What Problem Does Docker Solve? 6 Software Development Problems Docker Fixes

Docker solves the problem of software running differently in different environments. Before Docker, every developer laptop, test server and production server had to be set up by hand with the right operating system libraries, runtimes and service versions, and small differences between them caused bugs, conflicts and failed deployments. Docker packages each application with its exact environment into a container, so it runs the same way everywhere.

In this article I go through the 6 concrete problems Docker solves in the software development and deployment process, with a before and after for each, plus what Docker does not solve. The video above is my full Docker Crash Course, where I explain these problems and then show you how to use Docker in practice.

What problem does Docker solve, in short?

Docker solves environment inconsistency. An application doesn’t just float around on its own: it needs a runtime, libraries, services and configuration, and it has to run in many environments. Docker bundles all of that into one portable, isolated package, so the environment travels with the application.

Here are the 6 problems at a glance:

#	Problem without Docker	How Docker solves it
1	“It works on my machine”, but not on the server	The same image runs identically in every environment
2	Dependency conflicts between services (the “matrix from hell”)	Each service has its own isolated dependencies in its own container
3	Slow, error-prone setup of development environments	One command per service, the same on every operating system
4	Running two versions of the same software is painful	Run as many versions side by side as you need
5	Deployment depends on manual server setup and text guides	Developers ship an image, servers only need Docker
6	Virtual machines are heavy for running many apps	Containers share the host kernel and start in seconds

Let’s look at the context first, and then at each problem.

Why do modern applications need Docker?

Most modern applications are not one single program. They combine several technologies to build the complete functionality. For example, one application could use:

• Node.js for the backend web server
• React for the frontend
• MongoDB as the database
• Redis for caching and messaging

Each of these technologies has a specific version that the application depends on. And the application must run in several environments: every developer’s laptop, a test environment, and production. Those environments can differ in operating system, OS version, installed libraries and hardware. Without Docker, each of them must be configured with the correct versions of all these services, by hand. That is where the problems start.

Problem 1: “It works on my machine”

Docker solves “it works on my machine” by shipping the environment together with the application. The image that a developer tests locally is exactly the image that runs on the test server and in production, with the same OS libraries, runtime version and configuration.

Without Docker, the code is the same everywhere, but the environment around it isn’t. The developer has Node.js 22 on a Mac, the test server has an older version on Ubuntu, and production has slightly different system libraries. The app works locally and fails on the server, and finding the reason can take hours.

With Docker, developers and testers work with identical environments, because the environment is packaged in the image and moves around as one artifact, like a file.

Problem 2: Dependency conflicts between services

Docker solves dependency conflicts by isolating each service with its own dependencies in its own container. Two services can need different versions of the same library and still run on the same machine.

Without containers, all services are installed on the same operating system and share its libraries. That leads to problems like these:

• Each service must be compatible with the underlying operating system
• One service needs version X of an OS library, another service needs version Y of the same library
• Every time you update any service, you have to recheck compatibility with the OS and with all other services

People call this the “matrix from hell”: every combination of service, library version and environment that has to work together. With Docker, each service manages its required OS dependencies for itself, bundled and isolated in its own container. You can change one component without affecting the others, and you can even change the host’s operating system without affecting any of the services.

Problem 3: Slow and error-prone development setup

Docker turns setting up a development environment from a day of installation steps into a few commands. Instead of installing every service on your computer, you start each one from a ready image.

Without Docker, a new developer joining the team has to install the right versions of the database, the cache, the message broker and so on, on their specific operating system. Each service has several installation and configuration steps, the steps differ between Mac, Windows and Linux, and any mistake means debugging before writing the first line of code.

With Docker, there are already ready-made images for almost every service on Docker Hub. If I need a Postgres database for local development, I start it with one command:

docker run -d --name postgres -e POSTGRES_PASSWORD=mysecretpassword -p 5432:5432 postgres:17

And if the project needs several services, you describe them all in a compose.yaml file in the repository, and every developer starts the complete environment with docker compose up. The command is the same on every operating system.

Problem 4: Running multiple versions of the same software

Docker lets you run several versions of the same software side by side without conflicts. Each version runs in its own container, isolated from the others.

Without Docker, installing two versions of the same database on one machine is painful: they fight over installation paths, configuration files, system services and ports. But in real life you often need exactly that, for example when two projects use different Postgres versions, or when you test an upgrade.

With Docker, you just start a second container from the other version’s image:

docker run -d --name postgres-16 -e POSTGRES_PASSWORD=mysecretpassword -p 5433:5432 postgres:16

Now Postgres 17 runs on port 5432 and Postgres 16 on port 5433, completely independent of each other. If you want to see how that looks in practice, I show it step by step in What is a Docker container.

Problem 5: Painful deployments and dev vs ops handoffs

Docker simplifies deployment because the application and its whole environment are delivered as one image. The server only needs Docker; nothing else has to be installed or configured for the application.

Without Docker, the development team hands over an artifact, like a JAR file, plus a text guide on how to install and configure it, the database and other dependencies. The operations team follows that guide on each server. If a step is missing or unclear, the deployment fails, and the two teams go back and forth until it works. And because everything is installed directly on the server’s OS, applications on the same server can conflict with each other.

With Docker, the configuration and dependencies are defined in the Dockerfile, in code, and built into the image. Deploying means pulling the image from a registry and running it. This also makes CI/CD pipelines simple: the pipeline builds the image once and deploys the same image to test, staging and production. I describe this before and after in more detail in What is Docker.

Problem 6: Virtual machines are heavy for running applications

Docker gives you isolation between applications without the overhead of a full virtual machine per application. Containers share the host’s kernel, so they are small, start in seconds and you can run many of them on one server.

Before containers, the way to isolate applications from each other was to give each one its own virtual machine. Every VM runs a complete operating system, which uses gigabytes of disk and a lot of memory, and takes much longer to boot. Containers only package the application layer, so they are typically megabytes to a few hundred megabytes. I compare both in detail in Docker vs Virtual Machine.

What problems does Docker not solve?

Docker is very useful, but it’s not magic. To be fair, here is what it doesn’t solve on its own:

• Bugs in your code: a broken application runs just as broken in a container
• Kernel and CPU architecture differences: containers share the host’s kernel, so Linux images need a Linux kernel (Docker Desktop provides one on Windows and Mac), and an image built only for x86 (amd64) won’t run natively on an ARM machine unless you build multi-platform images
• Persistent data: data inside a container is lost when the container is removed, so you need volumes for databases and files
• Running containers at scale: scaling, self-healing and rolling updates across many servers need an orchestrator like Kubernetes
• Security by default: you still need small base images, a non-root user and image scanning. See my Docker best practices

Frequently asked questions

What problem does Docker solve?

Docker solves the problem of applications behaving differently in different environments. It packages an application with its runtime, libraries and configuration into a container image, so it runs identically on a laptop, a test server and in production. This also removes dependency conflicts, speeds up developer setup and simplifies deployment.

Why was Docker created?

Docker was created to make Linux containers easy to use for developers. Container features existed in the Linux kernel before, but they were complicated to work with. Docker added a simple command line, a standard image format and a way to share images, which made packaging and shipping applications in containers practical for everyone.

What is the “matrix from hell” in Docker?

The “matrix from hell” describes all the combinations of services, library versions and environments that have to work together when everything is installed on the same operating system. Every update means rechecking compatibility. Docker breaks this matrix by isolating each service with its own dependencies in its own container.

Does Docker solve “it works on my machine”?

Mostly, yes. Because the image contains the application’s whole environment, the same image behaves the same on every machine with Docker. Remaining differences usually come from things outside the image, like different environment variables, configuration, data or CPU architecture.

What are the main benefits of using Docker?

The main benefits are consistent environments from development to production, isolated dependencies per service, fast setup of development environments, easy deployment with one image, efficient use of resources compared to virtual machines, and a huge library of ready-made images on Docker Hub.

Do I still need virtual machines if I use Docker?

Often yes, they work together. In the cloud, containers almost always run on virtual machines, for example on AWS EC2 instances or Kubernetes worker nodes. Docker replaces VMs for packaging and isolating individual applications, not for providing the servers themselves.

Where to go from here

Now that you know which problems Docker solves, read What is Docker to see how Docker works, and What is a Docker container to run your first containers. Compare containers with VMs in Docker vs Virtual Machine, and when you write your own Dockerfiles, follow my Docker best practices. All my Docker articles and guides are on the Docker topic page.