OTel Next.js Style

For Next.js apps, prefer the framework entrypoint.

// instrumentation.ts
import { registerOTel } from "@vercel/otel";

export function register() {
  registerOTel({
    serviceName: "mugline-web",
  });
}

Do not replace this with a custom NodeSDK bootstrap unless the repo is not a normal Next/Vercel app or already has a custom provider that must be extended.

For JavaScript/TypeScript LLM providers, prefer provider instrumentation over manual child spans. For Anthropic, add OpenInference in the same bootstrap and keep call sites native. This example uses @vercel/[email protected]; if the installed types are v1, use logRecordProcessor singular instead.

import Anthropic from "@anthropic-ai/sdk";
import { AnthropicInstrumentation } from "@arizeai/openinference-instrumentation-anthropic";
import { OTLPLogExporter } from "@opentelemetry/exporter-logs-otlp-http";
import { BatchLogRecordProcessor } from "@opentelemetry/sdk-logs";
import { registerOTel } from "@vercel/otel";

const anthropicInstrumentation = new AnthropicInstrumentation({
  traceConfig: {
    hideInputs: true,
    hideOutputs: true,
  },
});

anthropicInstrumentation.manuallyInstrument(Anthropic);

export function register() {
  registerOTel({
    serviceName: "mugline-web",
    instrumentations: [anthropicInstrumentation],
    logRecordProcessors: [new BatchLogRecordProcessor(new OTLPLogExporter())],
  });
}

Route Handlers

Use native OTel APIs where auto-instrumentation is blind.

import { withSpan } from "@superlog/otel-helpers";

const tracer = trace.getTracer("mugline.web");
const meter = metrics.getMeter("mugline.web");
const requests = meter.createCounter("mug.copy.generated");

export async function POST(request: Request) {
  const tenantId = request.headers.get("x-tenant-id") ?? "tenant_demo";
  return await withSpan("mug.copy.generate", async (span) => {
    span.setAttribute("tenant.id", tenantId);
    requests.add(1, { "tenant.id": tenantId, outcome: "success" });
    return Response.json({ ok: true });
  }, { tracer });
}

For TypeScript route handlers, use @superlog/otel-helpers withSpan for bounded business spans and add @superlog/otel-helpers to package.json when it is not already present. This is required when the package can be installed. It keeps span lifecycle/error handling out of the handler body and avoids a large indentation diff. Do not expand the whole route into tracer.startActiveSpan(...) plus try / catch / finally unless the helper cannot be added or the span has a true cross-callback lifecycle.

If a route has an LLM call and OpenInference/provider instrumentation supports that SDK, do not wrap the provider call. Leave client.messages.create(...) / equivalent in place and put business context on the active product span or structured log. Do not duplicate provider/model/token attributes in route-level spans, logs, or metrics when OpenInference already reports them. Do not calculate LLM cost in route handlers; Superlog derives estimated cost in the UI/query layer from OpenInference provider/model/token attributes. For Anthropic in Next.js/ESM, keep the instrumentation instance and manuallyInstrument(Anthropic) call at module scope so it runs once and before route code.

Match the @vercel/otel logs option to the installed package/types: @vercel/[email protected] uses logRecordProcessor singular, while @vercel/[email protected] uses logRecordProcessors plural. For normal Next.js/Vercel apps, do not guard registerOTel(...) behind NEXT_RUNTIME; Next calls instrumentation.ts in the appropriate runtime and @vercel/otel handles its own runtime differences.

console.info is not OTLP log export. If there is no existing logger bridge, use @opentelemetry/api-logs for production log records. Remove pre-existing console.* calls that duplicate the same structured OTel log event:

logger.emit({
  severityNumber: SeverityNumber.INFO,
  severityText: "INFO",
  body: "generated mug copy",
  attributes: {
    "tenant.id": tenantId,
    "gen_ai.provider.name": "anthropic",
    "gen_ai.request.model": model,
    "app.gen_ai.use_case": "web.mug_copy",
    outcome: "success",
  },
});

Configuration And Smoke

Use the source-level public Superlog configuration pattern from otel-onboarding-style inside instrumentation.ts, then pass those constants explicitly to registerOTel. The public project token is write-only and belongs with the endpoint in the setup block, like a PostHog project token or Sentry DSN.

const SUPERLOG_ENDPOINT = "https://intake.superlog.sh";
const SUPERLOG_PUBLIC_TOKEN = "sl_public_...";

// The token MUST be sent as the `x-api-key` header. Ingest only reads
// `x-api-key` or `Authorization: Bearer <token>`; any other header name 401s.
function superlogHeaders(token: string): Record<string, string> {
  return { "x-api-key": token };
}

registerOTel({
  serviceName: "mugline-web",
  traceExporter: new OTLPTraceExporter({
    url: `${SUPERLOG_ENDPOINT}/v1/traces`,
    headers: superlogHeaders(SUPERLOG_PUBLIC_TOKEN),
  }),
  // …same shape for log + metric exporters
});

Smoke checks should use tools already in the repo, e.g. npm run typecheck or npm run build, plus a real app request where practical. Do not invent fragile inline Node scripts that import TypeScript source files directly, and do not assume ts-node exists unless it is already installed.