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ADK Observability

Free

Enhance monitoring for your ADK agents.

by google5.5k stars on google/agents-cli
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Updated Aug 4, 2026
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Free · Opens the source repo

What ADK Observability does

The ADK Observability skill provides essential tools for monitoring and debugging your deployed Agent Development Kit (ADK) agents. It focuses on setting up tracing, configuring logging, and enabling analytics to give developers and designers insight into their agents' performance and interactions. This skill is particularly useful for those looking to implement observability best practices in their AI-driven applications, ensuring they can track execution flow, latency, and errors effectively.

This skill is built around several key components: Cloud Trace for distributed tracing, Prompt-Response Logging for capturing interactions, and BigQuery Agent Analytics for structured event logging. Users can easily set up these features using Terraform, making it straightforward to provision the necessary infrastructure. The skill also supports third-party integrations, allowing teams to leverage existing observability platforms for enhanced visualization and prompt management.

To get started, users should run the agents-cli infra single-project command to provision the required resources. The skill emphasizes the importance of correct ordering in deployment operations to avoid state mismatches, guiding users through the process of switching to Terraform-managed deployments if needed. With these tools, developers can gain a comprehensive view of their agents’ performance, helping to identify issues and optimize their functionality.

Whether you are debugging production traffic or simply aiming to improve your observability practices, this skill provides the necessary guidance and tools to ensure your ADK agents are operating effectively and efficiently.

When to use it

Use this skill when you need to implement tracing, logging, or analytics for your ADK agents to enhance observability.

When not to use it

Do not use this skill for deployment setup or API code patterns, as it is specifically focused on observability.

What you can build with it

Debugging Latency Issues

Use Cloud Trace to identify and analyze latency in your ADK agent's execution flow.

Auditing AI Interactions

Enable Prompt-Response Logging to capture and audit interactions with your AI models for compliance.

Creating Custom Dashboards

Leverage BigQuery Agent Analytics to structure agent events and create custom dashboards for analysis.

How to install ADK Observability

View source

1. Install with the skills CLI

npx skills add google/agents-cli/google-agents-cli-observability --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by google

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 (service account, deployment spec, env vars), so applying it after an SDK-based deploy creates a state mismatch Terraform can't reconcile without taking ownership of the whole resource.

Already ran agents-cli deploy? Two options:

  1. Switch to Terraform-managed — delete the SDK-deployed Reasoning Engine, then run agents-cli infra single-project and agents-cli deploy (sessions and in-flight state are lost).
  2. Keep the SDK-deployed instance — skip infra single-project and set the observability env vars by re-running agents-cli deploy --update-env-vars "KEY=VALUE,..."; deploy matches the existing Reasoning Engine by display name and updates it in place, preserving env vars set outside the deploy. You must also grant its service account the telemetry IAM roles the Terraform module would otherwise provision: roles/storage.admin (write completions to the logs bucket), roles/logging.logWriter, roles/cloudtrace.agent, plus roles/bigquery.dataOwner + roles/bigquery.jobUser when scaffolded with --bq-analytics. The full set lives in deployment/terraform/single-project/iam.tf (from app_sa_roles) and telemetry.tf. Terraform-managed env vars aren't available in this mode.

Reference Files

FileContents
references/cloud-trace-and-logging.mdScaffolded project details — Terraform-provisioned resources, environment variables, verification commands, enabling/disabling locally
references/bigquery-agent-analytics.mdBQ Agent Analytics plugin — enabling, key features, GCS offloading, tool provenance

Observability Tiers

Choose the right level of observability based on your needs:

TierWhat It DoesScopeDefault StateBest For
Cloud TraceDistributed tracing — execution flow, latency, errors via OpenTelemetry spansAll templates, all environmentsAlways enabledDebugging latency, understanding agent execution flow
Prompt-Response LoggingGenAI interactions exported to GCS, BigQuery, and Cloud LoggingADK agents onlyDisabled locally, enabled when deployedAuditing LLM interactions, compliance
BigQuery Agent AnalyticsStructured agent events (LLM calls, tool use, outcomes) to BigQueryADK agents with plugin enabledOpt-in (--bq-analytics at scaffold time)Conversational analytics, custom dashboards, LLM-as-judge evals
Third-Party IntegrationsExternal observability platforms (AgentOps, Phoenix, MLflow, etc.)Any ADK agentOpt-in, per-provider setupTeam 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

invoke_workflow (top-level run)
  └── invoke_agent (one per agent in the chain)
        ├── call_llm (model request)
        │     └── generate_content (underlying GenAI model call)
        └── execute_tool (tool execution)

Setup by Deployment Type

DeploymentSetup
Agent RuntimeAutomatic — get_fast_api_app(otel_to_cloud=True), gated on GOOGLE_CLOUD_AGENT_ENGINE_ENABLE_TELEMETRY (set by deploy); exports to Cloud Trace/Logging + Agent Engine console
Cloud Run / GKE (scaffolded)Automatic — get_fast_api_app(otel_to_cloud=True) exports to Cloud Trace/Logging
Cloud Run / GKE (manual)Configure OpenTelemetry exporter in your app
Local devWorks 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 and exports to GCS (JSONL) and BigQuery (via log sinks + external tables). Content is governed by two independent tiers; the net Terraform-deploy default is full content in GCS/BigQuery, none in traces:

TierCapturesControlled byDefault (Terraform deploy)
GCS/BigQuery completionsFull prompts/responses (the prompt-response logging feature)OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload + LOGS_BUCKET_NAMEOn — full content
Trace spans / Cloud Logging eventsSpan/event contentOTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT + ADK_CAPTURE_MESSAGE_CONTENT_IN_SPANS=falseOffNO_CONTENT

The tiers are independent: GCS/BigQuery uploads capture full content whenever their upload vars are set and do not honor OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, which governs the traces/events tier only. Its valid (experimental-semconv) values:

  • NO_CONTENT — no content in spans/events (scaffolded default)
  • EVENT_ONLY — content in Cloud Logging events
  • SPAN_ONLY / SPAN_AND_EVENT — content in trace spans
  • true / falseinvalid; fall back to NO_CONTENT

For the full mechanics (semconv opt-in, declarative Terraform config, env-var table, 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 many third-party observability platforms (via OpenTelemetry or custom instrumentation). The table below covers common ones; the full list is larger (see the pointer below it).

PlatformKey DifferentiatorSetup ComplexitySelf-Hosted Option
AgentOpsSession replays, 2-line setup, replaces native telemetryMinimalNo (SaaS)
Arize AXCommercial platform, production monitoring, evaluation dashboardsLowNo (SaaS)
PhoenixOpen-source, custom evaluators, experiment testingLowYes
MLflowOTel traces to MLflow Tracking Server, span tree visualizationMedium (needs SQL backend)Yes
Monocle1-call setup, VS Code Gantt chart visualizerMinimalYes (local files)
WeaveW&B platform, team collaboration, timeline viewsLowNo (SaaS)
FreeplayPrompt management + evals + observability in one platformLowNo (SaaS)

Ask the user which platform they prefer — present the trade-offs and let them choose. Fetch a platform's setup page at https://adk.dev/integrations/<slug>/index.md (slugs for the table above: agentops, arize-ax, phoenix, mlflow-tracing, monocle, weave, freeplay). ADK has more observability integrations (Datadog, Galileo, LangWatch, Latitude, Future AGI, Respan, Zespan, …) — browse the complete, current list at https://adk.dev/integrations/ (observability topic).


Troubleshooting

IssueSolution
No traces in Cloud TraceVerify fast_api_app.py uses get_fast_api_app(otel_to_cloud=True) (Agent Runtime gates it on GOOGLE_CLOUD_AGENT_ENGINE_ENABLE_TELEMETRY) and the SA has the cloudtrace.agent role
Prompt-response data not appearingCheck LOGS_BUCKET_NAME is set; verify SA has storage.objectCreator on the bucket; check app logs for telemetry setup warnings
Content in traces/events (unwanted)OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=NO_CONTENT keeps content out of spans/events. NOTE: GCS/BigQuery completions still capture full content — to stop that, remove LOGS_BUCKET_NAME/OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK (drop the upload block in service.tf)
BigQuery Analytics not loggingVerify plugin is configured in app/agent.py; check BQ_ANALYTICS_DATASET_ID env var is set
Third-party integration not capturing spansCheck provider-specific env vars (API keys, endpoints); some providers (AgentOps) replace native telemetry
Traces missing tool spansTool execution spans appear under execute_tool — check trace explorer filters
High telemetry costsSwitch 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:

TopicURL
Observability overviewhttps://adk.dev/observability/index.md
Agent activity logginghttps://adk.dev/observability/logging/index.md
Cloud Trace integrationhttps://adk.dev/integrations/cloud-trace/index.md
BigQuery Agent Analyticshttps://adk.dev/integrations/bigquery-agent-analytics/index.md

Related Skills

  • /google-agents-cli-deploy — Deployment targets, CI/CD pipelines, and production workflows
  • /google-agents-cli-workflow — Development workflow, coding guidelines, and operational rules
  • /google-agents-cli-adk-code — ADK Python API quick reference for writing agent code

Frequently asked questions about ADK Observability

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