google-agents-cli-observability

por google

Esta habilidade deve ser usada quando o usuário deseja "configurar rastreamento", "monitorar meu agente ADK", "configurar registro", "adicionar observabilidade", "depurar tráfego de produção" ou precisar de orientação sobre monitoramento de agentes ADK (Agent Development Kit) implantados. Abrange Cloud Trace, registro de prompt-resposta, BigQuery Agent Analytics, integrações de terceiros (AgentOps, Phoenix, MLflow, etc.) e solução de problemas. Parte do conjunto de habilidades do Google ADK (Agent Development Kit). NÃO usar para configuração de implantação (use...

npx skills add https://github.com/google/agents-cli --skill google-agents-cli-observability

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

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

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

Setup by Deployment Type

DeploymentSetup
Agent RuntimeAutomatic — 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 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 (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.

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. For setup details, fetch the relevant ADK docs page from the Deep Dive table below.


Troubleshooting

IssueSolution
No traces in Cloud TraceVerify otel_to_cloud=True in FastAPI app; check service account has 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
Privacy mode misconfiguredCheck OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT value — use NO_CONTENT for metadata-only, false to disable
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
AgentOpshttps://adk.dev/integrations/agentops/index.md
Arize AXhttps://adk.dev/integrations/arize-ax/index.md
Phoenix (Arize)https://adk.dev/integrations/phoenix/index.md
MLflow tracinghttps://adk.dev/integrations/mlflow-tracing/index.md
Monoclehttps://adk.dev/integrations/monocle/index.md
W&B Weavehttps://adk.dev/integrations/weave/index.md
Freeplayhttps://adk.dev/integrations/freeplay/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

Mais skills de google

google-agents-cli-adk-code
google
Esta habilidade deve ser usada quando o usuário deseja "escrever código de agente", "criar um agente com ADK", "adicionar uma ferramenta", "criar um callback", "definir um agente", "usar gerenciamento de estado" ou precisar de padrões de API Python e exemplos de código do ADK (Agent Development Kit). Faz parte do conjunto de habilidades do Google ADK. Fornece uma referência rápida para tipos de agente, definições de ferramentas, padrões de orquestração, callbacks e gerenciamento de estado. NÃO use para criar novos projetos (use google-agents-cli-scaffold) ou implantação...
developmentapicode-review
google-agents-cli-eval
google
Esta habilidade deve ser usada quando o usuário deseja "executar uma avaliação", "avaliar meu agente ADK", "escrever um conjunto de dados de avaliação", "analisar falhas de avaliação", "comparar resultados de avaliação", "otimizar agente" ou precisar de orientação sobre a metodologia de avaliação do Agent Platform e o Quality Flywheel. Abrange métricas de avaliação, esquema de conjunto de dados, pontuação LLM-como-juiz e causas comuns de falha. NÃO use para padrões de código de API (use google-agents-cli-adk-code), implantação (use google-agents-cli-deploy) ou scaffolding de projeto (use...
developmenttestingdata-analysis
google-agents-cli-workflow
google
Esta habilidade deve ser usada quando o usuário deseja "desenvolver um agente", "criar um agente usando ADK", "executar o agente localmente", "depurar código do agente", "testar um agente", "implantar um agente", "publicar um agente", "monitorar um agente", ou precisar do ciclo de vida de desenvolvimento e diretrizes de codificação do ADK (Agent Development Kit). Ponto de entrada para criar agentes ADK. Sempre ativo — fornece o fluxo de trabalho completo (scaffold, build, evaluate, deploy, publish, observe), regras de preservação de código, orientação de seleção de modelo e...
developmentdevopstesting
google-agents-cli-deploy
google
Esta habilidade deve ser usada quando o usuário deseja "implantar um agente", "implantar meu agente ADK", "configurar CI/CD", "configurar segredos", "solucionar problemas de uma implantação" ou precisar de orientação sobre Agent Runtime, Cloud Run ou destinos de implantação no GKE. Abrange fluxos de trabalho de implantação, contas de serviço, reversão e infraestrutura de produção. Faz parte do conjunto de habilidades do Google ADK (Agent Development Kit). NÃO use para padrões de código de API (use google-agents-cli-adk-code), avaliação (use google-agents-cli-eval) ou...
developmentdevops
google-agents-cli-scaffold
google
This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the Google ADK (Agent Development Kit) skills suite. Covers `agents-cli scaffold create`, `scaffold enhance`, and `scaffold upgrade` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (use...
developmentdevops
google-agents-cli-publish
google
Esta habilidade deve ser usada quando o usuário deseja "publicar um agente", "publicar meu agente ADK", "registrar um agente no Gemini Enterprise", "publicar no Gemini Enterprise" ou precisar de orientação sobre o comando agents-cli publish gemini-enterprise. Abrange modos de registro ADK vs A2A, uso programático e interativo, referência de flags, detecção automática a partir de metadados de implantação e solução de problemas. Parte do conjunto de habilidades do Google ADK (Agent Development Kit). NÃO use para implantação (use...
developmentdevopsapi