Add instrumentation for Google Vertex AI (@google-cloud/vertexai)

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
58/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Active
Tech stack
google-cloud, nodejs, typescript
Domain
backend-api-design, observability

Research direction

Start by reading the existing instrumentation under packages/server-utils/src/ai/google-genai/ and the integration wiring in src/integrations/google-genai.ts, then compare the Vertex AI SDK entry points named in the issue. Add the standalone integration under packages/server-utils/src/ai/google-vertexai/, wire it through src/integrations/google-vertexai.ts and getTracingIntegrations(), and cover generation, chat, streaming, model, token, and finish-reason attributes.

Written by the indexing model from the issue text.

Description

Feature javascript Node.js

Add native gen-AI instrumentation for the standalone Google Vertex AI SDK, @google-cloud/vertexai (repo).

Coverage status / why this is a partial gap

Vertex is already reachable two ways today, so this is specifically about the standalone SDK:

  • @google/genai (which we already instrument) can target the Vertex backend via vertexai: true — already covered.
  • @ai-sdk/google-vertex (Vercel AI SDK provider, ~13.6M/mo) — covered by proxy through our vercel-ai integration.
  • @google-cloud/vertexai standalone SDK — not covered. This issue tracks that path.

Relevance (npm)

  • @google-cloud/vertexai: ~4.0M downloads/month (~33.7M last year). Slightly above its trailing-12-month run-rate, though Google is steering users toward the unified @google/genai SDK, so weigh this against the fact that the modern path is already instrumented.

Rough scope

  • Add instrumentation logic under packages/server-utils/src/ai/google-vertexai/ and wire it up via src/integrations/google-vertexai.ts, registered in getTracingIntegrations() (per the AI-integration architecture; runtime packages re-export from @sentry/server-utils).
  • Instrument VertexAI -> getGenerativeModel().generateContent() / generateContentStream() (and chat sessions), plus streaming.
  • Emit gen_ai.* spans following the span attribute conventions (gen_ai.provider.name = google_vertex, request/response model, token usage, finish reasons). Much of the response/attribute shaping likely overlaps with the existing google-genai instrumentation and can be shared.
  • Not OpenAI wire-compatible, so it needs its own instrumentation (can't reuse the openai-compatible shim).
Dominant language
TypeScript
Stars
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Forks
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Avg merge
1d 18h
Merged PRs (30d)
543

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First steps

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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