From interaction to insight: Announcing BigQuery Agent Analytics for the Google ADK

In a world of agentic AI, building an agent is only half the battle. The other half is understanding how users are interacting with it. What are their most common requests? Where do they get stuck? What paths lead to successful outcomes? Answering these questions is the key to refining your agent and delivering a better user experience. These insights are also super critical for optimizing agent performance.

Today, we're making it easier for agent developers in Google’s Agent Development Kit (ADK) to answer these questions. With a single line of code, ADK developers can stream agent interaction data directly to BigQuery and get insights into their agent activity in a scalable manner. To do so, we are introducing BigQuery Agent Analytics, a new plugin for ADK that exports your agent's interaction data directly into BigQuery to capture, analyze, and visualize agent performance, user interaction, and cost.

With your agent interaction data centralized in BigQuery, analyzing critical metrics such as latency, token consumption, and tool usage is straightforward. Creating custom dashboards in tools like Looker Studio or Grafana is easy. Furthermore, you can leverage cutting-edge BigQuery capabilities including generative AI functions, vector search, and embedding generation, to perform sophisticated analysis. This enables you to cluster agent interactions, precisely gauge agent performance, and rapidly pinpoint common user queries or systemic failure patterns — all of which are essential for refining the agent experience. You can also join interaction data with relevant business datasets — for instance, linking support agent interactions with CSAT scores — to accurately measure the agent's real-world impact. This entire capability is unlocked with a minimal code change.

This plugin is available in preview for ADK users today, with support for other agent frameworks soon to follow.

See the plugin in action in the following video.

Understanding BigQuery Agent Analytics

The BigQuery Agent Analytics plugin is a very lightweight way of streaming various agent activity data directly to your BigQuery table. It consists of three main components:

• ADK Plugin: With a single line of code, the new ADK plugin can stream agent activity like requests, responses, LLM tool calls, etc. to a BigQuery table.

• Predefined BigQuery schema: We provide an optimized table schema out-of-the-box that stores rich details about user interactions, agent responses, and tool usage.

• Low-cost, high-performance streaming: The plugin uses the BigQuery Storage Write API to stream events directly to BigQuery in real-time.

Why it matters: Data-driven agent development

By integrating your agent's analytic data in BigQuery, you can go from viewing basic metrics to generating deep, actionable insights. Specifically, this integration lets you:

• Visualize agent usage and interactions: Gain a clear understanding of your agent's performance. Easily track key operational metrics like token consumption and tool usage to monitor costs and resource allocation. 

• Evaluate agent quality with advanced AI: Go beyond simple metrics by using BigQuery's advanced AI capabilities. Leverage AI functions and vector search to perform quality analysis on conversation data, identifying areas for improvement with greater precision. 

• Learn by conversing with your agent data: Create a conversational data agent that works directly with your new observability data. This allows you and your team to ask questions about your agent activity in natural language and get immediate insights, without writing complex queries. 

How It works

We've designed the process of setting up robust analytics pipeline to be as simple as possible:

1. Add the required code: This plugin requires use of ADK’s application(apps) component when building the agent. The following code demonstrates how to initialize the new plugin and make it part of your app.

2. Choose what to stream and customize pre-processing: You have full control over what data you send to BigQuery. Choose the specific events you want to stream, so that you only capture the data that is most relevant to your needs. The following code example redacts dollar amounts before logging.

And that’s it — the plugin handles the rest, including auto-creating the necessary BigQuery table with the correct schema, and streaming the agent data in real-time. 

Now you are ready to analyze your agent metrics, using familiar BigQuery semantics. Here is an illustration of your logs as they appear in the BigQuery table using a “select * limit 10” on non-empty columns.

Get started today

It's time to unlock the full potential of your agents. With the new BigQuery Agent Analytics you can answer critical usage questions to refine your agent, optimize performance, and deliver a superior user experience.There is more to come in the near future, including integration with LangGraph to advanced analysis for multimodal agent interactions.

To get started, check out the Google Cloud BigQuery Agent Analytics documentation on the Google ADK site. For a guided walkthrough on using this plugin, we invite you to explore our comprehensive new codelab.

We’re excited to see the amazing, data-driven conversational experiences you build.