet<T>(string key, out T? value);
}

public record WorkflowExecutionResult(
    bool IsSuccess,
    IEnumerable<StepExecutionResult> StepResults,
    WorkflowContext FinalContext,
    TimeSpan Duration);

public record StepExecutionResult(
    string StepName,
    bool IsSuccess,
    string? Error,
    TimeSpan Duration);

public record WorkflowProgress(
    int TotalSteps,
    int CompletedSteps,
    string? CurrentStepName);

Implementation Strategy:

• Build dependency graph
• Topological sort for execution order
• Execute independent steps in parallel
• Pass context between steps
• Support conditional execution based on previous step results

4. OrchestrationService

Responsibility: High-level coordinator that uses all components

Features:

• Delegates to appropriate component (Executor, WorkflowEngine)
• Tool discovery and invocation
• Result aggregation
• Error handling and retry logic

Implementation:

public class OrchestrationService : IOrchestrationService
{
    private readonly IResourceManager _resourceManager;
    private readonly IConcurrentExecutor _concurrentExecutor;
    private readonly IWorkflowEngine _workflowEngine;
    private readonly IServiceProvider _serviceProvider;

    public IResourceManager ResourceManager => _resourceManager;

    public async Task<IEnumerable<ToolResult>> ExecuteParallelAsync(
        IEnumerable<(string toolName, string arguments)> operations,
        CancellationToken cancellationToken = default)
    {
        // Resolve tools, execute in parallel, aggregate results
    }

    public async Task<ToolResult> ExecuteWorkflowAsync(
        IWorkflow workflow,
        CancellationToken cancellationToken = default)
    {
        // Delegate to workflow engine
    }
}

Concurrency Patterns

Pattern 1: Simple Parallel Execution

var operations = projects.Select(p =>
    (token) => testExecutor.RunTestsAsync(p, token));

var result = await concurrentExecutor.ExecuteAsync(
    operations,
    new ConcurrentExecutionOptions { MaxDegreeOfParallelism = 4 },
    cancellationToken);

Pattern 2: Throttled Resource Access

var tasks = files.Select(async file =>
{
    return await resourceManager.ExecuteWithThrottlingAsync(
        async () => await analyzeFileAsync(file),
        cancellationToken);
});

var results = await Task.WhenAll(tasks);

Pattern 3: Complex Workflow

var workflow = new Workflow("BuildAndTest")
    .AddStep("RestoreDependencies", canParallel: false)
    .AddStep("BuildProjects", canParallel: true, dependsOn: "RestoreDependencies")
    .AddStep("RunUnitTests", canParallel: true, dependsOn: "BuildProjects")
    .AddStep("RunIntegrationTests", canParallel: true, dependsOn: "BuildProjects")
    .AddStep("GenerateReport", canParallel: false,
        dependsOn: new[] { "RunUnitTests", "RunIntegrationTests" });

var result = await workflowEngine.ExecuteAsync(workflow);

Performance Characteristics

Expected Performance

Scenario	Sequential	Concurrent	Improvement
4 test projects	40s	12s	70% faster
100 file analysis	100s	25s	75% faster
3-step workflow	30s	15s	50% faster

Resource Usage

• Memory: ~100MB overhead for orchestration
• CPU: Scales with MaxDegreeOfParallelism
• Threads: Uses thread pool efficiently

Error Handling

Strategies

1. Fail Fast: Stop on first error (default for workflows)
2. Continue on Error: Collect all errors (default for parallel execution)
3. Retry: Configurable retry with exponential backoff
4. Partial Success: Return successful results even if some fail

Example

try
{
    var result = await orchestrationService.ExecuteParallelAsync(operations);

    if (result.Errors.Any())
    {
        logger.LogWarning($"Completed with {result.Errors.Count()} errors");
        foreach (var error in result.Errors)
        {
            logger.LogError(error.Exception, error.Message);
        }
    }

    return result.SuccessfulResults;
}
catch (OperationCanceledException)
{
    logger.LogInformation("Operation cancelled by user");
    throw;
}
catch (Exception ex)
{
    logger.LogError(ex, "Orchestration failed");
    throw new OrchestrationException("Failed to execute operations", ex);
}

Testing Strategy

Unit Tests

• Test each component in isolation
• Mock dependencies
• Test error conditions
• Test cancellation

Integration Tests

• Test components working together
• Test realistic scenarios (test execution, file analysis)
• Test performance under load
• Test resource exhaustion scenarios

Performance Tests

• Benchmark parallel vs sequential
• Measure overhead of orchestration
• Test scalability (10, 100, 1000 operations)

Implementation Phases

Phase 1: ResourceManager (TDD)

1. Write tests for basic throttling
2. Implement with SemaphoreSlim
3. Add metrics collection
4. Test under load

Phase 2: ConcurrentExecutor (TDD)

1. Write tests for parallel execution
2. Implement with Task.WhenAll
3. Add error aggregation
4. Add progress reporting

Phase 3: WorkflowEngine (TDD)

1. Write tests for dependency resolution
2. Implement workflow graph
3. Add parallel step execution
4. Add context passing

Phase 4: OrchestrationService

1. Write integration tests
2. Implement coordinator
3. Add tool resolution
4. Add result aggregation

Phase 5: Optimization & Polish

1. Performance benchmarks
2. Memory profiling
3. Thread pool tuning
4. Documentation and examples

Configuration

{
  "Orchestration": {
    "MaxConcurrency": 8,
    "DefaultTimeout": "00:05:00",
    "EnableMetrics": true,
    "RetryPolicy": {
      "MaxRetries": 3,
      "InitialDelay": "00:00:01",
      "BackoffMultiplier": 2.0
    }
  }
}

Monitoring

Metrics to Track

• Operations per second
• Average execution time
• Success/failure ratio
• Resource utilization (CPU, memory, threads)
• Queue depth
• Throttling events

Logging

logger.LogInformation(
    "Executing {OperationCount} operations with max concurrency {MaxConcurrency}",
    operations.Count(),
    resourceManager.MaxConcurrency);

logger.LogInformation(
    "Execution completed: {Success} succeeded, {Failed} failed in {Duration}",
    result.SuccessfulOperations,
    result.Errors.Count(),
    result.Duration);

Future Enhancements

1. Distributed Orchestration: Scale across multiple machines
2. Priority Queues: High-priority operations first
3. Circuit Breaker: Prevent cascading failures
4. Adaptive Concurrency: Automatically adjust based on load
5. Workflow Persistence: Save/resume long-running workflows
6. Event-Driven: React to external events

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Next: Begin TDD implementation starting with ResourceManager tests.