Google ADK Observability & Monitoring with OpenTelemetry

Google has released a guide for setting up observability and monitoring for its Agent Development Kit (ADK) using OpenTelemetry, enabling developers to capture traces, logs, and metrics from AI agent applications. The integration with SigNoz provides unified dashboards and alerts to improve the reliability and responsiveness of AI agent workflows. The setup requires a SigNoz account, Python 3.10+, and a Google Gemini API key.

What is Google ADK Observability? Google ADK observability gives you full visibility into your AI agent applications by capturing traces, logs, and metrics with OpenTelemetry https://opentelemetry.io/ . This guide walks you through setting up Google ADK monitoring and exporting all three signals to SigNoz. With full Google ADK observability in SigNoz, you can correlate traces, logs, and metrics in unified dashboards, set alerts on latency and errors, and gain actionable insights to continuously improve the reliability and responsiveness of your AI agent workflows. Prerequisites - A SigNoz Cloud account https://signoz.io/teams/ with an active ingestion key or Self Hosted SigNoz instance https://signoz.io/docs/install/self-host/ - Internet access to send telemetry data to SigNoz Cloud - Python 3.10+ with google-adk installed - For Python: pip installed for managing Python packages - A Google Gemini API key. You can get it from Google AI Studio platform https://aistudio.google.com/app/api-keys Set Up Google ADK Monitoring with OpenTelemetry For more information on getting started with Google ADK in your Python environment, refer to the Google ADK Python quickstart guide https://google.github.io/adk-docs/get-started/python/ . Step 1: Install dependencies pip install \ opentelemetry-api \ opentelemetry-sdk \ opentelemetry-exporter-otlp \ opentelemetry-instrumentation-httpx \ opentelemetry-instrumentation-system-metrics \ google-adk \ openinference-instrumentation-google-adk Step 2: Create an agent project Run the adk create command to start a new agent project. adk create my agent Step 3: Update the .env file Update the .env file in your generated module to include your generated Gemini API key: GOOGLE API KEY=<YOUR API KEY Step 4: Import the necessary modules in your generated agent.py Traces: python from opentelemetry import trace from opentelemetry.sdk.resources import Resource from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import BatchSpanProcessor from opentelemetry.exporter.otlp.proto.http.trace exporter import OTLPSpanExporter from openinference.instrumentation.google adk import GoogleADKInstrumentor Logs: python from opentelemetry.sdk. logs import LoggerProvider, LoggingHandler from opentelemetry.sdk. logs.export import BatchLogRecordProcessor from opentelemetry.exporter.otlp.proto.http. log exporter import OTLPLogExporter from opentelemetry. logs import set logger provider import logging Metrics: python from opentelemetry.sdk.metrics import MeterProvider from opentelemetry.exporter.otlp.proto.http.metric exporter import OTLPMetricExporter from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader from opentelemetry import metrics from opentelemetry.instrumentation.system metrics import SystemMetricsInstrumentor from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor Step 5: Set up Traces python from opentelemetry.sdk.resources import Resource from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import BatchSpanProcessor from opentelemetry.exporter.otlp.proto.http.trace exporter import OTLPSpanExporter from opentelemetry import trace from openinference.instrumentation.google adk import GoogleADKInstrumentor import os resource = Resource.create {"service.name": "<service name "} provider = TracerProvider resource=resource span exporter = OTLPSpanExporter endpoint= os.getenv "OTEL EXPORTER TRACES ENDPOINT" , headers={"signoz-ingestion-key": os.getenv "SIGNOZ INGESTION KEY" }, processor = BatchSpanProcessor span exporter provider.add span processor processor trace.set tracer provider provider GoogleADKInstrumentor .instrument is the name of your service <service name → SigNoz Cloud trace endpoint with appropriate OTEL EXPORTER TRACES ENDPOINT region https://signoz.io/docs/ingestion/signoz-cloud/overview/ endpoint : https://ingest.<region .signoz.cloud:443/v1/traces → Your SigNoz SIGNOZ INGESTION KEY ingestion key https://signoz.io/docs/ingestion/signoz-cloud/keys/ Using self-hosted SigNoz? Most steps are identical. To adapt this guide, update the endpoint and remove the ingestion key header as shown in Cloud → Self-Hosted https://signoz.io/docs/ingestion/cloud-vs-self-hosted cloud-to-self-hosted . Step 6: Set up Metrics python from opentelemetry.sdk.resources import Resource from opentelemetry.sdk.metrics import MeterProvider from opentelemetry.exporter.otlp.proto.http.metric exporter import OTLPMetricExporter from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader from opentelemetry import metrics from opentelemetry.instrumentation.system metrics import SystemMetricsInstrumentor import os resource = Resource.create {"service.name": "<service name "} metric exporter = OTLPMetricExporter endpoint= os.getenv "OTEL EXPORTER METRICS ENDPOINT" , headers={"signoz-ingestion-key": os.getenv "SIGNOZ INGESTION KEY" }, reader = PeriodicExportingMetricReader metric exporter metric provider = MeterProvider metric readers= reader , resource=resource metrics.set meter provider metric provider meter = metrics.get meter name turn on out-of-the-box metrics SystemMetricsInstrumentor .instrument HTTPXClientInstrumentor .instrument is the name of your service <service name → SigNoz Cloud endpoint with appropriate OTEL EXPORTER METRICS ENDPOINT region https://signoz.io/docs/ingestion/signoz-cloud/overview/ endpoint : https://ingest.<region .signoz.cloud:443/v1/metrics → Your SigNoz SIGNOZ INGESTION KEY ingestion key https://signoz.io/docs/ingestion/signoz-cloud/keys/ Using self-hosted SigNoz? Most steps are identical. To adapt this guide, update the endpoint and remove the ingestion key header as shown in Cloud → Self-Hosted https://signoz.io/docs/ingestion/cloud-vs-self-hosted cloud-to-self-hosted . SystemMetricsInstrumentor provides system metrics CPU, memory, etc. , and HTTPXClientInstrumentor provides outbound HTTP request metrics such as request duration. If you want to add custom metrics to your Google ADK application, see Python Custom Metrics https://signoz.io/opentelemetry/python-custom-metrics/ . Step 7: Set up Logs python import logging from opentelemetry.sdk.resources import Resource from opentelemetry. logs import set logger provider from opentelemetry.sdk. logs import LoggerProvider, LoggingHandler from opentelemetry.sdk. logs.export import BatchLogRecordProcessor from opentelemetry.exporter.otlp.proto.http. log exporter import OTLPLogExporter import os resource = Resource.create {"service.name": "<service name "} logger provider = LoggerProvider resource=resource set logger provider logger provider otlp log exporter = OTLPLogExporter endpoint= os.getenv "OTEL EXPORTER LOGS ENDPOINT" , headers={"signoz-ingestion-key": os.getenv "SIGNOZ INGESTION KEY" }, logger provider.add log record processor BatchLogRecordProcessor otlp log exporter Attach OTel logging handler to root logger handler = LoggingHandler level=logging.INFO, logger provider=logger provider logging.basicConfig level=logging.INFO, handlers= handler logger = logging.getLogger name Enable httpx logging to capture HTTP requests httpx logger = logging.getLogger "httpx" httpx logger.setLevel logging.DEBUG httpx logger.addHandler handler is the name of your service <service name → SigNoz Cloud endpoint with appropriate OTEL EXPORTER LOGS ENDPOINT region https://signoz.io/docs/ingestion/signoz-cloud/overview/ endpoint : https://ingest.<region .signoz.cloud:443/v1/logs → Your SigNoz SIGNOZ INGESTION KEY ingestion key https://signoz.io/docs/ingestion/signoz-cloud/keys/ Using self-hosted SigNoz? Most steps are identical. To adapt this guide, update the endpoint and remove the ingestion key header as shown in Cloud → Self-Hosted https://signoz.io/docs/ingestion/cloud-vs-self-hosted cloud-to-self-hosted . Step 8: Run your Google ADK Agent Ensure you have completed the steps above traces, logs, and metrics configuration before running your agent. All OpenTelemetry instrumentation must be initialized first. Run with command-line interface Run your agent using the adk run command-line tool. adk run my agent Run with web interface The ADK framework provides a web interface you can use to test and interact with your agent. You can start the web interface using the following command: adk web --port 8000 View Google ADK Traces, Logs, and Metrics in SigNoz Once configured, your Google ADK application automatically emits traces, logs, and metrics. Google ADK traces are available in SigNoz under the Traces tab: When you click on a trace in SigNoz, you'll see a detailed view of the trace, including all associated spans, along with their events and attributes. Google ADK logs are available in SigNoz under the Logs tab. You can also view correlated logs by clicking the "Related Logs" button in the trace view: When you click on any of these logs in SigNoz, you'll see a detailed view of the log, including attributes: Google ADK metrics are available in SigNoz under the Metrics tab: When you click on any of these metrics in SigNoz, you'll see a detailed view of the metric, including attributes: Troubleshooting Google ADK Observability Troubleshooting Google ADK Observability troubleshooting-google-adk-observability If you don't see your telemetry data: Verify network connectivity - Ensure your application can reach SigNoz Cloud endpoints Check ingestion key - Verify your SigNoz ingestion key is correct Wait for data - OpenTelemetry batches data before sending, so wait 10-30 seconds after making API calls Try a console exporter — Enable a console exporter locally to confirm that your application is generating telemetry data before it’s sent to SigNoz Google ADK Dashboard You can also import our prebuilt Google ADK dashboard https://signoz.io/docs/dashboards/dashboard-templates/google-adk-dashboard/ , which provides specialized visualizations for monitoring your Google ADK usage in applications. The dashboard includes pre-built charts specifically tailored for LLM usage, along with import instructions to get started quickly. Setup OpenTelemetry Collector Optional Setup OpenTelemetry Collector Optional setup-opentelemetry-collector-optional What is the OpenTelemetry Collector? Think of the OTel Collector as a middleman between your app and SigNoz. Instead of your application sending data directly to SigNoz, it sends everything to the Collector first, which then forwards it along. Why use it? Cleaning up data — Filter out noisy traces you don't care about, or remove sensitive info before it leaves your servers. Keeping your app lightweight — Let the Collector handle batching, retries, and compression instead of your application code. Adding context automatically — The Collector can tag your data with useful info like which Kubernetes pod or cloud region it came from. Future flexibility — Want to send data to multiple backends later? The Collector makes that easy without changing your app. See Switch from direct export to Collector https://signoz.io/docs/opentelemetry-collection-agents/opentelemetry-collector/switch-to-collector/ for step-by-step instructions to convert your setup. For more details, see Why use the OpenTelemetry Collector? https://signoz.io/docs/opentelemetry-collection-agents/opentelemetry-collector/why-to-use-collector/ and the Collector configuration guide https://signoz.io/docs/opentelemetry-collection-agents/opentelemetry-collector/configuration/ . Additional resources: - Set up alerts https://signoz.io/docs/product-features/alert-management for high latency or error rates - Learn more about querying traces https://signoz.io/docs/product-features/trace-explorer - Explore log correlation https://signoz.io/docs/product-features/logs-explorer