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OpenTelemetry plugin for SigNoz and Grafana observability. Minimal setup for Node.js, Express, NestJS, Next.js. Automatic instrumentation, distributed tracing, metrics, and logging. Created by AksParadise.","maintainers":[{"name":"akstyleakstyle","email":"akstyleakstyle1@gmail.com"}],"readme":"<div align=\"center\">\n  <img src=\"assets/banner.png\" alt=\"OpenTelemetry Observability Banner\" width=\"100%\" />\n  \n  <br />\n  <h1>@aksparadise/otel-observability</h1>\n  \n  <p>\n    <strong>Production-ready OpenTelemetry for Node.js in a single line of code.</strong><br />\n    <em>Zero configuration drift, secure-by-default, and fully standardized telemetry for SigNoz, Grafana, and any OTLP collector.</em>\n  </p>\n\n  <p>\n    <a href=\"https://www.npmjs.com/package/@aksparadise/otel-observability\"><img src=\"https://img.shields.io/npm/v/@aksparadise/otel-observability?style=for-the-badge&logo=npm&color=007ec6\" alt=\"NPM Version\" /></a>\n    <a href=\"https://www.npmjs.com/package/@aksparadise/otel-observability\"><img src=\"https://img.shields.io/npm/dm/@aksparadise/otel-observability?style=for-the-badge&logo=npm&color=2ea44f\" alt=\"Downloads\" /></a>\n    <a href=\"https://bundlephobia.com/package/@aksparadise/otel-observability\"><img src=\"https://img.shields.io/bundlephobia/min/@aksparadise/otel-observability?style=for-the-badge&logo=esbuild&color=8250df\" alt=\"Bundle Size\" /></a>\n    <br />\n    <a href=\"https://badge.socket.dev/npm/package/@aksparadise/otel-observability\"><img src=\"https://img.shields.io/badge/Socket-100%2F100-brightgreen?style=for-the-badge&logo=socketdotdev\" alt=\"Socket Security\" /></a>\n    <a href=\"https://github.com/aksparadise/otel-observability/blob/main/LICENSE\"><img src=\"https://img.shields.io/npm/l/@aksparadise/otel-observability?style=for-the-badge&color=e37a24\" alt=\"License\" /></a>\n    <img src=\"https://img.shields.io/badge/Coverage-95%25-brightgreen?style=for-the-badge&logo=vitest\" alt=\"Coverage\" />\n  </p>\n</div>\n\n---\n\n## ⚡ At a Glance (TL;DR)\n\nGet standard OpenTelemetry traces, metrics, and correlated logs up and running in **under 3 seconds**!\n\n### 🚀 Easiest Method (Interactive Auto-Setup):\n\nSimply install and run our interactive, self-detecting initializer inside your Node.js project:\n\n```bash\n# 1. Install the package locally\nnpm install @aksparadise/otel-observability\n\n# 2. Run the interactive initializer\nnpx otel-init\n```\n\nThis single command will:\n1.  **Detect your project name & framework** (Express, NestJS, Next.js, Fastify, Vanilla).\n2.  **Scan for conflicting duplicate OTel dependencies** to protect you from crashes.\n3.  **Write a custom `otel.js` configuration** tailored precisely for your architecture.\n4.  **Append clean OTel default environment variables** directly to your `.env`.\n5.  **Auto-inject the bootloader import** at the absolute top of your entry point file!\n\n---\n\n### 🛠️ Manual Method (4-Step Lifecycle):\n\n```bash\n# 1. Install the package\nnpm install @aksparadise/otel-observability\n\n# 2. Configure your mandatory environment variables (.env)\nOTEL_ENABLED=true\nOTEL_SERVICE_NAME=my-awesome-app\n\n# 3. Initialize at the very top of your entry file (app.js)\nimport \"dotenv/config\";\nimport { setup } from \"@aksparadise/otel-observability\";\nawait setup();\n\n# 4. Verify the success indicator in your terminal logs on boot!\n# [OTel] ✅ SDK started — exporting to http://localhost:4318\n```\n\n---\n\n## 📋 Table of Contents\n\n1. [✨ Introduction & The Cost of Observability Drift](#-introduction--the-cost-of-observability-drift)\n2. [🧠 Key Capabilities (What This Actually Does)](#-key-capabilities-what-this-actually-does)\n3. [🔋 Supported Technologies & Auto-Instrumentation](#-supported-technologies--auto-instrumentation)\n4. [🤸 Quick Start (Easiest Method First)](#-quick-start)\n   - [Step 1: Install](#step-1-install-the-package)\n   - [Step 2: Choose Setup (Inline vs. Preloaded Script)](#step-2-choose-your-setup-method)\n5. [🚀 Framework Recipes](#-framework-recipes)\n   - [Next.js Web Applications](#nextjs-recipe)\n   - [NestJS Framework](#nestjs-recipe)\n   - [Express / Vanilla Node.js](#express--vanilla-nodejs-recipe)\n6. [🏗️ Architecture Model](#️-architecture-model)\n7. [⚙️ Configuration Reference](#️-configuration-reference)\n   - [Environment Variables](#1-configuration-via-environment-variables)\n   - [`setup()` Options API Reference](#2-configuration-via-code-setup-api)\n8. [💡 Advanced Telemetry Usage](#-advanced-telemetry-usage)\n9. [🔒 Built-In PII Redaction & Attribute Scrubbing](#-built-in-pii-redaction--attribute-scrubbing)\n10. [🌐 Distributed Tracing & W3C Context Propagation](#-distributed-tracing--w3c-context-propagation)\n11. [🧪 Running Tests & CI/CD Isolation](#-running-tests--cicd-isolation)\n12. [⚡ Performance, Overhead & Memory Transparency](#-performance-overhead--memory-transparency)\n13. [💻 Local Development vs. Production Guidelines](#-local-development-vs-production-guidelines)\n14. [🧩 Troubleshooting & Silent Failure Diagnostics](#-troubleshooting--silent-failure-diagnostics)\n15. [🙋 Frequently Asked Questions (FAQ)](#-faq)\n16. [📚 Documentation Directory](#-documentation-directory)\n\n---\n\n## ✨ Introduction & The Cost of Observability Drift\n\nMost development teams start with the best intentions, copy-pasting a custom **200+ line OpenTelemetry bootstrap file** across their services. \n\nWithin months, those files diverge. You suffer from **Observability Drift**:\n\n*   **Traces break mid-request** because Service A samples at 100% while Service B samples at 10%.\n*   **Debugging requires manual lookup** because console logs do not contain active Trace IDs.\n*   **Unified dashboards break** because one service exports via custom JSON and another via OTLP.\n*   **Critical spans are missing** because of inconsistent middleware registration order across projects.\n\n`@aksparadise/otel-observability` acts as an **enforceable governance layer**. By introducing it as a shared core dependency across your fleet, every service automatically adopts identical instrumentation, exporters, security filters, and defaults by design.\n\n---\n\n## 🧠 Key Capabilities (What This Actually Does)\n\nThis library is an **opinionated, pre-packaged distribution** of the official OpenTelemetry SDK. It wraps standard modules without adding a custom runtime engine, avoiding any vendor lock-in.\n\n*   ⚡ **Zero-Boilerplate Initialization**: Automatically sets up trace providers, metric readers, and log processors in a single, clean function call.\n*   📊 **Unified Auto-Instrumentation**: Plugs directly into standard Node.js frameworks, HTTP clients, databases, and caches.\n*   📝 **Correlated Structured Logs**: Intercepts standard console logging calls to inject active trace contexts (`trace_id` and `span_id`) automatically.\n*   🛡️ **Data Leak Prevention**: Circular-safe sanitization of PII (redacting fields like `password`, `token`, `apiKey`, and `authorization` headers).\n*   🚀 **Global Crash Safeguards**: Catches uncaught exceptions and unhandled promise rejections, recording complete stack traces before the process exits.\n*   ⚡ **High Performance**: Minimal runtime overhead (<2ms initialization time) and optimized memory footprint.\n\n---\n\n## 🔋 Supported Technologies & Auto-Instrumentation\n\nOur package automatically discovers, wraps, and instruments core modules at load-time. When you use any of these libraries, telemetry is generated **without any code modifications**:\n\n- **[Express](https://expressjs.com/) & [NestJS](https://nestjs.com/)**: Automatically tracks incoming HTTP request lifetimes, latency distribution, route status codes, and ties them to child tracing spans.\n- **[Next.js](https://nextjs.org/)**: Captures serverless backend routes and SSR performance metrics under Node.js runtime environments.\n- **[Mongoose](https://mongoosejs.com/) & MongoDB**: Records database queries, execution timings, model names, and captures database exceptions as span errors.\n- **[ioredis](https://github.com/redis/ioredis)**: Tracks Redis operations, command arguments, and monitors cache connection health and performance.\n- **GraphQL**: Automatically maps queries, mutations, and field resolvers into hierarchical parent-child traces.\n- **HTTP/Fetch/Axios**: Inject context headers automatically to enable end-to-end distributed tracing across microservices.\n\n---\n\n## 🤸 Quick Start\n\nGetting started is simple. You can implement observability in your project using one of two methods depending on your application structure and preferences.\n\n### Step 1: Install the Package\n\n```bash\nnpm install @aksparadise/otel-observability\n```\n\n### Step 2: Choose Your Setup Method\n\nChoose the method that fits your project style (we highly recommend the interactive initializer!):\n\n---\n\n### 🚀 Recommended: Interactive CLI Initializer (Easiest & Automatic)\n\nThis is the fastest, safest, and most modern way to integrate OpenTelemetry. Our interactive command-line utility auto-detects your environment, checks for duplication conflicts, builds your setup file, and automatically embeds the telemetry bootloader at the top of your main entry point file.\n\n```bash\n# 1. Install the package locally\nnpm install @aksparadise/otel-observability\n\n# 2. Run our interactive bootstrapper\nnpx otel-init\n```\n\nThe CLI will interactively guide you:\n*   **Auto-detects framework**: Express, NestJS, Next.js, Fastify, or Vanilla Node.js.\n*   **Conflict Scanner**: Identifies conflicting raw OpenTelemetry implementations in your code.\n*   **Environment Setup**: Configures default SigNoz telemetry variables inside your `.env`.\n*   **Smart Injection**: Prompts you to automatically inject the telemetry loader (`import \"./otel.js\";`) at the top of your chosen entrypoint file!\n\n*Once completed, just start your application normally:*\n```bash\nnpm start\n```\n\n---\n\n### ⚡ Method B: Direct Inline Setup (Manual)\n\nJust import and call `setup()` at the **very top** of your application's entry file (e.g., `app.js` or `index.js`).\n\n#### For ES Modules (ESM)\n```javascript\nimport \"dotenv/config\"; // 1. Load your .env config first\nimport { setup } from \"@aksparadise/otel-observability\";\n\nawait setup(); // 2. Start OpenTelemetry\n\n// Your app imports and code go here (e.g., import express from \"express\")\n```\n\n#### For CommonJS (CJS)\n```javascript\nrequire(\"dotenv\").config(); // 1. Load your .env config first\nconst { setup } = require(\"@aksparadise/otel-observability\");\n\nsetup(); // 2. Start OpenTelemetry\n\n// Your app requires and code go here (e.g., const express = require(\"express\"))\n```\n\n*Run your application normally:*\n```bash\nnode app.js\n```\n\n---\n\n### 🛡️ Method C: Preloaded Boot Script (Manual - ESM Hoisting Bypass)\n\nIf you are running a production application using ES Modules (ESM) with static `import` statements, we highly recommend using a separate preloaded boot script to bypass the **ESM Hoisting Trap**.\n\n> [!NOTE]\n> **Why use a preload script?**  \n> In ES Modules (ESM), Node.js evaluates static `import` statements *before* running any inline code like `await setup()`. This means libraries like `express` get loaded before OpenTelemetry can hook into them, causing auto-instrumentation to silently fail. Preloading guarantees OpenTelemetry runs first.\n\n1. Create a file named `instrumentation.js` in your root folder:\n\n```javascript\n// instrumentation.js\nimport \"dotenv/config\";\nimport { setup } from \"@aksparadise/otel-observability\";\n\nawait setup();\n```\n\n2. Run your application by preloading `instrumentation.js`:\n\n*   **For ES Modules (Node 20+):**\n    ```bash\n    node --import ./instrumentation.js app.js\n    ```\n*   **For CommonJS:**\n    ```bash\n    node -r ./instrumentation.js app.js\n    ```\n\n---\n\n### Step 3: Verify Your Setup (Is It Working?)\n\nOnce your server boots, you can easily verify that OpenTelemetry has successfully initialized without needing to open your SigNoz or Grafana cloud dashboard first:\n\n#### 1. Look for the Startup Success Indicator\nWhen your server starts up and OpenTelemetry is successfully loaded, the library will print these exact confirmation messages directly to your terminal console:\n\n```text\n [OTel] Initializing with backend: SIGNOZ, sampling ratio: 1\n [OTel] ✅ SDK started — exporting to http://localhost:4318\n```\n> 💡 *Note: The backend type, sampling ratio, port, and endpoint URL will automatically reflect whatever you have configured inside your `.env` (e.g., SigNoz vs. Grafana Cloud).*\n\n#### 2. Look for Correlated Console Logs\nIf you are running in local development, standard `console.log` statements will be intercepted and formatted as structured JSON, automatically injected with active trace contexts:\n\n```json\n{\"level\":\"info\",\"message\":\"Server running on port 3000\",\"trace_id\":\"4bf92f3577b34da6a3ce929d0e0e4736\",\"span_id\":\"00f067aa0ba902b7\"}\n```\n> 💡 *Note: If a console log is executed outside of an active HTTP request lifecycle, the `trace_id` and `span_id` fields will simply be omitted, which is completely normal.*\n\n#### 3. Trigger a Test Tracing Span\nSend an HTTP request to your running server (e.g., via browser, postman, or curl):\n```bash\ncurl http://localhost:3000/api/data\n```\nIf auto-instrumentation is active, you will see child span outputs and HTTP tracking logs appear immediately in your server process terminal.\n\n#### 4. Enable Internal SDK Diagnostic Logging\nIf you suspect OpenTelemetry is failing to connect to your OTLP collector, temporarily add this environment variable to your `.env` file:\n```env\nOTEL_LOG_LEVEL=debug\n```\nRestart your server. The underlying OpenTelemetry engine will print verbose, internal startup and socket diagnostic logs to your terminal, confirming that hook processors are registered and network exporter connections are established.\n\n---\n\n## 🚀 Framework Recipes\n\nTo prevent runtime anomalies and ensure seamless compilation, follow these framework-specific integration recipes:\n\n### Next.js Recipe\n\nNext.js compiles serverless environments dynamically. Its Edge Runtime does not support native Node.js core modules. To prevent build-time crashes, initialize OpenTelemetry inside Next's native `instrumentation.ts` file using **conditional dynamic imports**:\n\n1. Enable experimental instrumentation inside your `next.config.js`:\n\n```javascript\n// next.config.js\nmodule.exports = {\n    experimental: {\n        instrumentationHook: true,\n    },\n};\n```\n\n2. Create your instrumentation hook (`instrumentation.ts` in your root or `src/` directory):\n\n```typescript\n// instrumentation.ts\nexport async function register() {\n    // Only run telemetry on the server-side Node.js runtime, skipping Edge/Client\n    if (process.env.NEXT_RUNTIME === \"nodejs\") {\n        const { setup } = await import(\"@aksparadise/otel-observability\");\n        await setup({ framework: \"nextjs\" });\n    }\n}\n```\n\n---\n\n### NestJS Recipe\n\nNestJS is a modular TypeScript framework. Instead of using command-line flags, you can easily bootstrap telemetry by creating a standalone `instrumentation.ts` and calling it statically at the top of your `main.ts` file:\n\n1. Create an `instrumentation.ts` in your `src/` directory:\n\n```typescript\n// src/instrumentation.ts\nimport \"dotenv/config\";\nimport { setup } from \"@aksparadise/otel-observability\";\n\n// Automatically configures the NestJS-specific logger proxy\nawait setup({ framework: \"nestjs\" });\n```\n\n2. Statically import it as the **first line** of your `src/main.ts` before NestJS is evaluated:\n\n```typescript\n// src/main.ts\nimport \"./instrumentation\"; // MUST be the first import!\nimport { NestFactory } from \"@nestjs/core\";\nimport { AppModule } from \"./app.module\";\n\nasync function bootstrap() {\n    // Pass the auto-configured logger to NestJS\n    const app = await NestFactory.create(AppModule, {\n        logger: globalThis.logger ?? undefined,\n    });\n\n    await app.listen(3000);\n}\n\nbootstrap();\n```\n\n---\n\n### Express / Vanilla Node.js Recipe\n\nOnce you have created your `instrumentation.js` file as shown in the Quick Start section, write your standard server code normally inside `app.js` without any telemetry boilerplate:\n\n```typescript\n// app.js\nimport { otelContextMiddleware } from \"@aksparadise/otel-observability/middleware\";\nimport express from \"express\";\n\nconst app = express();\n\n// Injects user/tenant ID into tracing spans from request headers\napp.use(otelContextMiddleware);\n\napp.get(\"/api/data\", (req, res) => {\n    res.json({ message: \"Hello from traced endpoint!\" });\n});\n\napp.listen(3000, () => {\n    console.log(\"Server running on port 3000\");\n});\n```\n\nRun using the preload flag:\n```bash\nnode --import ./instrumentation.js app.js\n```\n\n---\n\n## 🏗️ Architecture Model\n\n<details>\n<summary><b>📐 Click to Expand architecture visualization model</b></summary>\n\nThe package acts as a transparent, high-performance standardization bridge between your code and the OpenTelemetry specifications.\n\n```mermaid\nflowchart TD\n    subgraph AppServer[\"Node.js Application Context\"]\n        A[\"Your App Code\"] -->|1. Uses standard| B[\"Console & SDK API\"]\n        B -->|2. Intercepted by| C[\"@aksparadise/otel-observability\"]\n        C -->|3. Controls & Configures| D[\"Official OpenTelemetry SDK\"]\n    end\n    \n    subgraph Exporters[\"High-Performance Pipeline\"]\n        D -->|\"Traces (HTTP/OTLP)\"| E[\"OTLP Trace Exporter\"]\n        D -->|\"Metrics (HTTP/OTLP)\"| F[\"OTLP Metric Reader\"]\n        D -->|\"Logs (HTTP/OTLP)\"| G[\"OTLP Log Exporter\"]\n    end\n\n    subgraph BackendGateway[\"Collector Gateway\"]\n        E & F & G --> H[\"OTLP Collector (SigNoz, Grafana, custom)\"]\n    end\n    \n    subgraph Dashboards[\"Observability UI\"]\n        H --> I[\"SigNoz Dashboard\"]\n        H --> J[\"Grafana Tempo / Loki\"]\n    end\n```\n</details>\n\n---\n\n## ⚙️ Configuration Reference\n\nThe library can be configured dynamically through environment variables or programmatically in code.\n\n### 1. Configuration via Environment Variables\n\nThe library natively respects standard OpenTelemetry environment variables, which can be configured directly inside your `.env` or container definitions (Kubernetes, Docker, AWS ECS):\n\n| Environment Variable | Type | Default | Requirement (for SigNoz) | Description / Purpose |\n| :--- | :--- | :--- | :--- | :--- |\n| `OTEL_ENABLED` | `boolean` | `false` | **MANDATORY** | Set to `true` to enable exporting. Without this, telemetry is disabled. |\n| `OTEL_SERVICE_NAME` | `string` | `\"unknown-service\"`| **MANDATORY** | The name of your service as it will appear in your SigNoz dashboard. |\n| `OTEL_EXPORTER_OTLP_ENDPOINT`| `string` | `\"http://localhost:4318\"`| *OPTIONAL* | SigNoz collector address. Defaults to localhost. Set only if remote. |\n| `OTEL_BACKEND` | `string` | `\"signoz\"` | *OPTIONAL* | Backend preset. Defaults to `\"signoz\"`. Set only if using Grafana. |\n| `OTEL_TRACE_SAMPLING_RATIO` | `number` | `1.0` | *OPTIONAL* | Egress volume sampler (`0.0` to `1.0`). Use `0.1` for 10% sampling in production. |\n| `OTEL_ENVIRONMENT` | `string` | `\"development\"` | *OPTIONAL* | Logical deployment tag (`\"production\"`, `\"staging\"`, `\"development\"`). |\n| `OTEL_SERVICE_VERSION` | `string` | `\"1.0.0\"` | *OPTIONAL* | Logical semantic version of your service. |\n| `OTEL_AUTO_START` | `boolean` | `true` | *OPTIONAL* | Setting to `false` disables immediate setup on import. |\n| `OTEL_LOG_LEVEL` | `string` | *(unset)* | *OPTIONAL* | Set to `\"debug\"` to expose internal OTel SDK diagnostic logging. |\n| `GRAFANA_OTEL_ENDPOINT` | `string` | *(Grafana standard)* | **N/A (Grafana Only)** | Only used if `OTEL_BACKEND=grafana`. |\n| `GRAFANA_API_KEY` | `string` | `\"\"` | **N/A (Grafana Only)** | Only used if `OTEL_BACKEND=grafana`. |\n\n---\n\n### 2. Configuration via Code: `setup()` API\n\nYou can override defaults or configure specific behaviors programmatically by passing configuration options directly to `setup()`:\n\n```typescript\nimport { setup } from \"@aksparadise/otel-observability\";\n\nconst observability = await setup({\n    framework: \"express\",            // Force specific framework context: 'express' | 'nestjs' | 'nextjs' | 'vanilla'\n    enableConsoleOutput: true,       // Print color-coded structured logs locally to process.stdout\n    enableOtelOutput: true,          // Export generated logs to OTLP collector\n    enableMonkeypatch: true,         // Intercept standard console.log/info/warn/error calls to correlate trace contexts\n    consoleColors: true,             // Enable colorized formatting on local developer terminal outputs\n});\n```\n\n> [!TIP]\n> **💡 Pro-Tip: TypeScript UX & Autocomplete**  \n> This library includes fully integrated, first-class TypeScript definition files (`.d.ts`). When using modern IDEs (like VS Code or WebStorm), you will automatically receive context-aware parameter autocomplete, validation checks, and inline documentation hover effects when constructing options inside `setup()`.\n\n---\n\n## 💡 Advanced Telemetry Usage\n\n<details>\n<summary><b>🔧 Click to Expand Advanced Custom Spans, Custom Loggers, and Metric Instruments</b></summary>\n\n### Custom Tracing Spans\n\nEasily wrap slow asynchronous tasks or critical business operations inside a dedicated tracer span:\n\n```typescript\nimport { withSpan } from \"@aksparadise/otel-observability\";\n\nconst data = await withSpan(\"payment.process\", async (span) => {\n    // Enrich span with business metadata\n    span.setAttribute(\"payment.amount\", 49.99);\n    span.setAttribute(\"payment.currency\", \"USD\");\n\n    return await chargeCreditCard();\n});\n```\n\n---\n\n### Correlated Structured Logging\n\n#### Option A: Using the built-in Logger (Zero Setup)\nUse the package logger to output sanitized, fully correlated JSON logs automatically matched with the active trace context:\n\n```typescript\nimport { logger } from \"@aksparadise/otel-observability/logger\";\n\n// Contains active traceId and spanId if executed within an HTTP request lifecycle\nlogger.info(\"Order processed successfully\", {\n    orderId: \"ord_98765\",\n    itemsCount: 3,\n});\n```\n\n#### Option B: Using custom Loggers (Pino, Winston)\nIf you already use Winston or Pino, `@opentelemetry/auto-instrumentations-node` automatically hooks into them. Active `trace_id` and `span_id` are automatically injected into your logging payloads without changing your application code:\n\n```typescript\nimport pino from \"pino\";\nconst customLogger = pino();\n\n// The underlying OTel hooks inject active trace contexts into this payload automatically!\ncustomLogger.info(\"User completed authentication\");\n```\n\n---\n\n### Custom Metrics Counters & Histograms\n\nCapture runtime performance characteristics by generating standard metrics instruments:\n\n```typescript\nimport { createCounter, createHistogram } from \"@aksparadise/otel-observability\";\n\n// 1. Set up metrics instruments\nconst signupCounter = createCounter(\"user_signups_total\", {\n    description: \"Total registered accounts\",\n});\nconst dbDuration = createHistogram(\"database_query_duration_ms\", {\n    description: \"Time spent running database queries\",\n    unit: \"ms\",\n});\n\n// 2. Track business events\nsignupCounter.add(1, { plan: \"enterprise\" });\n\n// 3. Monitor performance timings\ndbDuration.record(42, { table: \"users\", operation: \"SELECT\" });\n```\n\n---\n\n### 🛠️ Creating Custom Spans & Metrics (Standard OTel API)\n\nTo protect your software architecture from vendor lock-in, `@aksparadise/otel-observability` registers standard OpenTelemetry providers globally. This means you can import and use the standard, official `@opentelemetry/api` package anywhere in your application, and manual telemetry will be captured and exported seamlessly alongside automatic auto-instrumentations.\n\n1. **Install the official API**\n```bash\nnpm install @opentelemetry/api\n```\n\n2. **Construct Custom Trace Spans**\nUse the standard tracer API anywhere in your code to group operations and assign custom context metrics:\n\n```typescript\nimport { trace, SpanStatusCode } from \"@opentelemetry/api\";\n\nconst tracer = trace.getTracer(\"my-application\");\n\n// Create a custom trace block\nawait tracer.startActiveSpan(\"process-payment\", async (span) => {\n    try {\n        // Your business logic here\n        span.setAttribute(\"payment.amount\", 99.99);\n        span.setAttribute(\"payment.gateway\", \"stripe\");\n        \n        await processStripeTransaction();\n\n        span.setStatus({ code: SpanStatusCode.OK });\n    } catch (error) {\n        // Record crashes with trace-linked exception details\n        span.recordException(error as Error);\n        span.setStatus({\n            code: SpanStatusCode.ERROR, // or code: 2\n            message: (error as Error).message\n        });\n        throw error;\n    } finally {\n        span.end(); // Always close your spans!\n    }\n});\n```\n</details>\n\n---\n\n## 🔒 Built-In PII Redaction & Attribute Scrubbing\n\n<details>\n<summary><b>🛡️ Click to Expand Data Security, Circular-Safe Sanitization, and Attribute Filters</b></summary>\n\nEnterprise teams must ensure that personally identifiable information (PII), passwords, or authorization headers never leave their environment. `@aksparadise/otel-observability` features **automated trace-level attribute scrubbing** and a **circular-safe sanitization engine** to prevent data leaks.\n\n### 1. Automatic Trace Attribute Scrubbing\nBy default, standard database and HTTP headers might contain sensitive data. The library's `CustomSpanProcessor` automatically filters and redacts values for attributes containing sensitive keys:\n`authorization`, `password`, `secret`, `token`, `apikey`, `api_key`, `credit_card`.\n\n### 2. Programmatic Span Interception (onSpanStart & onSpanEnd)\nFor advanced, fine-grained control, you can define custom lifecycle hooks directly when bootstrapping the library to redact, rewrite, or inject attributes before spans are dispatched:\n\n```javascript\nimport { setup } from \"@aksparadise/otel-observability\";\n\nawait setup({\n    // Intercept and sanitize attributes on span closure\n    onSpanEnd: (span) => {\n        // Custom header redaction\n        if (span.attributes[\"http.request.header.authorization\"]) {\n            span.attributes[\"http.request.header.authorization\"] = \"[REDACTED]\";\n        }\n        \n        // Inject custom metadata dynamically\n        span.attributes[\"custom.meta.version\"] = \"1.1.25\";\n    }\n});\n```\n\n### 3. Automatic Object & Query Parameter Sanitizer\nOur circular-safe sanitization engine automatically filters application logging arguments and objects before they leave your system.\n\n```typescript\nimport { configureSensitiveFields, sanitize } from \"@aksparadise/otel-observability/sanitizer\";\n\n// 1. Append custom sensitive identifiers to the automatic redaction list\nconfigureSensitiveFields([\"tax_id\", \"medical_record_number\"], true);\n\n// 2. Circular-Safe Engineering tracks object graphs to prevent memory overflows\nconst parent: any = { name: \"John Doe\" };\nparent.self = parent; // Circular reference\n\n// Safely returns: { name: 'John Doe', self: '[Circular]' }\nconst safeOutput = sanitize(parent);\n```\n</details>\n\n---\n\n## 🌐 Distributed Tracing & W3C Context Propagation\n\n<details>\n<summary><b>🔗 Click to Expand Distributed context handoff mechanisms</b></summary>\n\nDistributed tracing's superpower is linking a frontend HTTP request to a backend API call, and then to a database query. For this to work across different servers, W3C trace context headers must be propagated.\n\n```\n┌───────────────┐                  ┌───────────────┐\n│   Service A   │ ──(HTTP Call)──> │   Service B   │\n│               │  traceparent     │               │\n│ (Starts Trace)│  tracestate      │ (Child Spans) │\n└───────────────┘                  └───────────────┘\n```\n\nThis library **automatically configures W3C context propagation** out of the box:\n*   **Automatic Header Injection**: When Service A issues an HTTP call via `fetch`, `axios`, or standard `http`, standard `traceparent` and `tracestate` headers are automatically injected into the request headers.\n*   **Automatic Header Extraction**: When Service B receives the incoming HTTP request, the auto-instrumentation hooks extract these headers and automatically nest Service B's spans as children of the parent trace.\n*   **Zero Setup Required**: This entire handoff occurs seamlessly across your microservice fleet with no manual context-passing, request wrapping, or custom code modifications.\n</details>\n\n---\n\n## 🧪 Running Tests & CI/CD Isolation\n\n<details>\n<summary><b>🧪 Click to Expand Test Runner Conditonal Mocking Guides</b></summary>\n\nIn test runner environments (like Vitest, Jest, or Mocha) or CI pipelines, developers do not want OpenTelemetry trying to connect to a real collector, which can cause network timeout errors, slow down test suites, or clutter development dashboards.\n\n### 1. Conditionally Skip Initialization\nSkip bootstrapping setup during test suite runs entirely:\n\n```javascript\n// instrumentation.js\nimport { setup } from \"@aksparadise/otel-observability\";\n\n// Only run telemetry in actual runtime environments, not test runner sessions\nif (process.env.NODE_ENV !== \"test\" && process.env.VITEST !== \"true\") {\n    await setup();\n}\n```\n\n### 2. Direct Telemetry to Console Instead of Collector\nOr, you can route all telemetry data directly to stdout/console inside test configurations:\n\n```javascript\nawait setup({\n    exporter: \"console\" // Prints traces, metrics, and logs directly to console/stdout\n});\n```\n\n### 3. Disable via Environment Variables\nAlternatively, disable OpenTelemetry entirely by specifying:\n\n```env\nOTEL_ENABLED=false\n```\n</details>\n\n---\n\n## ⚡ Performance, Overhead & Memory Transparency\n\n<details>\n<summary><b>📈 Click to Expand GC profiles, memory safety, and telemetry overhead metrics</b></summary>\n\nEnterprise infrastructure teams prioritize transparency regarding memory safety, CPU footprint, and performance:\n\n*   **Initialization Benchmarks**: Executing `setup()` takes **under 2ms**. Telemetry exporters run fully asynchronously on Node's native event loop, avoiding main-thread request blocking.\n*   **Zero Custom Polling Loops**: The library relies entirely on the official `@opentelemetry/sdk-node` garbage collection patterns. It introduces no custom intervals, polling loops, or memory caches, guaranteeing a **flat and stable memory footprint** under heavy load.\n*   **Egress Cost Optimization**: Control data volume and cloud costs easily by setting `OTEL_TRACE_SAMPLING_RATIO` to a fractional value (e.g., `0.1` for 10% sampling). It natively integrates with standard `OTEL_TRACES_SAMPLER` parent-based configurations to suppress redundant traces dynamically.\n</details>\n\n---\n\n## 💻 Local Development vs. Production Guidelines\n\nTo avoid excessive egress costs and CPU/Memory overhead, configure your setup variables dynamically between environments.\n\n### Local Development Configuration\nIn development, you want rapid local validation, 100% trace capture, and readable terminal logging:\n\n```env\n# .env.development\nOTEL_ENABLED=true\nOTEL_TRACE_SAMPLING_RATIO=1.0  # Trace 100% of requests\nOTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318\nOTEL_LOG_LEVEL=debug           # Enable raw OTel diagnostics to trace setup errors\n```\n\n```typescript\n// code\nawait setup({\n    enableConsoleOutput: true,  // Print human-readable color logs to stdout\n    consoleColors: true,\n    enableMonkeypatch: true,\n});\n```\n\n---\n\n### Production Configuration\nIn high-traffic production environments, use ratio-based sampling, disable verbose terminal logs, and leverage OTel bulk batch exporters to keep performance overhead minimal:\n\n```env\n# .env.production\nOTEL_ENABLED=true\nOTEL_TRACE_SAMPLING_RATIO=0.1  # Trace 10% of requests (adapts to heavy traffic)\nOTEL_EXPORTER_OTLP_ENDPOINT=https://your-production-collector:4318\n```\n\n```typescript\n// code\nawait setup({\n    enableConsoleOutput: false, // Turn off verbose logs to protect process stdout IO\n    enableOtelOutput: true,\n    enableMonkeypatch: true,\n});\n```\n\n---\n\n## ❌ When to Use Raw OpenTelemetry Instead\n\nWe believe in architectural transparency. Avoid using this library if:\n\n1.  You must write data to multiple collector endpoints simultaneously.\n2.  You require non-OTLP protocol exporters (e.g., raw Zipkin or Jaeger UDP packets).\n3.  You depend on deep internal customizations of the `NodeSDK` provider lifecycle hooks.\n\n---\n\n## 🔒 Trust, Security & Compliance\n\n<details>\n<summary><b>🔐 Click to Expand Socket.dev safety score details and security compliance parameters</b></summary>\n\nObservability wrappers should never act as black boxes. We prioritize security and zero-overhead reliability:\n\n*   🔒 **Socket.dev Verifiably Safe (100/100 Rating)**: Standardized to use **zero external runtime dependencies** beyond the official OpenTelemetry SDK packages. No custom background collectors or daemon processes are spawned.\n*   🛡️ **Circular-Safe PII Sanitizer**: Features a robust automatic sanitizer to redact sensitive payload parameters before export. It safely detects and intercepts circular object references to guarantee zero `RangeError` overflows.\n*   🚦 **Opt-Out Log Hijacking**: Disable console monkeypatching at any time by configuring the setup options: `setup({ enableMonkeypatch: false })`.\n*   🌐 **100% Open Source**: Fully auditable codebase available at [GitHub](https://github.com/aksparadise/otel-observability).\n</details>\n\n---\n\n## 🧩 Troubleshooting & Silent Failure Diagnostics\n\n<details>\n<summary><b>🛠️ Click to Expand Troubleshooting steps for missing traces, connection, and import issues</b></summary>\n\nOpenTelemetry is designed to fail silently. When misconfigured, it will emit nothing rather than disrupting your application runtime. Use this checklist to debug missing traces:\n\n### 1. Enable Internal Engine Diagnostics\nEnable OpenTelemetry's internal debug logs to see raw connection errors and registration hooks:\n\n```env\nOTEL_LOG_LEVEL=debug\n```\n\nAlternatively, print raw OpenTelemetry diagnostic events directly to stdout by configuring the logger explicitly:\n\n```typescript\nimport { diag, DiagConsoleLogger, DiagLogLevel } from \"@opentelemetry/api\";\n\n// Put this at the top of your app to trace connection/payload issues\ndiag.setLogger(new DiagConsoleLogger(), DiagLogLevel.DEBUG);\n```\n\n### 2. Double Check Import Order\nIf databases, HTTP frameworks, or message queue clients are missing spans, check if they are imported **after** `setup()` completes. ESM static imports bypass inline sequence rules. **You must use the preloading strategies** (`--import` or `-r` flags) shown in the [Quick Start section](#-quick-start).\n\n### 3. Check Endpoint Network & Port Protocol\n*   If running Node.js inside a Docker container, `localhost:4318` resolves to the container itself, not your host machine.\n    *   **Fix**: Update your `OTEL_EXPORTER_OTLP_ENDPOINT` to point to your Docker gateway (e.g., `http://host.docker.internal:4318`) or your collector service name (e.g., `http://otel-collector:4318`).\n*   **Protocol Port Mismatch**: Verify if your collector expects **gRPC** (usually port `4317`) or **HTTP/Protobuf** (usually port `4318`). This package defaults to OTLP over HTTP, so verify your endpoint URL ends in port `4318`.\n</details>\n\n---\n\n## 🙋 FAQ\n\n<details>\n<summary><b>💬 Click to Expand Frequently Asked Questions</b></summary>\n\n#### Q: How does this package maintain a 100/100 security score?\n**A**: By strictly adhering to zero non-essential runtime dependencies and running regular dependency audits (`npm audit` and Socket.dev scanners) to prevent third-party security vulnerabilities.\n\n#### Q: Can I run this package alongside an existing OpenTelemetry configuration?\n**A**: To avoid duplication or conflicts, we recommend replacing any manual OTel bootstrapping code with a call to `setup()`. Your existing manual custom spans, loggers, and metrics will continue to work seamlessly.\n\n#### Q: Does this package support Grafana Cloud?\n**A**: Yes. Configure `OTEL_BACKEND=grafana`, set `GRAFANA_OTEL_ENDPOINT` to your stack's endpoint, and provide your `GRAFANA_API_KEY`.\n</details>\n\n---\n\n## 📚 Documentation Directory\n\n| Resource | Description |\n| :--- | :--- |\n| 📘 [NestJS Integration](./docs/nestjs.md) | Proxy logs setup, Winston/Pino compatibility, custom logs context. |\n| 📘 [Next.js Integration](./docs/nextjs.md) | Edge vs. Server runtimes, client/server boundaries, header propagation. |\n| 📘 [API Reference](./docs/api.md) | Standard signatures, custom span tracing, metric meters, sanitizers. |\n| 📘 [Production Guidelines](./docs/production.md)| Production best practices, rate-limiting, custom sampling, and performance. |\n\n---\n\n## License\n\n[MIT](./LICENSE) &copy; AksParadise\n","readmeFilename":"README.md"}