---
title: "Solving the \"it works on my machine\" issue using Docker"
description: Docker has revolutionized the way applications are developed, tested, and deployed. In this blog, I'll give an overview of the tool.
---

[DDBM Blog ](https://www.ddbm.com/en/blog)

# [Solving the "it works on my machine" issue using Docker](https://www.ddbm.com/en/blog/docker-overview)

 Written by [Darko Monzio Compagnoni](https://www.ddbm.com/en/blog/author/darko-compagnoni) | 12 Dec, 2024

Docker has revolutionized the way applications are developed, tested, and deployed. It addresses several common problems in software development, including inconsistent environments, difficulty in scaling applications, and issues with dependency management.

By using containers, Docker ensures that applications run in a standardized, isolated environment regardless of where they are deployed.

### **What problem does it solve?**

The primary problem Docker solves is the **"it works on my machine"** issue. Developers often face challenges when applications work perfectly in one environment but fail when deployed elsewhere. This happens due to differences in operating systems, libraries, and configuration settings. Docker provides a solution by containerizing applications, ensuring that they run consistently on any machine or server that has Docker installed.

Furthermore, Docker simplifies **dependency management**. Each application can be packaged with its exact dependencies, libraries, and configuration, ensuring that all necessary components are available when the application is deployed, avoiding compatibility issues between different environments.

Moreover, [Docker integrates with Dagster.](https://nimbusintelligence.com/2024/11/apache-airflow-vs-dagster-for-data-orchestration/)

### **What is a Docker Container?**

A Docker container is a lightweight, standalone, and executable package that contains everything needed to run a piece of software: the **code**, **runtime**, **system tools**, **libraries**, and **settings**. Containers are **isolated** from each other and from the host system, allowing multiple applications to run simultaneously without interfering with one another.

Containers are portable across different systems and environments, making it easier to develop, test, and deploy applications. Unlike traditional virtual machines, containers **do not require a separate operating system to run**, making them more **efficient** and **faster** to start.

Snowflake resolves these problems with its Snowflake Container Services.

### **<https://www.docker.com/resources/what-container/>**

### **What is a Docker Image?**

A Docker image serves as a **blueprint** or template for creating containers. It is a **read-only** file that contains **instructions for running an application**, including all the dependencies, configurations, and code necessary to execute the application. You typically build images from a Dockerfile, which defines the steps to install dependencies and set up the application environment.

While images themselves are not running applications, they provide the foundation for creating containers. Once you create an image, you can use it to instantiate as many containers as needed. **The beauty of Docker images lies in their immutability**; once you create an image, it does not change, **ensuring consistency** across different environments.

### **How to persist data between containers?**

By default, containers are **ephemeral**, meaning that when you remove them, any data stored inside them is also lost. However, in many scenarios, **data needs to persist** beyond the life of a container.

Enter Docker volume: a storage area that exists outside of a container's filesystem. **Volumes are independent of the container lifecycle** and are designed specifically for data persistence. When a container is removed, its associated volume remains intact and **can be reused** by other containers. Volumes can also be shared between containers, enabling **data sharing** and **synchronization** across different parts of an application.

### **How to Containerize an Application**

**Containerizing** an application involves converting an app and its environment into a **Docker image**, which you can then use to create Docker containers. This process typically starts with creating a **Dockerfile**, which specifies the necessary steps to set up the environment and **install dependencies** for the application.

You begin by selecting a base image that matches the application's requirements (e.g., a specific version of Node.js or Python). Then, you copy the application code and any necessary files into the image, and install the dependencies. Once you set up the Dockerfile, you build the image and use it to run the application in a container.

The result is a **portable, isolated environment** that can run the application anywhere Docker supports, ensuring **consistency** across development, testing, and production environments.

### **Resources:**

- [Use containers to Build, Share and Run your applications](https://www.docker.com/resources/what-container/?utm_source=chatgpt.com)
- [What is Docker?](https://docs.docker.com/get-started/docker-overview/?utm_source=chatgpt.com)
- [What problems does Docker really solve? ](https://dev.to/techworld_with_nana/what-problems-does-docker-really-solve-496a?utm_source=chatgpt.com)

Banner photo by [Todd Cravens](https://unsplash.com/@toddcravens?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash) on [Unsplash](https://unsplash.com/photos/blue-whale-on-sea-lwACYK8ScmA?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash)

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