Observability setup guide for ADK agents covering tracing, logging, analytics, and third-party integrations.
Works with
Four observability tiers: Cloud Trace (always enabled, distributed tracing), Prompt-Response Logging (GenAI interactions to GCS/BigQuery), BigQuery Agent Analytics (structured agent events), and third-party platforms (AgentOps, Phoenix, MLflow, Weave, Arize, Monocle, Freeplay)
Cloud Trace automatically configured in scaffolded projects and Agent Engine deployments; captures execu
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionadk-observability-guideExecute the skills CLI command in your project's root directory to begin installation:
Fetches adk-observability-guide from google/adk-docs and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate adk-observability-guide. Access via /adk-observability-guide in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Scaffolded project? Cloud Trace and prompt-response logging are pre-configured by Terraform. See
references/cloud-trace-and-logging.mdfor infrastructure details, env vars, and verification commands.No scaffold? Follow the ADK docs links below for manual setup. For production infrastructure, scaffold with
/adk-scaffold.
| 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 |
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.
ADK uses OpenTelemetry to emit distributed traces. Every agent invocation produces spans that track the full execution flow.
invocation
└── agent_run (one per agent in the chain)
├── call_llm (model request/response)
└── execute_tool (tool execution)
| Deployment | Setup |
|---|---|
| Agent Engine | 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 make playground; traces visible in Cloud Console |
View traces: Cloud Console → Trace → Trace explorer
For detailed setup instructions (Agent Engine CLI/SDK, Cloud Run, custom deployments), fetch https://adk.dev/integrations/cloud-trace/index.md.
Captures GenAI interactions (model name, tokens, timing) and exports to GCS (JSONL), BigQuery (external tables), and Cloud Logging (dedicated bucket). 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.
Optional plugin that logs structured agent events to BigQuery. Enable with --bq-analytics at scaffold time. See references/bigquery-agent-analytics.md for details.
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.
| 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 |
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 | https://adk.dev/integrations/cloud-trace/index.md |
| BigQuery Agent Analytics | https://adk.dev/integrations/bigquery-agent-analytics/index.md |
| AgentOps | https://adk.dev/integrations/agentops/index.md |
| Arize AX | https://adk.dev/integrations/arize-ax/index.md |
| Phoenix (Arize) | https://adk.dev/integrations/phoenix/index.md |
| MLflow tracing | https://adk.dev/integrations/mlflow/index.md |
| Monocle | https://adk.dev/integrations/monocle/index.md |
| W&B Weave | https://adk.dev/integrations/weave/index.md |
| Freeplay | https://adk.dev/integrations/freeplay/index.md |
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
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✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
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Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Keeps context tight: adk-observability-guide is the kind of skill you can hand to a new teammate without a long onboarding doc.
adk-observability-guide reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend adk-observability-guide for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
adk-observability-guide has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in adk-observability-guide — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: adk-observability-guide is focused, and the summary matches what you get after install.
Keeps context tight: adk-observability-guide is the kind of skill you can hand to a new teammate without a long onboarding doc.
adk-observability-guide is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: adk-observability-guide is the kind of skill you can hand to a new teammate without a long onboarding doc.
adk-observability-guide is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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