Deploying a frontend, two APIs, and a database means deciding where each component runs, how it finds the others, and which parts of the system are reachable from outside. A sound starting design keeps the database private, gives each API a stable internal endpoint, and exposes only the frontend unless there is a specific reason to make another service public.
Kubernetes and Docker Compose offer different ways to express that design. The examples below are documented patterns, not a claim that this particular installment uses either platform.
Plan the component boundaries before deploying
Think of the system as four workloads: one frontend, two APIs, and one database. The frontend handles browser-facing traffic and calls the APIs; the APIs perform application work and use the database as needed. The database should normally be reachable only by the workloads that require it.
Deployment has two related but distinct parts: defining the workloads and designing the traffic paths between them. A running container or Pod does not, by itself, give other components a reliable way to locate it. Nor does startup prove that the application is ready to serve requests or that network communication works.
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- Workloads: Define how each application component runs and how it is replaced or replicated.
- Discovery: Give callers stable names rather than relying on changing container or Pod addresses.
- Exposure: Make the frontend public, while keeping APIs and the database internal by default.
- State and configuration: Persist database files independently of a replaceable container, and manage configuration and secrets separately from application images where appropriate.
How the Kubernetes deployment pattern works
Kubernetes separates workload management from service discovery. A Deployment manages application Pods; a Kubernetes Service gives a stable network endpoint and routes requests to matching Pods. The official [Kubernetes frontend-to-backend example](https://kubernetes.io/docs/tasks/access-application-cluster/connecting-frontend-backend/) uses a backend Deployment with three replicas and a Service named hello, selected by labels. Other workloads in the cluster can reach that backend using the Service DNS name hello.
Give each API its own internal Service
For a frontend that calls two APIs, define a workload and an internal Service for each API. The frontend can call the APIs by their Service names instead of needing to know which Pod currently handles a request. Each Service selects the appropriate Pods through labels, so the labels on the workload and the selector on the Service must agree.
The cited Kubernetes example illustrates the same mechanism with one backend: it does not prescribe names, API responsibilities, database setup, or a four-component application architecture. Apply its discovery pattern to the two APIs rather than treating its sample as a complete application blueprint.
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Proxy frontend requests to internal names
In the example, the frontend runs NGINX and proxies incoming requests to the internal DNS name hello. A frontend proxy can use the corresponding Service names for both APIs, keeping browser traffic directed to the public frontend while the frontend communicates with private in-cluster endpoints.
The tutorial builds the NGINX configuration into its image, but notes that a ConfigMap would make the configuration easier to change. Separating runtime configuration from image contents avoids rebuilding the frontend image solely to update an upstream address or related setting.
Expose only the frontend
The example exposes the frontend through a Service of type LoadBalancer; its backend Service is not externally resolvable. This makes the public boundary explicit: outside clients reach the frontend, while internal services call the backend over the cluster network.
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An external load balancer requires a supported environment. Where one is unavailable, the Kubernetes tutorial identifies NodePort as an alternative. The tutorial shows an external address becoming available after provisioning and then demonstrates a curl request returning {"message":"Hello"}; neither that provisioning behavior nor that sample response is guaranteed for every cluster. For a real system, choose the exposure method supported by its hosting environment and keep API and database endpoints private unless external access is intentionally required.
How the Docker Compose deployment pattern works
Docker Compose describes application components as services in a compose.yaml file. Services attached to the same Compose network can reach one another by service name, so an API can use the database service name rather than a container IP address. The [Compose application model documentation](https://docs.docker.com/compose/intro/compose-application-model/) also covers service lifecycle commands, configs, secrets, and persistent volumes.
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Docker’s illustrative topology has a frontend on both a front-tier and back-tier network, while a backend joins only the back-tier. The frontend exposes port 443; the backend is not placed on the front-tier. This is an example, not a mandatory layout. For a frontend, two APIs, and a database, you can apply the same principle by joining components only to networks needed for their communication paths.
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For example, APIs that need database access can share a private network with the database. The frontend can communicate with the APIs on an application network without giving outside clients a direct route to the database. Exact network membership depends on how the application components call one another.
Persist database data and separate sensitive values
The Compose example declares a persistent volume for backend data, along with a configuration object and a secret for an HTTPS certificate. A volume gives data a lifecycle distinct from the container that uses it; without persistent storage, replacing a database container can put its data at risk. A volume alone is not a backup or recovery plan, and the example does not establish production database operating procedures.
Use configuration for non-sensitive runtime settings and secrets for sensitive values, rather than treating either as a substitute for secure handling. The Compose model supports these objects, but the particular certificate and HTTP configuration in Docker’s example are illustrative rather than required for every deployment.
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Connect separate Compose projects deliberately
Service-name discovery applies to services sharing a Compose network. If services live in separate Compose projects, Docker documents creating an external shared network and attaching the relevant services to it. Its hybrid-network example lets an API join both a shared network and an internal network while keeping the database only on the internal network. That arrangement can allow selected cross-project communication without making every service mutually reachable.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose a pattern that fits the deployment scope
| Decision | Docker Compose | Kubernetes |
|---|---|---|
| Typical scope | Defines and operates a multi-container application through a Compose file. | Manages workloads in a cluster; a Deployment manages Pods and a Service provides stable discovery and routing. |
| Service discovery | Services on a shared network can connect using service names. | Services provide stable in-cluster endpoints; the documented example uses a Service DNS name and label selector. |
| External access in the examples | The frontend example exposes port 443; network and host exposure depend on the Compose configuration. | The example uses a frontend LoadBalancer Service; NodePort is identified as an alternative when an external load balancer is unavailable. |
| State and runtime data | The illustrative application model declares a persistent volume for backend data. | Not stated in the cited frontend-to-backend example; it focuses on connecting frontend and backend services. |
| Configuration and secrets | The illustrative model declares a config and a secret. | The tutorial says a ConfigMap could make NGINX configuration easier to change; it does not provide a complete secrets design. |
Compose is a practical way to describe connected containers for an application. Kubernetes adds cluster-level workload management and Service-based routing. Neither choice removes the need to decide which services should be reachable, how database state is protected, or how runtime settings are maintained.
Verify health and networking after startup
Successful startup is only the first check. Confirm that expected services are running, that each is attached to the intended network, and that a caller can reach its destination. Docker’s [Compose networking guide](https://docs.docker.com/compose/how-tos/networking) recommends checking network configuration and attachment before testing live connectivity.
- List service status: Run
docker compose psto inspect the project’s containers and status. - Inspect application output: Run
docker compose logs, or add a service name to focus on one component’s logs. - Check network configuration: Run
docker network inspect NETWORK_NAMEto inspect a network and its attached containers. - Test from the caller’s context: Use
docker compose exec SERVICE_NAME COMMANDto run an appropriate connectivity check from a service container. Test the actual service name and port the application uses.
If a request fails, check that the caller and destination share a network, that the name resolves as expected, and that the application is listening on the target port. In Kubernetes, also check the Service selector against the Pod labels and confirm the intended Service is internal or externally exposed as designed.
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