google-agents-cli-observability

What this skill does

# ADK Observability Guide

> **Cloud Trace** works out of the box — no infrastructure needed. **Prompt-response logging** and **BigQuery Agent Analytics** require Terraform-provisioned infrastructure (service account, GCS bucket, BigQuery dataset). Run `agents-cli infra single-project --project PROJECT_ID` to provision these resources. See `references/cloud-trace-and-logging.md` for details, env vars, and verification commands. If your project isn't scaffolded yet, see `/google-agents-cli-scaffold` first.

### Order of operations for `agent_runtime` deployments

For `deployment_target = agent_runtime`, run `agents-cli infra single-project` **before** the first `agents-cli deploy`. The Terraform module owns the entire Reasoning Engine resource (display_name, service account, deployment spec, env vars), so applying it after a SDK-based deploy creates a state mismatch — Terraform has no record of the SDK-deployed instance and cannot layer env vars onto it without taking ownership of the whole resource.

If you have already run `agents-cli deploy`, you have two options:

1. **Switch to Terraform-managed.** Delete the SDK-deployed Reasoning Engine, then run `agents-cli infra single-project` followed by `agents-cli deploy`. Sessions and any in-flight state on the previous instance are lost.
2. **Keep the SDK-deployed instance.** Skip `infra single-project` and set the observability env vars on the running instance directly via the `vertexai` client `update` API. You will also need to grant the instance's service account the IAM permissions required to emit telemetry — writing to the logs GCS bucket, BigQuery dataset access, log writer, etc. See `deployment/terraform/single-project/iam.tf` and `telemetry.tf` in your scaffolded project for the full set of bindings the Terraform module would otherwise provision. Terraform-managed env vars are not available in this mode.

### Reference Files

| File | Contents |
|------|----------|
| `references/cloud-trace-and-logging.md` | Scaffolded project details — Terraform-provisioned resources, environment variables, verification commands, enabling/disabling locally |
| `references/bigquery-agent-analytics.md` | BQ Agent Analytics plugin — enabling, key features, GCS offloading, tool provenance |

---

## Observability Tiers

Choose the right level of observability based on your needs:

| Tier | What It Does | Scope | Default State | Best For |
|------|-------------|-------|---------------|----------|
| **Cloud Trace** | Distributed tracing — execution flow, latency, errors via OpenTelemetry spans | All templates, all environments | Always enabled | Debugging latency, understanding agent execution flow |
| **Prompt-Response Logging** | GenAI interactions exported to GCS, BigQuery, and Cloud Logging | ADK agents only | Disabled locally, enabled when deployed | Auditing LLM interactions, compliance |
| **BigQuery Agent Analytics** | Structured agent events (LLM calls, tool use, outcomes) to BigQuery | ADK agents with plugin enabled | Opt-in (`--bq-analytics` at scaffold time) | Conversational analytics, custom dashboards, LLM-as-judge evals |
| **Third-Party Integrations** | External observability platforms (AgentOps, Phoenix, MLflow, etc.) | Any ADK agent | Opt-in, per-provider setup | Team collaboration, specialized visualization, prompt management |

**Ask the user** which tier(s) they need — they can be combined. Cloud Trace is always on; the others are additive.

---

## Cloud Trace

ADK uses OpenTelemetry to emit distributed traces. Every agent invocation produces spans that track the full execution flow.

### Span Hierarchy

```
invocation
  └── agent_run (one per agent in the chain)
        ├── call_llm (model request/response)
        └── execute_tool (tool execution)
```

### Setup by Deployment Type

| Deployment | Setup |
|-----------|-------|
| **Agent Runtime** | Automatic — traces are exported to Cloud Trace by default |
| **Cloud Run (scaffolded)** | Automatic — `otel_to_cloud=True` in the FastAPI app |
| **GKE (scaffolded)** | Automatic — `otel_to_cloud=True` in the FastAPI app |
| **Cloud Run / GKE (manual)** | Configure OpenTelemetry exporter in your app |
| **Local dev** | Works with `agents-cli playground`; traces visible in Cloud Console |

View traces: **Cloud Console → Trace → Trace explorer**

For detailed setup instructions (Agent Runtime CLI/SDK, Cloud Run, custom deployments), fetch `https://adk.dev/integrations/cloud-trace/index.md`.

---

## Prompt-Response Logging

Captures GenAI interactions (model name, tokens, timing) and exports to GCS (JSONL) and BigQuery (via direct log sinks and external tables). Privacy-preserving by default — only metadata is logged unless explicitly configured otherwise.

Key env var: `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT` — set to `NO_CONTENT` (metadata only, default in deployed envs), `true` (full content), or `false` (disabled). Logging is disabled locally unless `LOGS_BUCKET_NAME` is set.

For scaffolded project details (Terraform resources, env vars, privacy modes, enabling/disabling, verification commands), see `references/cloud-trace-and-logging.md`.

For ADK logging docs (log levels, configuration, debugging), fetch `https://adk.dev/observability/logging/index.md`.

---

## BigQuery Agent Analytics Plugin

Optional plugin that logs structured agent events to BigQuery. Enable with `--bq-analytics` at scaffold time. See `references/bigquery-agent-analytics.md` for details.

---

## Third-Party Integrations

ADK supports several third-party observability platforms. Each uses OpenTelemetry or custom instrumentation to capture agent behavior.

| Platform | Key Differentiator | Setup Complexity | Self-Hosted Option |
|----------|-------------------|-----------------|-------------------|
| **AgentOps** | Session replays, 2-line setup, replaces native telemetry | Minimal | No (SaaS) |
| **Arize AX** | Commercial platform, production monitoring, evaluation dashboards | Low | No (SaaS) |
| **Phoenix** | Open-source, custom evaluators, experiment testing | Low | Yes |
| **MLflow** | OTel traces to MLflow Tracking Server, span tree visualization | Medium (needs SQL backend) | Yes |
| **Monocle** | 1-call setup, VS Code Gantt chart visualizer | Minimal | Yes (local files) |
| **Weave** | W&B platform, team collaboration, timeline views | Low | No (SaaS) |
| **Freeplay** | Prompt management + evals + observability in one platform | Low | No (SaaS) |

**Ask the user** which platform they prefer — present the trade-offs and let them choose. For setup details, fetch the relevant ADK docs page from the Deep Dive table below.

---

## Troubleshooting

| Issue | Solution |
|-------|----------|
| No traces in Cloud Trace | Verify `otel_to_cloud=True` in FastAPI app; check service account has `cloudtrace.agent` role |
| Prompt-response data not appearing | Check `LOGS_BUCKET_NAME` is set; verify SA has `storage.objectCreator` on the bucket; check app logs for telemetry setup warnings |
| Privacy mode misconfigured | Check `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT` value — use `NO_CONTENT` for metadata-only, `false` to disable |
| BigQuery Analytics not logging | Verify plugin is configured in `app/agent.py`; check `BQ_ANALYTICS_DATASET_ID` env var is set |
| Third-party integration not capturing spans | Check provider-specific env vars (API keys, endpoints); some providers (AgentOps) replace native telemetry |
| Traces missing tool spans | Tool execution spans appear under `execute_tool` — check trace explorer filters |
| High telemetry costs | Switch to `NO_CONTENT` mode; reduce BigQuery retention; disable unused tiers |

---

## Deep Dive: ADK Docs (WebFetch URLs)

For detailed documentation beyond what this skill covers, fetch these pages:

| Topic | URL |
|-------|-----|
| Observability overview | `https://adk.dev/observability/index.md` |
| Agent activity logging | `https://adk.dev/observability/logging/index.md` |
| Cloud Trace integration | `ht