Deploy Your First Agent: Free Google ADK Deployment Course

Deploying an agent means deciding how it runs beyond your local development session. Deploy Your First Agent follows a Google Agent Development Kit workflow from local execution toward hosted runtime options, including Agent Runtime and Cloud Run. It provides a more procedural route than a general agent architecture overview.

The course is advertised at about one hour and fifteen minutes and at Google’s Advanced level, shown here as Professional. The reviewed instruction includes several modules and quizzes, so prepare to follow technical concepts rather than expect a first introduction to AI.

Course at a glance

What you’ll learn

• Follow an ADK agent’s progression from local execution toward a hosted service.
• Explore deployment concepts involving Agent Runtime and Cloud Run.
• Understand the distinction between a session and information retained across sessions.
• Examine Memory Bank as an optional part of the broader workflow.

Skills you’ll gain

• Agent deployment planning
• Runtime selection
• Session-state reasoning
• Memory-design awareness

Know what changes after localhost

A local agent is under the developer’s immediate control. A hosted agent needs a defined entry point, appropriate permissions and an environment that can keep serving requests. Follow how the instructional modules move through those concerns and identify which choices affect the application itself versus its hosting configuration.

For optional preparation, document the agent’s dependencies, the configuration it needs and the actions it may perform. Note which values should remain secret and which are ordinary settings. This independent checklist can make the deployment material easier to follow, but it is not a provider-completed readiness assessment.

Separate session state from longer-term memory

State and memory answer different questions. A session may need enough context to complete a current interaction, while retaining information across sessions introduces additional design choices. The course’s optional Memory Bank discussion should be considered in relation to the actual application rather than added automatically to every agent.

An optional review exercise is to list what the agent needs to remember for one interaction and what, if anything, should persist afterward. Consider user expectations, permission and deletion requirements. Avoid retaining sensitive information simply because a feature makes it possible. These are planning questions, not a promise that the course configures all privacy controls.

Choose a first deployment that you can inspect

This course is suited to learners with some agent-development and cloud application context who want a concrete deployment sequence. The Professional label reflects the provider’s Advanced level; it is not a professional qualification or a guarantee of independent deployment competence after completion.

Use a non-critical example for any optional live experiment and define how you will check a response, a failure and a new version. Review current product documentation before applying a step to a real environment. Deployment success should mean more than a service responding once: it should also leave you able to understand and manage what has been deployed.

Free learning and practical access

The complete advertised course instruction and quizzes are free with a free Google Skills account. Agent Runtime, Cloud Run, model calls and optional memory services are separate cloud products and may incur charges. No subscription, payment card or trial is required to study the instructional route. This listing does not promise a funded cloud lab or included production hosting. Google advertises a course completion badge after the required activities. It is not a professional certification or academic credit.

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