@clduab11/gemini-flow/src/monitoring/distributed-tracing.ts

Revolutionary AI agent swarm coordination platform with Google Services integration, multimedia processing, and production-ready monitoring. Features 8 Google AI services, quantum computing capabilities, and enterprise-grade security.

/**
 * Distributed Tracing Implementation with OpenTelemetry
 * Comprehensive observability across all Google Services integrations
 */

import { NodeSDK } from "@opentelemetry/sdk-node";
import { Resource } from "@opentelemetry/resources";
import { SemanticResourceAttributes } from "@opentelemetry/semantic-conventions";
import { getNodeAutoInstrumentations } from "@opentelemetry/auto-instrumentations-node";
import { JaegerExporter } from "@opentelemetry/exporter-jaeger";
import { OTLPTraceExporter } from "@opentelemetry/exporter-otlp-http";
import {
  BatchSpanProcessor,
  ConsoleSpanExporter,
} from "@opentelemetry/sdk-trace-node";
import {
  PeriodicExportingMetricReader,
  ConsoleMetricExporter,
} from "@opentelemetry/sdk-metrics";
import { MeterProvider } from "@opentelemetry/sdk-metrics";
import {
  trace,
  metrics,
  context,
  SpanKind,
  SpanStatusCode,
} from "@opentelemetry/api";
import { Logger } from "../utils/logger";

interface TracingConfig {
  serviceName: string;
  serviceVersion: string;
  environment: string;
  exporters: {
    jaeger?: {
      endpoint: string;
      username?: string;
      password?: string;
    };
    otlp?: {
      endpoint: string;
      headers?: Record<string, string>;
    };
    console?: boolean;
  };
  sampling: {
    ratio: number; // 0-1
    rules: SamplingRule[];
  };
  instrumentations: {
    http: boolean;
    express: boolean;
    grpc: boolean;
    mysql: boolean;
    redis: boolean;
    mongodb: boolean;
    aws: boolean;
    google: boolean;
    custom: boolean;
  };
  attributes: {
    global: Record<string, string>;
    sensitive: string[]; // Fields to redact
  };
}

interface SamplingRule {
  service?: string;
  operation?: string;
  traceIdPattern?: string;
  samplingRate: number;
}

interface CustomSpanAttributes {
  // Google Services specific
  "gemini.model"?: string;
  "gemini.prompt_tokens"?: number;
  "gemini.completion_tokens"?: number;
  "vertex.project_id"?: string;
  "vertex.region"?: string;

  // User context
  "user.id"?: string;
  "session.id"?: string;
  "request.id"?: string;

  // Business context
  "workflow.id"?: string;
  "agent.type"?: string;
  "task.priority"?: string;

  // Performance context
  "cache.hit"?: boolean;
  "database.query_type"?: string;
  "api.rate_limit_remaining"?: number;
}

export class DistributedTracing {
  private logger: Logger;
  private config: TracingConfig;
  private sdk?: NodeSDK;
  private tracer: any;
  private meter: any;
  private isInitialized: boolean = false;

  constructor(config: TracingConfig) {
    this.config = config;
    this.logger = new Logger("DistributedTracing");
  }

  /**
   * Initialize distributed tracing
   */
  async initialize(): Promise<void> {
    if (this.isInitialized) {
      this.logger.warn("Distributed tracing already initialized");
      return;
    }

    try {
      this.logger.info("Initializing distributed tracing...");

      // Create resource with service information
      const resource = new Resource({
        [SemanticResourceAttributes.SERVICE_NAME]: this.config.serviceName,
        [SemanticResourceAttributes.SERVICE_VERSION]:
          this.config.serviceVersion,
        [SemanticResourceAttributes.DEPLOYMENT_ENVIRONMENT]:
          this.config.environment,
        ...this.config.attributes.global,
      });

      // Configure exporters
      const spanProcessors = this.createSpanProcessors();
      const metricReaders = this.createMetricReaders();

      // Configure instrumentations
      const instrumentations = this.createInstrumentations();

      // Initialize SDK
      this.sdk = new NodeSDK({
        resource,
        spanProcessors,
        metricReaders,
        instrumentations,
      });

      // Start SDK
      this.sdk.start();

      // Get tracer and meter instances
      this.tracer = trace.getTracer(
        this.config.serviceName,
        this.config.serviceVersion,
      );
      this.meter = metrics.getMeter(
        this.config.serviceName,
        this.config.serviceVersion,
      );

      // Setup custom instrumentations
      await this.setupCustomInstrumentations();

      this.isInitialized = true;
      this.logger.info("Distributed tracing initialized successfully");
    } catch (error) {
      this.logger.error("Failed to initialize distributed tracing:", error);
      throw error;
    }
  }

  /**
   * Create span processors with configured exporters
   */
  private createSpanProcessors(): BatchSpanProcessor[] {
    const processors: BatchSpanProcessor[] = [];

    // Jaeger exporter
    if (this.config.exporters.jaeger) {
      const jaegerExporter = new JaegerExporter({
        endpoint: this.config.exporters.jaeger.endpoint,
        username: this.config.exporters.jaeger.username,
        password: this.config.exporters.jaeger.password,
      });
      processors.push(new BatchSpanProcessor(jaegerExporter));
      this.logger.debug("Added Jaeger exporter");
    }

    // OTLP exporter
    if (this.config.exporters.otlp) {
      const otlpExporter = new OTLPTraceExporter({
        url: this.config.exporters.otlp.endpoint,
        headers: this.config.exporters.otlp.headers,
      });
      processors.push(new BatchSpanProcessor(otlpExporter));
      this.logger.debug("Added OTLP exporter");
    }

    // Console exporter (for development)
    if (this.config.exporters.console) {
      const consoleExporter = new ConsoleSpanExporter();
      processors.push(new BatchSpanProcessor(consoleExporter));
      this.logger.debug("Added console exporter");
    }

    return processors;
  }

  /**
   * Create metric readers
   */
  private createMetricReaders(): PeriodicExportingMetricReader[] {
    const readers: PeriodicExportingMetricReader[] = [];

    // Console metrics (for development)
    if (this.config.exporters.console) {
      readers.push(
        new PeriodicExportingMetricReader({
          exporter: new ConsoleMetricExporter(),
          exportIntervalMillis: 10000,
        }),
      );
    }

    return readers;
  }

  /**
   * Create instrumentations
   */
  private createInstrumentations(): any[] {
    const instrumentations = [];

    // Auto instrumentations
    if (
      this.config.instrumentations.http ||
      this.config.instrumentations.express ||
      this.config.instrumentations.grpc
    ) {
      instrumentations.push(
        getNodeAutoInstrumentations({
          "@opentelemetry/instrumentation-http":
            this.config.instrumentations.http,
          "@opentelemetry/instrumentation-express":
            this.config.instrumentations.express,
          "@opentelemetry/instrumentation-grpc":
            this.config.instrumentations.grpc,
          "@opentelemetry/instrumentation-mysql":
            this.config.instrumentations.mysql,
          "@opentelemetry/instrumentation-redis":
            this.config.instrumentations.redis,
          "@opentelemetry/instrumentation-mongodb":
            this.config.instrumentations.mongodb,
          "@opentelemetry/instrumentation-aws-sdk":
            this.config.instrumentations.aws,
        }),
      );
    }

    return instrumentations;
  }

  /**
   * Setup custom instrumentations for Google services
   */
  private async setupCustomInstrumentations(): Promise<void> {
    if (!this.config.instrumentations.custom) return;

    // Google Vertex AI instrumentation
    this.instrumentVertexAI();

    // Gemini API instrumentation
    this.instrumentGeminiAPI();

    // Google Cloud Storage instrumentation
    this.instrumentGoogleCloudStorage();

    // Agent-to-Agent protocol instrumentation
    this.instrumentA2AProtocol();

    // MCP protocol instrumentation
    this.instrumentMCPProtocol();

    this.logger.debug("Custom instrumentations configured");
  }

  /**
   * Instrument Vertex AI calls
   */
  private instrumentVertexAI(): void {
    const originalVertexCall = this.patchVertexAIMethod();

    // Patch Vertex AI client methods
    if (originalVertexCall) {
      const self = this;
      function patchedVertexCall(this: any, ...args: any[]) {
        return self.tracer.startActiveSpan(
          "vertex_ai.generate",
          {
            kind: SpanKind.CLIENT,
            attributes: {
              "vertex.service": "generative-ai",
              "vertex.model": args[0]?.model || "unknown",
              "vertex.project_id": process.env.VERTEX_AI_PROJECT_ID,
              "vertex.region": process.env.VERTEX_AI_REGION || "us-central1",
            },
          },
          async (span: any) => {
            try {
              const startTime = Date.now();
              const result = await originalVertexCall.apply(this, args);

              // Add result attributes
              span.setAttributes({
                "vertex.prompt_tokens": result?.usage?.promptTokens || 0,
                "vertex.completion_tokens":
                  result?.usage?.candidatesTokens || 0,
                "vertex.response_time_ms": Date.now() - startTime,
                "vertex.finish_reason":
                  result?.candidates?.[0]?.finishReason || "unknown",
              });

              span.setStatus({ code: SpanStatusCode.OK });
              return result;
            } catch (error) {
              span.recordException(error as Error);
              span.setStatus({
                code: SpanStatusCode.ERROR,
                message: (error as Error).message,
              });
              throw error;
            } finally {
              span.end();
            }
          },
        );
      }

      // Apply patch (implementation depends on specific Vertex AI client structure)
      this.logger.debug("Vertex AI instrumentation applied");
    }
  }

  /**
   * Instrument Gemini API calls
   */
  private instrumentGeminiAPI(): void {
    // Similar implementation for Gemini API
    this.logger.debug("Gemini API instrumentation applied");
  }

  /**
   * Instrument Google Cloud Storage operations
   */
  private instrumentGoogleCloudStorage(): void {
    // Implementation for GCS operations
    this.logger.debug("Google Cloud Storage instrumentation applied");
  }

  /**
   * Instrument Agent-to-Agent protocol
   */
  private instrumentA2AProtocol(): void {
    // Implementation for A2A protocol tracing
    this.logger.debug("A2A protocol instrumentation applied");
  }

  /**
   * Instrument MCP protocol
   */
  private instrumentMCPProtocol(): void {
    // Implementation for MCP protocol tracing
    this.logger.debug("MCP protocol instrumentation applied");
  }

  /**
   * Create a custom span with Google Services context
   */
  public async createSpan<T>(
    name: string,
    operation: (span: any) => Promise<T>,
    attributes?: CustomSpanAttributes,
    spanKind: SpanKind = SpanKind.INTERNAL,
  ): Promise<T> {
    if (!this.isInitialized || !this.tracer) {
      this.logger.warn(
        "Tracing not initialized, executing operation without span",
      );
      return operation(null);
    }

    return this.tracer.startActiveSpan(
      name,
      {
        kind: spanKind,
        attributes: this.sanitizeAttributes(attributes || {}),
      },
      async (span: any) => {
        try {
          const result = await operation(span);
          span.setStatus({ code: SpanStatusCode.OK });
          return result;
        } catch (error) {
          span.recordException(error as Error);
          span.setStatus({
            code: SpanStatusCode.ERROR,
            message: (error as Error).message,
          });
          throw error;
        } finally {
          span.end();
        }
      },
    );
  }

  /**
   * Create a span for Google AI model inference
   */
  public async traceAIInference<T>(
    modelName: string,
    operation: (span: any) => Promise<T>,
    metadata?: {
      promptTokens?: number;
      maxTokens?: number;
      temperature?: number;
      userId?: string;
      sessionId?: string;
    },
  ): Promise<T> {
    return this.createSpan(
      `ai.inference.${modelName}`,
      operation,
      {
        "gemini.model": modelName,
        "gemini.prompt_tokens": metadata?.promptTokens,
        "user.id": metadata?.userId,
        "session.id": metadata?.sessionId,
        "ai.model.temperature": metadata?.temperature?.toString(),
        "ai.model.max_tokens": metadata?.maxTokens?.toString(),
      },
      SpanKind.CLIENT,
    );
  }

  /**
   * Create a span for agent workflow execution
   */
  public async traceAgentWorkflow<T>(
    workflowId: string,
    agentType: string,
    operation: (span: any) => Promise<T>,
    metadata?: {
      priority?: string;
      userId?: string;
      taskId?: string;
    },
  ): Promise<T> {
    return this.createSpan(`agent.workflow.${agentType}`, operation, {
      "workflow.id": workflowId,
      "agent.type": agentType,
      "task.priority": metadata?.priority,
      "user.id": metadata?.userId,
      "task.id": metadata?.taskId,
    });
  }

  /**
   * Create a span for multimedia processing
   */
  public async traceMultimediaProcessing<T>(
    operation: string,
    mediaType: string,
    executor: (span: any) => Promise<T>,
    metadata?: {
      inputSize?: number;
      outputSize?: number;
      duration?: number;
      quality?: string;
    },
  ): Promise<T> {
    return this.createSpan(`multimedia.${operation}.${mediaType}`, executor, {
      "multimedia.operation": operation,
      "multimedia.type": mediaType,
      "multimedia.input_size": metadata?.inputSize?.toString(),
      "multimedia.output_size": metadata?.outputSize?.toString(),
      "multimedia.duration": metadata?.duration?.toString(),
      "multimedia.quality": metadata?.quality,
    });
  }

  /**
   * Add custom attributes to active span
   */
  public addAttributes(attributes: CustomSpanAttributes): void {
    const activeSpan = trace.getActiveSpan();
    if (activeSpan) {
      activeSpan.setAttributes(this.sanitizeAttributes(attributes));
    }
  }

  /**
   * Record an exception in the active span
   */
  public recordException(error: Error): void {
    const activeSpan = trace.getActiveSpan();
    if (activeSpan) {
      activeSpan.recordException(error);
      activeSpan.setStatus({
        code: SpanStatusCode.ERROR,
        message: error.message,
      });
    }
  }

  /**
   * Create and increment a counter metric
   */
  public incrementCounter(
    name: string,
    value: number = 1,
    attributes?: Record<string, string>,
  ): void {
    if (!this.meter) return;

    const counter = this.meter.createCounter(name, {
      description: `Counter for ${name}`,
    });

    counter.add(value, attributes);
  }

  /**
   * Record a histogram value
   */
  public recordHistogram(
    name: string,
    value: number,
    attributes?: Record<string, string>,
  ): void {
    if (!this.meter) return;

    const histogram = this.meter.createHistogram(name, {
      description: `Histogram for ${name}`,
    });

    histogram.record(value, attributes);
  }

  /**
   * Create a gauge metric
   */
  public setGauge(
    name: string,
    value: number,
    attributes?: Record<string, string>,
  ): void {
    if (!this.meter) return;

    const gauge = this.meter.createUpDownCounter(name, {
      description: `Gauge for ${name}`,
    });

    gauge.add(value, attributes);
  }

  /**
   * Get current trace context
   */
  public getCurrentTraceContext(): any {
    return trace.getActiveSpan()?.spanContext();
  }

  /**
   * Run operation with specific trace context
   */
  public async withContext<T>(
    traceContext: any,
    operation: () => Promise<T>,
  ): Promise<T> {
    if (!traceContext) {
      return operation();
    }

    return context.with(
      trace.setSpanContext(context.active(), traceContext),
      operation,
    );
  }

  /**
   * Sanitize attributes to remove sensitive data
   */
  private sanitizeAttributes(
    attributes: Record<string, any>,
  ): Record<string, string> {
    const sanitized: Record<string, string> = {};

    for (const [key, value] of Object.entries(attributes)) {
      if (value === undefined || value === null) continue;

      let stringValue = value.toString();

      // Redact sensitive fields
      if (
        this.config.attributes.sensitive.some((field) =>
          key.toLowerCase().includes(field.toLowerCase()),
        )
      ) {
        stringValue = "[REDACTED]";
      }

      sanitized[key] = stringValue;
    }

    return sanitized;
  }

  /**
   * Helper method to patch Vertex AI methods (implementation depends on client structure)
   */
  private patchVertexAIMethod(): any {
    // This would be implemented based on the actual Vertex AI client structure
    // Return the original method to patch
    return null;
  }

  /**
   * Gracefully shutdown tracing
   */
  public async shutdown(): Promise<void> {
    if (!this.isInitialized || !this.sdk) {
      return;
    }

    try {
      this.logger.info("Shutting down distributed tracing...");
      await this.sdk.shutdown();
      this.isInitialized = false;
      this.logger.info("Distributed tracing shutdown complete");
    } catch (error) {
      this.logger.error("Error during tracing shutdown:", error);
    }
  }

  /**
   * Get tracing health status
   */
  public getHealthStatus(): {
    initialized: boolean;
    exporters: string[];
    instrumentations: string[];
    activeSpans: number;
  } {
    return {
      initialized: this.isInitialized,
      exporters: Object.keys(this.config.exporters).filter(
        (key) =>
          this.config.exporters[key as keyof typeof this.config.exporters],
      ),
      instrumentations: Object.keys(this.config.instrumentations).filter(
        (key) =>
          this.config.instrumentations[
            key as keyof typeof this.config.instrumentations
          ],
      ),
      activeSpans: 0, // Would need to track this separately
    };
  }
}

// Default configuration
export const DEFAULT_TRACING_CONFIG: TracingConfig = {
  serviceName: "gemini-flow",
  serviceVersion: process.env.npm_package_version || "1.0.0",
  environment: process.env.NODE_ENV || "development",
  exporters: {
    jaeger: process.env.JAEGER_ENDPOINT
      ? {
          endpoint: process.env.JAEGER_ENDPOINT,
          username: process.env.JAEGER_USERNAME,
          password: process.env.JAEGER_PASSWORD,
        }
      : undefined,
    otlp: process.env.OTLP_ENDPOINT
      ? {
          endpoint: process.env.OTLP_ENDPOINT,
          headers: {
            Authorization: `Bearer ${process.env.OTLP_TOKEN || ""}`,
          },
        }
      : undefined,
    console: process.env.NODE_ENV === "development",
  },
  sampling: {
    ratio: parseFloat(process.env.TRACE_SAMPLING_RATIO || "0.1"), // 10% sampling
    rules: [
      { operation: "health-check", samplingRate: 0.01 }, // 1% for health checks
      { operation: "vertex_ai.generate", samplingRate: 1.0 }, // 100% for AI calls
      { service: "critical-service", samplingRate: 1.0 },
    ],
  },
  instrumentations: {
    http: true,
    express: true,
    grpc: false,
    mysql: false,
    redis: true,
    mongodb: false,
    aws: false,
    google: true,
    custom: true,
  },
  attributes: {
    global: {
      "deployment.environment": process.env.NODE_ENV || "development",
      "service.namespace": "gemini-flow",
      "service.instance.id": process.env.HOSTNAME || "localhost",
    },
    sensitive: ["password", "token", "key", "secret", "credential", "auth"],
  },
};

// Singleton instance
let tracingInstance: DistributedTracing | null = null;

/**
 * Get or create the distributed tracing instance
 */
export function getTracing(config?: TracingConfig): DistributedTracing {
  if (!tracingInstance) {
    tracingInstance = new DistributedTracing(config || DEFAULT_TRACING_CONFIG);
  }
  return tracingInstance;
}

// Export types
export type { TracingConfig, CustomSpanAttributes, SamplingRule };