Microservices do not become deployable merely because they are split into smaller repositories or directories. The real test arrives when each service needs its own runtime, configuration, network access, database connection, health check, and release path. Docker gives PHP teams a disciplined way to package those concerns so that a service behaves predictably from a developer laptop to a production platform.

The goal is not to put every moving part into containers for its own sake. It is to create a repeatable operating boundary: the same PHP version, required extensions, application code, and startup command travel together. That consistency reduces a familiar category of failure: code that was correct, but ran in an environment that was subtly different.

Start with a small, explicit PHP image

A microservice image should contain what the service needs to run and little else. For a typical PHP HTTP service, that means a PHP runtime, necessary extensions, Composer dependencies, application code, and an entry command. Development-only tooling should not casually leak into the production image.

A multi-stage build keeps Composer available during dependency installation without making it part of the final runtime image.

FROM composer:2 AS dependencies

WORKDIR /app
COPY composer.json composer.lock ./
RUN composer install --no-dev --prefer-dist --no-interaction --no-scripts

FROM php:8.3-cli

WORKDIR /app
COPY --from=dependencies /app/vendor /app/vendor
COPY . .

EXPOSE 8080
CMD ["php", "-S", "0.0.0.0:8080", "-t", "public"]

This example is intentionally simple. The built-in PHP server can be useful for a small service or local workflow, but production HTTP handling often uses PHP-FPM behind a web server or a platform-managed process model. The important design choice is that the container command is explicit and matches the way the service is intended to run.

Copy dependency manifests before the application source. Docker can then reuse the dependency-installation layer when only application code changes. That makes iterative builds faster while preserving reproducibility through composer.lock.

Define contracts between services

Containers make services easy to start; they do not define how services should depend on one another. That is an architectural responsibility. A PHP service should know its upstream dependencies through configuration, not through hard-coded hostnames, credentials, or assumptions about local infrastructure.

For local development, Docker Compose is useful for describing a small system and its service-to-service network.

services:
  orders:
    build: ./orders
    environment:
      DATABASE_URL: "mysql://app:secret@db:3306/orders"
      INVENTORY_BASE_URL: "http://inventory:8080"
    depends_on:
      db:
        condition: service_healthy
    ports:
      - "8080:8080"

  inventory:
    build: ./inventory

  db:
    image: mysql:8
    environment:
      MYSQL_DATABASE: orders
      MYSQL_USER: app
      MYSQL_PASSWORD: secret
      MYSQL_ROOT_PASSWORD: root-secret
    healthcheck:
      test: ["CMD", "mysqladmin", "ping", "-h", "localhost"]
      interval: 5s
      timeout: 3s
      retries: 10

Within this network, inventory and db are service names that resolve as hostnames. That is convenient locally, but the broader lesson matters more: configuration should express dependency endpoints, and deployment environments should supply the correct values.

Also distinguish between “the container started” and “the dependency is ready.” A database process may exist while it is still initializing. Compose health checks can improve local startup behavior, but an application should still handle transient connection failures. A short, bounded retry with backoff is reasonable during startup; infinite retries that hide a bad configuration are not.

Keep the service stateless

Containers are replaceable by design. Treating their local filesystem as durable storage creates trouble during scaling, redeployments, and recovery. Store durable data in the appropriate external system: relational data in a database, shared files in object or network storage, and transient coordination state in a purpose-built service when needed.

This principle also clarifies database migrations. Do not make every application replica race to run migrations during startup. Run migrations as a separate deployment step or a dedicated one-off job, then start the new application version. That separation makes failures visible and prevents a horizontal scale-out event from becoming a schema-management event.

Configuration is an interface, not a convenience

Environment variables are a practical delivery mechanism for non-secret configuration such as ports, log levels, feature switches, and service URLs. Secrets need tighter handling: inject them through the deployment platform or an approved secret-management mechanism, avoid committing them to Compose files, and never bake them into an image layer.

Validate required configuration when the process starts. A service that cannot connect because DATABASE_URL is missing should fail clearly rather than continue with an implicit fallback. Clear failures shorten incident response and keep development and production behavior aligned.

Build for observability and graceful failure

In a distributed system, a request can fail after it leaves your service. Timeouts, structured logs, correlation identifiers, and meaningful health endpoints turn that uncertainty into something operators can diagnose. Every outbound HTTP call should have a timeout. Without one, a slow downstream dependency can consume worker capacity until the service appears unavailable.

Retries require judgment. Retrying a read request after a temporary network failure may be appropriate. Retrying a non-idempotent operation, such as creating an order, can produce duplicates unless the receiving service supports an idempotency key. The safe default is to retry only when the operation and failure mode make duplicate execution acceptable.

Expose health information with care. A liveness endpoint should answer whether the process can continue running. A readiness endpoint should answer whether it can safely receive traffic. If the service must reach a database before it can serve requests, readiness may reflect that dependency; liveness usually should not turn a temporary database outage into continuous container restarts.

Make deployment boring on purpose

A reliable deployment pipeline builds one immutable image, tests it, tags it with a traceable version identifier, and promotes that exact artifact through environments. Rebuilding from a branch for each environment introduces avoidable uncertainty: the supposedly same release may contain different dependency resolution, base-image contents, or source state.

• Run unit and integration tests before publishing the release image.
• Scan and update base images through a deliberate maintenance process.
• Use configuration and secrets supplied by each environment, not altered image contents.
• Deploy compatible application and schema changes in a sequence that supports rollback.
• Watch error rate, latency, and logs during rollout before widening traffic.

Schema compatibility deserves special attention. A safer pattern is additive first: add a nullable column or new table, deploy code that can work with both old and new shapes, backfill if necessary, then remove obsolete structures in a later release. Docker standardizes the runtime, but it cannot make an incompatible database change reversible.

The container is the beginning of the operational design

Dockerizing PHP microservices is valuable because it makes runtime assumptions concrete. It encourages small images, explicit dependencies, repeatable builds, and portable deployment artifacts. But containers do not erase distributed-systems concerns. They make those concerns visible enough to design well.

The strongest result is not a clever Compose file or the smallest possible image. It is a service that starts predictably, fails clearly, keeps its state in the right place, and can be replaced without drama. When every PHP microservice follows those habits, orchestration becomes less about fighting the platform and more about delivering changes with confidence.