Deploying a frontend, two APIs, and a database means deciding both where each component runs and which network paths it can use. A sound starting design keeps the database and APIs private, gives services stable internal names, and exposes only the frontend. Kubernetes and Docker Compose both support that pattern, though they model workloads and networking differently.
Map the components before deploying them
Think of the application as four workloads: one frontend, two API services, and one database. The frontend receives browser traffic and calls the APIs; the APIs access the database. The database should not be directly reachable from the public internet merely because the application needs it internally.
Draw the intended paths first: public client to frontend; frontend to each API; APIs to database. This makes the exposure boundary explicit and helps distinguish a service that needs a stable internal address from one that needs a public entry point. The exact API responsibilities, database engine, images, and cloud provider depend on the application; the deployment patterns below do not prescribe them.
Choose an orchestration model for the environment
| Decision area | Docker Compose | Kubernetes |
|---|---|---|
| Scope | Defines and runs a multi-container application, commonly on one Docker host. | Manages workloads and networking in a cluster. |
| Service discovery | Services on a shared Compose network can reach each other by service name. | A Service provides stable in-cluster discovery and routes to Pods selected by labels. |
| External access | Publish a host port on the frontend, or connect it to an externally shared network as appropriate. | Configure the frontend Service as LoadBalancer where supported, or use NodePort where that is the chosen access method. |
| Persistent data | The application model can declare a volume for database data; persistence still requires a backup and recovery plan. | Persistent storage must be designed for the cluster and database; the cited frontend/backend example does not define database storage operations. |
| Configuration and secrets | Compose can declare configs and secrets separately from service definitions. | Runtime configuration can be separated from an image, for example with a ConfigMap for NGINX configuration. |
These are different operating models, not interchangeable guarantees of production readiness. Compose is a straightforward way to describe cooperating containers; Kubernetes adds cluster-level workload management. Pick based on where the application must run and how that environment is operated.
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How Kubernetes separates workload management from networking
Deploy APIs as workloads, then give them stable Services
A Kubernetes Deployment manages application Pods, including their desired replica count. A Service does a different job: it selects matching Pods and gives clients a stable network identity. Pods can be replaced, so clients should use the Service rather than depend on an individual Pod address.
In Kubernetes’ documented example, a backend Deployment runs three replicas and a Service named hello selects them using labels. Other workloads in the cluster can discover that backend by the Service DNS name hello and send traffic to it. For an application with two APIs, define a workload and an internal Service for each API, using distinct names and selectors that match only the intended Pods. The example’s three replicas illustrate the mechanism; they are not a sizing recommendation for your APIs. Kubernetes’ frontend/backend Services example documents the pattern.
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Make the frontend the public boundary
The Kubernetes example runs NGINX as the frontend and configures it to proxy requests to the backend Service using the internal DNS name hello. Its frontend Service is configured as type: LoadBalancer, while the backend Service is not externally resolvable. Applied to four components, the same boundary means exposing the frontend and keeping both APIs and the database on internal paths unless a separate, justified access requirement exists.
An external LoadBalancer address depends on a supported environment and provisioning by its infrastructure; Kubernetes’ tutorial shows an address becoming available, but that timing is not a universal guarantee. If an external load balancer is unavailable, the documentation identifies NodePort as an alternative. Choose the access method that matches the cluster and its surrounding network rather than assuming every cluster can provision a public load balancer. The Kubernetes task also notes that its NGINX configuration is baked into the image and that a ConfigMap can make configuration changes easier.
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How Compose services find one another
Use shared networks to express allowed paths
A Compose application is described in a compose.yaml file as a set of services. Services attached to the same Compose network can resolve one another by service name. A useful topology is to put the frontend on a front-facing network and an API-facing network, APIs on the API-facing network and a database-facing network, and the database only on the database-facing network. This is a design example, not a mandatory Compose layout.
Docker’s example uses front-tier and back-tier networks: the frontend joins both, while the backend joins only the back-tier. It also demonstrates a persistent volume for backend data, a config for HTTP settings, and a secret for an HTTPS certificate. These objects let the application model distinguish data persistence and runtime configuration from the container image. They do not by themselves provide database backups, secret rotation, or a complete production security policy. See Docker’s Compose application model.
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Keep separate projects connected deliberately
Services in separate Compose projects do not automatically share a network. Docker documents creating an external network and attaching services from each project to it when cross-project communication is needed. Its hybrid-network example lets an API join a shared network and an internal network while the database remains on the internal network. That is useful when components are deployed independently but the database should not join the shared path. Docker’s Compose networking guide explains service-name discovery and network setup.
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Give database data persistent storage
A database container’s writable filesystem is not a data-retention strategy. In Compose, declare persistent storage and mount it at the database’s data location; the Docker example illustrates a volume for backend data. In Kubernetes, choose an appropriate persistent-storage arrangement for the database workload. In either environment, persistence and backup are separate concerns: a volume can preserve data across container replacement, but it does not establish that the data can be restored after loss or corruption.
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Keep changeable settings out of image contents
Embedding an upstream hostname or other environment-specific setting in an image makes changes require a new image build or a more involved rollout. Kubernetes’ NGINX example explicitly bakes its proxy configuration into the image and points to a ConfigMap as a more manageable alternative. Compose likewise supports config and secret objects. Keep non-secret runtime settings distinct from credentials and certificates, and avoid treating a configuration mechanism as a substitute for secret access controls.
Verify startup, service discovery, and live traffic
A running container or Pod does not prove that a request can traverse the intended network path. Check each boundary in sequence: whether services are running, whether they are attached to the expected network, whether names resolve from the caller’s environment, and whether the receiving process accepts the connection.
- Check service status. In Compose, run
docker compose psto inspect the project’s containers and status. - Inspect startup output. Run
docker compose logsto look for configuration errors, failed connections, or application startup problems. - Confirm network attachment. Use
docker network inspectto examine network membership and configuration; verify the relevant services are on a common network. - Test from the caller’s context. Use
docker compose execto run a connectivity or name-resolution check from a service container, where available. Testing from the host alone may not exercise the same network path. - Follow the request path. Confirm frontend-to-API connectivity, then API-to-database connectivity, rather than inferring end-to-end health from one successful check.
Docker’s guidance emphasizes checking network configuration, container attachment, and live connectivity. The commands above are inspection aids; the precise test utility available inside a container depends on its image. Docker’s networking guide and Compose application model overview describe the relevant Compose features and commands.
What this deployment pattern does not decide
The examples establish ways to define workloads, discover services, set network boundaries, and represent persistent data and configuration. They do not determine the right replica counts, database engine, cloud provider, TLS termination design, health-check policy, migration process, secret-rotation schedule, backup retention, or availability objective for a particular application. Those choices require the application’s requirements and the capabilities of the target environment; they should be made explicitly rather than inferred from a hello-world topology.
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