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standard instrumentation SDK for NodeJS based project","maintainers":[{"name":"samsalvatico","email":"samuele.salvatico.social@gmail.com"},{"name":"andrea.cappadona.nearform","email":"andrea.cappadona@nearform.com"},{"name":"bozzelliandrea","email":"andrea.bozzelli@nearform.com"},{"name":"ogcio_per","email":"krzysztof.przybylak@per.gov.ie"},{"name":"tiago_ramos","email":"tiago.ramos@nearform.com"},{"name":"hamza.khan.nearform","email":"hamza.khan@nearform.com"},{"name":"matteo.lacognata","email":"matteo.lacognata@nearform.com"},{"name":"gianmarco.poggi","email":"gianmarco.poggi@nearform.com"}],"readme":"# Observability NodeJS SDK\n\nThe NodeJS observability sdk is a npm package used to setup and implement opentelemetry instrumentation.\n\n## Installation\n\npnpm\n\n```bash\npnpm i --save @ogcio/o11y-sdk-node\n```\n\nnpm\n\n```bash\nnpm i @ogcio/o11y-sdk-node\n```\n\n### Entry points\n\nThe package exposes three code entry points, and no other paths into its internals:\n\n| Import path                                | Contents                                                                                                  |\n| ------------------------------------------ | --------------------------------------------------------------------------------------------------------- |\n| `@ogcio/o11y-sdk-node`                     | `instrumentNode`, traces, metrics, geo, the shared core utilities and the re-exported OpenTelemetry types |\n| `@ogcio/o11y-sdk-node/presets/sentry-node` | `withSentry`, requires `@sentry/node` and `@sentry/opentelemetry`                                         |\n| `@ogcio/o11y-sdk-node/presets/sentry-next` | `withSentryNextjs`, requires `@sentry/nextjs` and `@sentry/opentelemetry`                                 |\n\nThe Sentry packages are optional peer dependencies. Installing only the SDK is enough\nfor the root entry point to build and run: see [Presets Documentation](./lib/presets/README.md).\n\n## Usage\n\nSetup using constructor function\n\n```javascript\n// instrumentation.ts\n\nimport(\"@ogcio/o11y-sdk-node\").then((sdk) =>\n  sdk.instrumentNode({\n    serviceName: \"node-microservice\",\n    collectorUrl: \"http://localhost:4317\",\n    resourceAttributes: {\n      \"team.infra.cluster\": \"dev-01\",\n      \"team.infra.pod\": \"01\",\n      \"team.service.type\": \"fastify\",\n    },\n    spanAttributes: {\n      \"signal.namespace\": \"documentation\",\n    },\n    ignoreUrls: [{ type: \"equals\", url: \"/api/health\" }],\n  }),\n);\n```\n\nRun your node script with instrumentation\n\n`node --import instrumentation.js server.js`\n\nOr setup inside your package.json\n\n```json\n{\n  \"main\": \"dist/index.js\",\n  \"type\": \"module\",\n  \"scripts\": {\n    \"start\": \"node --env-file=.env --import ./dist/instrumentation.js dist/index.js\"\n  }\n}\n```\n\n# Traces\n\n## Span Customization\n\nIt is possible to customize spans such as traces and logs globally or in a single code statement using predefined functions.\n\n### Global Configuration\n\nIn the SDK configuration, you can set the following properties:\n\n- `spanAttributes` Object containing static properties or functions used to evaluate custom attributes for every logs and traces.\n- `resourceAttributes` Object containing static properties used as resources attributes for any signal.\n- `traceRatio` Faction value from 0 to 1, used by TraceIdRatioBasedSampler which it deterministically samples a percentage of traces that you pass in as a parameter.\n\n```typescript\nfunction generateRandomString(): string {\n  return Math.random() + \"_\" + Date.now();\n}\n\ninstrumentNode({\n  resourceAttributes: {\n    \"property.name.one\": \"value_one\",\n    \"property.name.two\": \"value_two\",\n  },\n  spanAttributes: {\n    \"custom.span.value\": \"example\",\n    \"custom.span.value_with_function\": generateRandomString,\n  },\n});\n```\n\n### PII Detection\n\nBy default the sdk detect and redact email PII from traces and logs\n\nexample:\n\n```\ninput: user access: name.lastname@domain.com\noutput: user access: [REDACTED EMAIL]\n```\n\nYou can disable PII detection with `detection` object inside `NodeSDKConfig`\n\n```typescript\ninstrumentNode({\n  detection: {\n    email: false,\n  },\n});\n```\n\n## Extension Points\n\nThe SDK provides extension points for integrating with third-party observability vendors (e.g. Sentry) or adding custom processing logic.\n\n### Span Processors\n\nAdd custom span processors that run before the default OTLP exporters:\n\n```typescript\nimport { instrumentNode } from \"@ogcio/o11y-sdk-node\";\nimport { MyCustomSpanProcessor } from \"./my-processor\";\n\nawait instrumentNode({\n  collectorUrl: \"http://localhost:4317\",\n  serviceName: \"my-service\",\n\n  // Processors that run before OTLP export (e.g., vendor processors)\n  prependSpanProcessors: [new MyCustomSpanProcessor()],\n});\n```\n\n### Log Processors\n\nSimilarly, add custom log record processors:\n\n```typescript\nawait instrumentNode({\n  collectorUrl: \"http://localhost:4317\",\n  serviceName: \"my-service\",\n\n  prependLogProcessors: [new MyLogProcessor()],\n});\n```\n\n### Custom Sampler\n\nWrap or replace the default sampler using `samplerWrapper`:\n\n```typescript\nimport { TraceIdRatioBasedSampler } from \"@opentelemetry/sdk-trace-base\";\n\nawait instrumentNode({\n  collectorUrl: \"http://localhost:4317\",\n  serviceName: \"my-service\",\n\n  // Wrap the default sampler with custom logic\n  samplerWrapper: (_defaultSampler) => {\n    // Discard the default sampler and return your custom sampler, or wrap it and leverage it as default\n    return new MyCustomSampler();\n  },\n});\n```\n\n### Custom Context Manager\n\nOverride the default context manager:\n\n```typescript\nimport { AsyncLocalStorageContextManager } from \"@opentelemetry/context-async-hooks\";\n\nawait instrumentNode({\n  collectorUrl: \"http://localhost:4317\",\n  serviceName: \"my-service\",\n\n  contextManager: new AsyncLocalStorageContextManager(), //(the current default)\n});\n```\n\n### Additional Propagators\n\nAdd propagators to the composite propagator (W3CTraceContextPropagator is always included):\n\n```typescript\nimport { B3Propagator } from \"@opentelemetry/propagator-b3\";\n\nawait instrumentNode({\n  collectorUrl: \"http://localhost:4317\",\n  serviceName: \"my-service\",\n\n  additionalPropagators: [new B3Propagator()],\n});\n```\n\n### Post-Start Callback\n\nExecute code after the SDK has started:\n\n```typescript\nawait instrumentNode({\n  collectorUrl: \"http://localhost:4317\",\n  serviceName: \"my-service\",\n\n  onSdkStarted: (sdk) => {\n    console.log(\"SDK started successfully\");\n    // Perform vendor-specific validation, register additional hooks, etc.\n  },\n});\n```\n\n## Vendor Presets\n\nFor common integrations, the SDK provides preset functions that configure all extension points automatically. See [Presets Documentation](./lib/presets/README.md) for details.\n\n## Geo Enrichment\n\nThe SDK can attach geo attributes (`geo.country`, `geo.city`, `geo.hash`) to your\nsignals from CloudFront viewer headers. There are two ways to do it.\n\n### Automatic enrichment (opt-in)\n\nAutomatic enrichment is **disabled by default**. Enable it to have the SDK add geo\nattributes to every span, log, and metric and propagate them downstream via\nbaggage:\n\n```ts\nawait instrumentNode({\n  // ...other config\n  geoEnrichment: { enabled: true },\n});\n```\n\nWhen enabled, use `getGeoAttributes()` to read the geo attributes resolved for the\ncurrent request context (populated by the geo baggage propagator) and merge them\ninto any custom span, log, or metric:\n\n```ts\nimport { getActiveSpan, getGeoAttributes } from \"@ogcio/o11y-sdk-node\";\n\ngetActiveSpan()?.setAttributes(getGeoAttributes());\n```\n\n### Pinpoint enrichment (auto-enrichment off)\n\nWhen automatic enrichment is left disabled, enrich a **single** span, log, or\nmetric on demand. This is the supported pattern for adding geo attributes without\nthe processors or baggage propagator.\n\n**From CloudFront headers** — `createGeoAttributesFromHeaders` reads the\ncloudfront headers directly, a plain header map such as Node's\n`IncomingHttpHeaders` works out of the box, and requires neither auto-enrichment\nnor baggage propagation:\n\n```ts\nimport { withSpan, createGeoAttributesFromHeaders } from \"@ogcio/o11y-sdk-node\";\n\napp.get(\"/\", async (req, reply) => {\n  const geoAttr = createGeoAttributesFromHeaders(req.headers);\n\n  await withSpan({\n    spanName: \"list users\",\n    spanOptions: { attributes: { ...geoAttr } },\n    fn: async (span) => {\n      /* ... */\n    },\n  });\n});\n```\n\n**From explicit input** — `createGeoAttributesFrom` builds the same attributes\nfrom values you already have. A geohash is computed automatically when both `lat`\nand `lon` are provided:\n\n```ts\nimport { getMetric, createGeoAttributesFrom } from \"@ogcio/o11y-sdk-node\";\n\nconst geoAttr = createGeoAttributesFrom({\n  country: \"IE\",\n  city: \"Dublin\",\n  lat: 53.3498,\n  lon: -6.2603,\n});\n\ngetMetric(\"counter\", { metricName: \"user.insert\", meterName: \"app\" }).add(1, {\n  ...geoAttr,\n});\n```\n\n## Utils:\n\n- ## `withSpan`:\n\n  ### Key Features\n  - **Automatic Span Management**: Spans are automatically started, ended, and their status is set based on execution success or failure\n    - **Exception Recording**: Errors are automatically recorded with proper span status codes\n    - **Flexible Configuration**: Support for custom tracer names, span options, and attributes\n    - **Promise Support**: Works seamlessly with both synchronous and asynchronous functions\n    - **Nested Tracing**: Spans created within existing trace contexts automatically become child spans\n\n  ### Usage:\n\n  ```ts\n  import { SpanOptions } from \"@opentelemetry/api\";\n\n  export type WithSpanParams<T> = {\n    /**\n     * The name of the trace the span should belong to.\n     * NOTE: If you want the new span to belong to an already existing trace, you should provide the same tracer name\n     */\n    traceName?: string;\n    spanName: string;\n    spanOptions?: SpanOptions;\n    /** A function defining the task you want to be wrapped by this span */\n    fn: (span: Span) => T | Promise<T>;\n  };\n  ```\n\n  ### examples:\n\n  ### **Creating a Top-Level Trace (e.g. Worker Job)**\n\n  Use to create a top-level trace for background jobs, workers, or any standalone operations: `withSpan`\n\n  ```ts\n  import { withSpan } from \"@ogcio/o11y-sdk-node\";\n\n  async function processEmailQueue() {\n    return withSpan({\n      traceName: \"email-worker\",\n      spanName: \"process-email-queue\",\n      fn: async (span) => {\n        // Your worker logic here\n        const emails = await fetchPendingEmails();\n        span.setAttributes({\n          \"email.count\": emails.length,\n          \"worker.batch.id\": generateBatchId(),\n        });\n\n        for (const email of emails) {\n          await sendEmail(email);\n        }\n\n        return { processed: emails.length };\n      },\n    });\n  }\n  ```\n\n  ### **Nesting Spans Inside Existing Traces**\n\n  Create child spans within existing trace contexts to provide detailed operation breakdown:\n\n  ```typescript\n  async function orderProcessing(orderId: string) {\n    return withSpan({\n      spanName: \"process-order\",\n      fn: async (parentSpan) => {\n        // Child span for validation\n        const validation = await withSpan({\n          spanName: \"validate-order\",\n          fn: async (span) => {\n            span.setAttribute(\"order.id\", orderId);\n            return await validateOrder(orderId);\n          },\n        });\n        // Child span for payment\n        const payment = await withSpan({\n          spanName: \"process-payment\",\n          fn: async (span) => {\n            span.setAttribute(\"payment.amount\", validation.amount);\n            return await processPayment(orderId, validation.amount);\n          },\n        });\n\n        parentSpan.setAttributes({\n          \"order.status\": \"completed\",\n          \"order.total\": payment.amount,\n        });\n\n        return { orderId, status: \"completed\" };\n      },\n    });\n  }\n  ```\n\n- ## `getActiveSpan`:\n\n  Using `getActiveSpan` function, you can access to current transaction span and customize it.\n\n  ### Examples:\n\n  ### **Edit Active Span**\n\n  You can use the function everywhere in your code, and set some custom attributes that are enabled for that single span\n\n  ```typescript\n  import { getActiveSpan } from \"@ogcio/o11y-sdk-node\";\n\n  async function routes(app: FastifyInstance) {\n    app.get(\"/\", async (req, reply) => {\n      // validation and business logic\n\n      // set span attribute\n      getActiveSpan()?.setAttribute(\"business.info\", \"dummy\");\n\n      reply.status(200).send(response);\n    });\n  }\n  ```\n\n## Sending Custom Metrics\n\nThis package gives the possibility to send custom metrics and define them as desired in the code, you can choose between sync metrics and observable async metrics.\n\nTo use this functionality, you only need to import `getMetric` and enable the application instrumentation.\n\n```typescript\nimport { getMetric } from \"@ogcio/o11y-sdk-node\";\n```\n\n### Sync\n\nSync metrics are signals sent when the function has been called.\n\nCreating a counter, there are 2 types of counter:\n\n- **counter** a simple counter that can only add positive numbers\n- **updowncounter** counter that support also negative numbers\n\n```typescript\nconst counter = getMetric(\"counter\", {\n  attributeName: \"counter\",\n  metricName: \"fastify-counter\",\n});\n\ncounter.add(1, {\n  my: \"my\",\n  custom: \"custom\",\n  attributes: \"attributes\",\n});\n```\n\nCreating a Histogram\n\n```typescript\nconst histogram = getMetric(\"histogram\", {\n  metricName: \"response_duration\",\n  attributeName: \"http_response\",\n  options: {\n    advice: {\n      explicitBucketBoundaries: [0, 100, 200, 500, 1000],\n    },\n    description: \"Response durations\",\n  },\n});\n\nhistogram.record(120, { path: \"/home\" });\n```\n\n### Async\n\nAsync metrics are called by the scraper collector to read current data using the `Observable` pattern.\nCreating an async metric means that the application will subscribe to the observability URL and record data on call (default 60s).\n\n_keep in mind, you can't send signals on-demand with this component_\n\nCreating an async Gauge\n\n```typescript\nconst asyncGauge = getMetric(\"async-gauge\", {\n  metricName: \"cpu_usage\",\n  attributeName: \"server_load\",\n  options: { unit: \"percentage\" },\n}).addCallback((observer) => {\n  observer.observe(50, { host: \"server1\" });\n});\n```\n\nCreating an async Counter\n\n```typescript\ngetMetric(\"async-counter\", {\n  attributeName: \"scraped-memory\",\n  metricName: \"fastify-counter\",\n}).addCallback((observer) => {\n  observer.observe(freemem(), {\n    \"application.os.memory\": \"free-memory\",\n  });\n});\n```\n\n## API Reference\n\n#### Protocol\n\nprotocol is a string parameter used to define how to send signals to observability infrastructure\n\n- **grpc** Use gRPC protocol, usually default port use 4317. Is the most performant option for server side applications.\n- **http** Use HTTP standard protocol, usually default port use 4318. Mainly used on web or UI client applications.\n- **console** Used for debugging sending signals to observability cluster, every information will be printed to your runtime console.\n\n#### Shared Types\n\n```typescript\nexport type SDKLogLevel =\n  \"NONE\" | \"ERROR\" | \"WARN\" | \"INFO\" | \"DEBUG\" | \"VERBOSE\" | \"ALL\";\n```\n\n### Config\n\n| Parameter                    | Type                                   | Description                                                                                                       |\n| :--------------------------- | :------------------------------------- | :---------------------------------------------------------------------------------------------------------------- |\n| `collectorUrl`               | `string`                               | **Required**. The opentelemetry collector entrypoint url, if null, instrumentation will not be activated          |\n| `serviceName`                | `string`                               | Name of your application used for the collector to group logs                                                     |\n| `diagLogLevel`               | `SDKLogLevel`                          | Diagnostic log level for the internal runtime instrumentation                                                     |\n| `collectorMode`              | `single \\| batch`                      | Signals sending mode, default is batch for performance                                                            |\n| `enableFS`                   | `boolean`                              | **Deprecated**. Use `autoInstrumentationConfig` instead. Flag to enable or disable the tracing for node:fs module |\n| `autoInstrumentationConfig`  | `InstrumentationConfigMap`             | Configuration object for auto instrumentations. Default: `{\"@opentelemetry/instrumentation-fs\":{enabled:false}}`  |\n| `additionalInstrumentations` | `Instrumentation[]`                    | Additional custom instrumentations to be added to the NodeSDK. Default: `[]`                                      |\n| `protocol`                   | `string`                               | Type of the protocol used to send signals                                                                         |\n| `prependSpanProcessors`      | `SpanProcessor[]`                      | Span processors to run before OTLP export. Default: `[]`                                                          |\n| `prependLogProcessors`       | `LogRecordProcessor[]`                 | Log processors to run before OTLP export. Default: `[]`                                                           |\n| `samplerWrapper`             | `(defaultSampler: Sampler) => Sampler` | Function to wrap or replace the default sampler                                                                   |\n| `contextManager`             | `ContextManager`                       | Custom context manager to use                                                                                     |\n| `additionalPropagators`      | `TextMapPropagator[]`                  | Additional propagators to add to the composite propagator. Default: `[]`                                          |\n| `onSdkStarted`               | `(sdk: NodeSDK) => void`               | Callback invoked after the SDK has started                                                                        |\n","readmeFilename":""}