@sentry/ember

Important Changes

• aws-serverless: Ship Lambda extension in npm package for container image Lambdas

  The Sentry Lambda extension is now included in the npm package, enabling container image-based Lambda functions to use it. Copy the extension files into your Docker image and set the tunnel option:

  RUN mkdir -p /opt/sentry-extension
  COPY node_modules/@sentry/aws-serverless/build/lambda-extension/sentry-extension /opt/extensions/sentry-extension
  COPY node_modules/@sentry/aws-serverless/build/lambda-extension/index.mjs /opt/sentry-extension/index.mjs
  RUN chmod +x /opt/extensions/sentry-extension /opt/sentry-extension/index.mjs

  Sentry.init({
    dsn: '__DSN__',
    tunnel: 'http://localhost:9000/envelope',
  });

  This works with any Sentry SDK (@sentry/aws-serverless, @sentry/sveltekit, @sentry/node, etc.).

• cloudflare: Support basic WorkerEntrypoint

  withSentry now supports instrumenting classes extending Cloudflare's WorkerEntrypoint. This instruments fetch, scheduled, queue, and tail handlers.

  import * as Sentry from '@sentry/cloudflare';
  import { WorkerEntrypoint } from 'cloudflare:workers';
  
  class MyWorker extends WorkerEntrypoint {
    async fetch(request: Request): Promise<Response> {
      return new Response('Hello World!');
    }
  }
  
  export default Sentry.withSentry(env => ({ dsn: env.SENTRY_DSN, tracesSampleRate: 1.0 }), MyWorker);

• ref(core): Unify .do* span ops to gen_ai.generate_content (#20074)

  All Vercel AI do* spans (ai.generateText.doGenerate, ai.streamText.doStream, ai.generateObject.doGenerate, ai.streamObject.doStream) now use a single unified span op gen_ai.generate_content instead of separate ops like gen_ai.generate_text, gen_ai.stream_text, gen_ai.generate_object, and gen_ai.stream_object.

• core: Support embeddings in LangChain

  Adds instrumentation for LangChain embeddings (embedQuery, embedDocuments), creating gen_ai.embeddings spans. In Node.js, embedding classes from @langchain/openai, @langchain/google-genai, @langchain/mistralai, and @langchain/google-vertexai are auto-instrumented. For other runtimes, use the new instrumentLangChainEmbeddings API:

  import * as Sentry from '@sentry/cloudflare';
  import { OpenAIEmbeddings } from '@langchain/openai';
  
  const embeddings = Sentry.instrumentLangChainEmbeddings(new OpenAIEmbeddings({ model: 'text-embedding-3-small' }));
  
  await embeddings.embedQuery('Hello world');

Other Changes

• core: Support registerTool/registerResource/registerPrompt in MCP integration

• core, node: Portable Express integration

• deno: Add denoRuntimeMetricsIntegration

• node, bun: Enforce minimum collection interval in runtime metrics integrations

• nuxt: Exclude tracing meta tags on cached pages in Nuxt 5

• react-router: Export sentryOnError

• aws-serverless: Add timeout to _endSpan forceFlush to prevent Lambda hanging

• cloudflare: Ensure every request instruments functions

• core: Only attach flags context to error events

• core: Replace regex with string check in stack parser to prevent main thread blocking

• core: Set span.status to error when MCP tool returns JSON-RPC error response

• gatsby: Fix errorHandler signature to match bundler-plugin-core API

Internal Changes

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