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What Compose does—and what it does not do
Docker Compose configures and runs an application made up of services. A Compose file describes how containers should be configured and connected, including their networks and volumes. A Dockerfile, by contrast, contains instructions for building an image. Compose does not write your application or turn one command into an agent; it starts and coordinates the components you define.
docker compose up creates and starts the services in the Compose configuration. During development, docker compose up --build also builds services that have a build configuration. Compose is declarative: you change the configuration, then run Compose to bring the application into line with it. Docker’s Compose overview explains the Dockerfile distinction, and the Compose CLI reference documents the command.
Learn the pattern with Flask and Redis
Docker’s Compose Quickstart uses a small Flask web service and Redis counter. The web service reaches Redis by its service name on the Compose network. This makes the example useful for understanding a multi-service application: each component has a job, and Compose gives them a shared way to run and communicate.
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Follow the tutorial’s progression
The Quickstart moves from starting the app to health checks, Compose Watch, volumes, multiple Compose files, logs, and debugging with docker compose exec. Health checks help represent whether a service is ready, rather than merely started. Logs show what a service reports, while exec lets you run a command inside a running service’s container.
Understand what happens to data
A container’s writable layer is removed when that container is removed. In the tutorial, a named volume preserves Redis data across a docker compose down and a later docker compose up. The command docker compose down -v removes volumes too, resetting the tutorial counter. Use it only when you intend to delete the data stored in those volumes.
Rank #2
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Apply the same service model to an agent
Docker’s agentic AI guide presents an agent application as a small stack with three roles:
- Model: provides the capability to reason over a request.
- Agent: coordinates the task and decides how to use available capabilities.
- MCP gateway: connects the agent to tools and services through the Model Context Protocol (MCP).
In Docker’s example, an Auditor coordinates a Critic and a Reviser to fact-check and refine generated answers. That is one demonstrated multi-agent design, not a requirement for every custom agent. A simpler project may use one agent, and the tools it can access depend on how its gateway and services are configured.
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Run the guide’s local example
The guide’s requirements are specific to this example and may change as Docker updates it. As checked on October 4, 2026, Docker specifies Docker Desktop 4.43 or later, Docker Model Runner enabled, at least 3.5 GB of VRAM, and 2.31 GB of storage. Its Compose Quickstart prerequisite is the latest version of Docker Compose and a basic understanding of Docker.
- Meet the guide’s prerequisites and enable Docker Model Runner in Docker Desktop.
- Open a terminal in the guide’s
adk/directory. - Start the application with
docker compose up. - On the first run, allow time for the model to be pulled; then open http://localhost:8080 to use the example.
The command starts the services defined by that project’s Compose configuration. Compose is orchestrating the app, model, and MCP gateway; it is not generating an agent from scratch.
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Check the stack before debugging agent behavior
When the example does not work as expected, first establish whether its services are running and communicating. The following is a practical troubleshooting order based on the service and debugging concepts in Docker’s tutorials; it is not a guaranteed diagnosis for every project.
- Inspect the Compose configuration. Identify the services, their build or image settings, and how they are connected.
- Check service status and health. Confirm that required services are running and, where health checks are configured, healthy.
- Read the logs. Use
docker compose logsto look for startup errors or connection failures. - Debug a running service. Use
docker compose execto inspect a container from within it, following the Quickstart’s approach. - Verify the connections. Check whether the app can reach the model and the MCP gateway before investigating the agent’s task logic.
What changes before production
A local learning example is not production-ready simply because it starts with Compose. Docker’s production guidance describes adjustments that deployments may need, such as different ports and environment variables, a restart policy, and production-specific configuration. It also describes using an additional Compose file and rebuilding or recreating services when code changes. Treat those as deployment considerations to evaluate for your own application, not as proof that the tutorial’s sample is secure or scalable.
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Design choices to make for your own agent
Docker’s example documents a local model and a multi-agent workflow, while the Compose Quickstart demonstrates persistent state with a named volume. Those examples suggest useful questions for your design, rather than universal best answers:
Quick Recap
- Local or remote model: decide where inference should run and what that means for your setup and deployment.
- Single agent or multiple agents: use multiple roles only when the task benefits from that coordination; the Auditor, Critic, and Reviser are one example.
- Persistent or disposable state: choose whether data should survive container replacement, and make volume deletion an intentional operation.
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