adk-observability-guide

Observability setup guide for ADK agents covering tracing, logging, analytics, and third-party integrations.

google/adk-docs|Updated Apr 8, 2026

Works with

Claude CodeCursorClineWindsurfCodexGoose

What it does

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

Repository

google/adk-docs

Last updated

Apr 8, 2026

Installation Guide

Select your AI agent

How to use adk-observability-guide on Cursor

AI-first code editor with Composer

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your machine
›Node.js 16+ with npm — verify with node --version
›Active project directory where you want to add adk-observability-guide

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/google/adk-docs --skill adk-observability-guide

Fetches adk-observability-guide from google/adk-docs and configures it for Cursor.

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ────────────────

│ · Cline · Codex · Goose · Windsurf

│ ●Cursor(selected)

│ · Cursor · Aider · Continue

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/adk-observability-guide

Restart Cursor to activate adk-observability-guide. Access via /adk-observability-guide in your agent's command palette.

⚠

Security Notice

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.

›View source on GitHub ›Skills CLI docs ›About Cursor ›What are agent skills?

Documentation

List & Monetize Your Skill

Submit your Claude Code skill and start earning

Get started →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

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

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

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

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)

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

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`

adk-observability-guide

What it does

Category

Repository

Last updated

Installation Guide

How to use adk-observability-guide on Cursor

Prerequisites

Run the install command

Select Cursor when prompted

Verify installation

Security Notice

Documentation

List & Monetize Your Skill

Use Cases

Task Automation & Efficiency

Knowledge Enhancement

Quality Improvement

Install Skill

ADK Observability Guide

Reference Files

Observability Tiers

Cloud Trace

Span Hierarchy

Setup by Deployment Type

Prompt-Response Logging

BigQuery Agent Analytics Plugin

Third-Party Integrations

Troubleshooting

Deep Dive: ADK Docs (WebFetch URLs)

Implementation Guide

Best Practices

When to Use This

Learning Path

Related Skills

frontend-design

premium-frontend-ui

ui-animation

high-end-visual-design

antigravity-design-expert

interior-design-expert

Reviews

Discussion