Multiple Environments in Docker

Published on 17 Sep 2025 by Adam Lloyd-Jones

In the dynamic world of software development, ensuring that an application behaves identically across various stages—from a developer’s local machine to a testing server and finally, live in production—is a persistent challenge. This consistency is paramount for reliable software delivery and reducing the infamous “it works on my machine” syndrome. Docker, an indispensable and ubiquitous tool, has revolutionized how we build, package, and deploy software, offering a robust solution to this multi-environment dilemma. It acts as a universal package manager, encapsulating applications and their dependencies into portable, self-sufficient containers. This article will delve into Docker’s comprehensive approaches to managing multiple environments, highlighting its role in streamlining workflows from development to production.

Why multiple environments are essential and challenging

Modern software development often involves several distinct environments:

Development: Where developers write and test code locally.
Testing/QA: Where automated and manual tests are run to ensure quality.
Staging/Pre-production: A near-production environment for final validation.
Production: The live environment where end-users interact with the application.

Traditionally, managing these environments was fraught with inconsistencies due to differing operating systems, libraries, and configurations. Applications built as monoliths often made these issues worse, encouraging monolithic architecture throughout the code and data layers, making interface design a chore. Microservices, while offering benefits like independent deployment, can introduce complexity if not managed correctly across these environments. Docker directly addresses this by providing a standardized runtime environment, ensuring consistency across all stages.

Docker as the universal package manager

Docker’s core strength lies in its ability to package microservices into immutable images, which are bootable snapshots of a server, including all necessary code, dependencies, and assets. These images can then be instantiated as containers, which are virtualized servers providing an isolated runtime environment.

This process offers several critical advantages across environments:

Standardization: Docker standardizes environments, ensuring that development, testing, and production all run on the same environment, maximizing the probability that code working in development also works in production.
Portability: Containers are portable, allowing an application bundled with its runtime, libraries, and dependencies to work uniformly across any computing environment, whether a developer’s laptop, a test server, or a production cloud server.
Isolation: Each Docker container operates independently, providing isolation from the host machine and other containers, ensuring consistent application behavior.

Docker approaches for development environments

Single Microservice Development with Docker: For individual microservices, developers can install Docker Desktop and run their services directly in containers. This allows focused testing of a single microservice in an environment consistent with production. For Node.js microservices, running them under Docker, or directly on the host OS, is a choice developers can make, depending on the stage of testing.
Orchestrating Multiple Microservices with Docker Compose: When developing applications composed of multiple microservices, managing individual Docker commands for each container quickly becomes tedious. Docker Compose emerges as an invaluable tool for local development, allowing developers to define, build, and run multi-container Docker applications using a single YAML file (docker-compose.yml).
- Simplified Application Bootstrapping: With Docker Compose, an entire microservices application, including databases (like MongoDB or PostgreSQL) and message brokers (like RabbitMQ or Kafka), can be brought up with a single docker compose up --build command. This saves significant time compared to running separate docker build and docker run commands for each service.
- Fast Iteration with Live Reload: Docker Compose can be configured to support “live reload,” enabling developers to update code and have microservices automatically restart in their containers, greatly enhancing the pace of development. This often involves sharing code between the development computer and containers using Docker volumes.
- Development vs. Production Dockerfiles: To optimize for differing needs, it’s common to split Dockerfiles into Dockerfile-dev (for fast iteration) and Dockerfile-prod (for performance and security). This separation allows specific configurations for each environment, with the production versions being crucial for deployment to live environments.

Docker for automated testing environments

Docker and Docker Compose are instrumental in establishing stable and repeatable testing environments.

Production-like Environments: They allow for testing environments that closely emulate production, minimizing discrepancies that lead to bugs. This capability makes the “it worked on my computer” excuse less common, as the Docker environment configured locally is highly likely to work in the production environment.
Automated Testing: Docker Compose is used to boot up the microservices application for automated end-to-end testing, along with database fixtures to load realistic test data. Testing frameworks like Jest (for unit/integration tests) and Playwright (for end-to-end UI tests) can be integrated with Docker-based setups.
CI/CD Pipelines: Docker images are a cornerstone of Continuous Integration (CI) and Continuous Deployment (CD) pipelines. CI pipelines run automated tests on newly built Docker images, ensuring code quality. These images are then pushed to a container registry, ready for deployment to various environments.

Docker for production environments (orchestration with Kubernetes)

While Docker Compose is ideal for local development and testing, Kubernetes is the industry standard for hosting and managing containerized applications in production environments.

Packaging and Publishing Microservices:
- Microservices are packaged into Docker images using a Dockerfile.
- These images are then pushed to a private container registry (e.g., Azure Container Registry, AWS Elastic Container Registry, Docker Hub for public images). This registry acts as a centralized repository for application images, accessible by the production cluster.
Deployment to Kubernetes:
- Kubernetes orchestrates the deployment of these Docker images as pods on a cluster, handling aspects like replication, scaling, and self-healing.
- Deployment configurations for Kubernetes are often defined in YAML files, which can be templated and injected with environment-specific values using tools like envsubst.
- Continuous Deployment (CD) pipelines, often built with tools like GitHub Actions, automate the entire process from code commit to deployment to Kubernetes. This includes building and publishing Docker images, and then using kubectl to deploy them.
Infrastructure as Code (IaC) with Terraform and Pulumi: For provisioning and managing the underlying infrastructure for Docker and Kubernetes (like the container registry itself or the Kubernetes cluster), Infrastructure as Code (IaC) tools like Terraform and Pulumi are extensively used.
- Terraform: Allows defining cloud infrastructure (e.g., Kubernetes clusters, container registries) as code, ensuring repeatable and consistent provisioning across development, testing, and production environments. Terraform can manage multiple environments by copying and editing definition files, or by using templated modules for reusability.
- Pulumi: Offers a modern IaC approach, allowing developers to define infrastructure using general-purpose programming languages (like TypeScript), integrating Docker build processes and managing environments through “stacks”. This enhances flexibility, scalability, and efficiency in cloud infrastructure management. Pulumi also facilitates secure management of secrets and environment variables in Docker builds.

Key benefits of docker across multiple environments

By embracing Docker and its ecosystem (Compose, Kubernetes, IaC tools), organizations achieve:

Consistency: Eliminates environment-related discrepancies, ensuring applications run the same everywhere.
Portability: Allows applications to be moved seamlessly between different environments and cloud providers.
Efficiency: Speeds up development iterations with tools like live reload and simplifies deployment processes.
Scalability: Supports scaling applications and development teams by providing modular, independent components and automated management.
Reduced Risk: Automated testing and consistent environments help catch bugs earlier and enable safer, more reliable deployments.

Conclusion

Docker’s impact on managing applications across multiple environments is profound. From empowering individual developers with local containerization and Docker Compose for multi-service local setups, to providing the bedrock for robust CI/CD pipelines and production-grade Kubernetes deployments, Docker ensures unparalleled consistency and efficiency. Integrated with Infrastructure as Code tools like Terraform and Pulumi, it offers a holistic solution for defining, provisioning, and managing software applications from inception to operation, making it an essential skill set for modern developers and operations teams alike. By standardizing packaging and runtime, Docker provides the freedom to choose the most appropriate tech stack and cloud vendor, avoiding lock-in and fostering agility.

Adam Lloyd-Jones

Adam is a privacy-first SaaS builder, technical educator, and automation strategist. He leads modular infrastructure projects across AWS, Azure, and GCP, blending deep cloud expertise with ethical marketing and content strategy.