This post was contributed by Lance Haig, a solutions engineer at Docker.

In today’s fast-paced development environments, balancing productivity with security while rapidly innovating is a constant juggle for senior leaders. Slow feedback loops, inconsistent environments, and cumbersome tooling can derail progress. As a solutions engineer at Docker, I’ve learned from my conversations with industry leaders that a key focus for senior leaders is on creating processes and providing tools that let developers move faster without compromising quality or security. 

Let’s explore how Docker’s suite of products and Docker Business empowers industry leaders and their development teams to innovate faster, stay secure, and deliver impactful results.

1. Create a foundation for reliable workflows

A recurring pain point I’ve heard from senior leaders is the delay between code commits and feedback. One leader described how their team’s feedback loops stretched to eight hours, causing delays, frustration, and escalating costs.

Optimizing feedback cycles often involves localizing testing environments and offloading heavy build tasks. Teams leveraging containerized test environments — like Testcontainers Cloud — reduce this feedback loop to minutes, accelerating developer output. Similarly, offloading complex builds to managed cloud services ensures infrastructure constraints don’t block developers. The time saved here is directly reinvested in faster iteration cycles.

Incorporating Docker’s suite of products can significantly enhance development efficiency by reducing feedback loops. For instance, The Warehouse Group, New Zealand’s largest retail chain, transformed its development process by adopting Docker. This shift enabled developers to test applications locally, decreasing feedback loops from days to minutes. Consequently, deployments that previously took weeks were streamlined to occur within an hour of code submission.

2. Shorten feedback cycles to drive results

Inconsistent development environments continue to plague engineering organizations. These mismatches lead to wasted time troubleshooting “works-on-my-machine” errors or inefficiencies across CI/CD pipelines. Organizations achieve consistent environments across local, staging, and production setups by implementing uniform tooling, such as Docker Desktop.

For senior leaders, the impact isn’t just technical: predictable workflows simplify onboarding, reduce new hires’ time to productivity, and establish an engineering culture focused on output rather than firefighting. 

For example, Ataccama, a data management company, leveraged Docker to expedite its deployment process. With containerized applications, Ataccama reduced application deployment lead times by 75%, achieving a 50% faster transition from development to production. By reducing setup time and simplifying environment configuration, Docker allows the team to spin up new containers instantly and shift focus to delivering value. This efficiency gain allowed the team to focus more on delivering value and less on managing infrastructure.

3. Empower teams to collaborate in distributed workflows

Today’s hybrid and remote workforces make developer collaboration more complex. Secure, pre-configured environments help eliminate blockers when working across teams. Leaders who adopt centralized, standardized configurations — even in zero-trust environments — reduce setup time and help teams remain focused.

Docker Build Cloud further simplifies collaboration in distributed workflows by enabling developers to offload resource-intensive builds to a secure, managed cloud environment. Teams can leverage parallel builds, shared caching, and multi-architecture support to streamline workflows, ensuring that builds are consistent and fast across team members regardless of their location or platform. By eliminating the need for complex local build setups, Docker Build Cloud allows developers to focus on delivering high-quality code, not managing infrastructure.

Beyond tools, fostering collaboration requires a mix of practices: sharing containerized services, automating repetitive tasks, and enabling quick rollbacks. The right combination allows engineering teams to align better, focus on goals, and deliver outcomes quickly.

Empowering engineering teams with streamlined workflows and collaborative tools is only part of the equation. Leaders must also evaluate how these efficiencies translate into tangible cost savings, ensuring their investments drive measurable business value.

To learn more about how Docker simplifies the complex, read From Legacy to Cloud-Native: How Docker Simplifies Complexity and Boosts Developer Productivity.

4. Reduce costs

Every organization feels pressured to manage budgets effectively while delivering on demanding expectations. However, leaders can realize cost savings in unexpected areas, including hiring, attrition, and infrastructure optimization, by adopting consumption-based pricing models, streamlining operations, and leveraging modern tooling.

Easy access to all Docker products provides flexibility and scalability 

Updated Docker plans make it easier for development teams to access everything they need under one subscription. Consumption is included for each new product, and more can be added as needed. This allows organizations to scale resources as their needs evolve and effectively manage their budgets. 

Cost savings through streamlined operations

Organizations adopting Docker Business have reported significant reductions in infrastructure costs. For instance, a leading beauty company achieved a 25% reduction in infrastructure expenses by transitioning to a container-first development approach with Docker. 

Bitso, a leading financial services company powered by cryptocurrency, switched to Docker Business from an alternative solution and reduced onboarding time from two weeks to a few hours per engineer, saving an estimated 7,700 hours in the eight months while scaling the team. Returning to Docker after spending almost two years with the alternative open-source solution proved more cost-effective, decreasing the time spent onboarding, troubleshooting, and debugging. Further, after transitioning back to Docker, Bitso has experienced zero new support tickets related to Docker, significantly reducing the platform support burden. 

Read the Bitso case study to learn why Bitso returned to Docker Business.

Reducing infrastructure costs with modern tooling

Organizations that adopt Docker’s modern tooling realize significant infrastructure cost savings by optimizing resource usage, reducing operational overhead, and eliminating inefficiencies tied to legacy processes. 

By leveraging Docker Build Cloud, offloading resource-intensive builds to a managed cloud service, and leveraging shared cache, teams can achieve builds up to 39 times faster, saving approximately one hour per day per developer. For example, one customer told us they saw their overall build times improve considerably through the shared cache feature. Previously on their local machine, builds took 15-20 minutes. Now, with Docker Build Cloud, it’s down to 110 seconds — a massive improvement.

Check out our calculator to estimate your savings with Build Cloud.

5. Retain talent through frictionless environments

High developer turnover is expensive and often linked to frustration with outdated or inefficient tools. I’ve heard countless examples of developers leaving not because of the work but due to the processes and tooling surrounding it. Providing modern, efficient environments that allow experimentation while safeguarding guardrails improves satisfaction and retention.

Year after year, developers rank Docker as their favorite developer tool. For example, more than 65,000 developers participated in Stack Overflow’s 2024 Developer Survey, which recognized Docker as the most-used and most-desired developer tool for the second consecutive year, and as the most-admired developer tool.

Providing modern, efficient environments with Docker tools can enhance developer satisfaction and retention. While specific metrics vary, streamlined workflows and reduced friction are commonly cited as factors that improve team morale and reduce turnover. Retaining experienced developers not only preserves institutional knowledge but also reduces the financial burden of hiring and onboarding replacements.

6. Efficiently manage infrastructure 

Consolidating development and operational tooling reduces redundancy and lowers overall IT spend. Organizations that migrate to standardized platforms see a decrease in toolchain maintenance costs and fewer internal support tickets. Simplified workflows mean IT and DevOps teams spend less time managing environments and more time delivering strategic value.

Some leaders, however, attempt to build rather than buy solutions for developer workflows, seeing it as cost-saving. This strategy carries risks: reliance on a single person or small team to maintain open-source tooling can result in technical debt, escalating costs, and subpar security. By contrast, platforms like Docker Business offer comprehensive protection and support, reducing long-term risks.

Cost management and operational efficiency go hand-in-hand with another top priority: security. As development environments grow more sophisticated, ensuring airtight security becomes critical — not just for protecting assets but also for maintaining business continuity and customer trust.

7. Secure developer environments

Security remains a top priority for all senior leaders. As organizations transition to zero-trust architectures, the role of developer workstations within this model grows. Developer systems, while powerful, are not exempt from being targets for potential vulnerabilities. Securing developer environments without stifling productivity is an ongoing leadership challenge.

Tightening endpoint security without reducing autonomy

Endpoint security starts with visibility, and Docker makes it seamless. With Image Access Management, Docker ensures that only trusted and compliant images are used throughout your development lifecycle, reducing exposure to vulnerabilities. However, these solutions are only effective if they don’t create bottlenecks for developers.

Recently, a business leader told me that taking over a team without visibility into developer environments and security revealed significant risks. Developers were operating without clear controls, exposing the organization to potential vulnerabilities and inefficiencies. By implementing better security practices and centralized oversight, the leaders improved visibility and reduced operational risks, enabling a more secure and productive environment for developer teams. This shift also addressed compliance concerns by ensuring the organization could effectively meet regulatory requirements and demonstrate policy adherence.

Securing the software supply chain

From trusted content repositories to real-time SBOM insights, securing dependencies is critical for reducing attack surfaces. In conversations with security-focused leaders, the message is clear: Supply chain vulnerabilities are both a priority and a pain point. Leaders are finding success when embedding security directly into developer workflows rather than adding it as a reactive step. Tools like Docker Scout provide real-time visibility into vulnerabilities within your software supply chain, enabling teams to address risks before they escalate. 

Securing developer environments strengthens the foundation of your engineering workflows. But for many industries, these efforts must also align with compliance requirements, where visibility and control over processes can mean the difference between growth and risk.

Improving compliance

Compliance may feel like an operational requirement, but for senior leadership, it’s a strategic asset. In regulated industries, compliance enables growth. In less regulated sectors, it builds customer trust. Regardless of the driver, visibility, and control are the cornerstones of effective compliance.

Proactive compliance, not reactive audits

Audits shouldn’t feel like fire drills. Proactive compliance ensures teams stay ahead of risks and disruptions. With the right processes in place — automated logging, integrated open-source software license checks, and clear policy enforcement — audit readiness becomes a part of daily operations. This proactive approach ensures teams stay ahead of compliance risks while reducing unnecessary disruptions.

While compliance ensures a stable and trusted operational baseline, innovation drives competitive advantage. Forward-thinking leaders understand that fostering creativity within a secure and compliant framework is the key to sustained growth.

8. Accelerating innovation

Every senior leader seeks to balance operational excellence and fostering innovation. Enabling engineers to move fast requires addressing two critical tensions: reducing barriers to experimentation and providing guardrails that maintain focus.

Building a culture of safe experimentation

Experimentation thrives in environments where developers feel supported and unencumbered. By establishing trusted guardrails — such as pre-approved images and automated rollbacks — teams gain the confidence to test bold ideas without introducing unnecessary risks.

From MVP to market quickly

Reducing friction in prototyping accelerates the time-to-market for Minimum Viable Products (MVPs). Leaders prioritizing local testing environments and streamlined approval processes create conditions where engineering creativity translates directly into a competitive advantage.

Innovation is no longer just about moving fast; it’s about moving deliberately. Senior leaders must champion the tools, practices, and environments that unlock their teams’ full potential.

Unlock the full potential of your teams

As a senior leader, you have a unique position to balance productivity, security, and innovation within your teams. Reflect on your current workflows and ask: Are your developers empowered with the right tools to innovate securely and efficiently? How does your organization approach compliance and risk management without stifling creativity?

Tools like Docker Business can be a strategic enabler, helping you address these challenges while maintaining focus on your goals.

Learn more

• Docker Scout: Integrates seamlessly into your development lifecycle, delivering vulnerability scans, image analysis, and actionable recommendations to address issues before they reach production.
• Docker Health Scores: A security grading system for container images that offers teams clear insights into their image security posture.
• Docker Hub: Access trusted, verified content, including Docker Official Images (DOI), to build secure and compliant software applications.
• Docker Official Images (DOI): A curated set of high-quality images that provide a secure foundation for containerized applications.
• Image Access Management (IAM): Enforce image-sharing policies and restrict access to sensitive components, ensuring only trusted team members access critical assets.
• Hardened Docker Desktop: A tamper-proof, enterprise-grade development environment that aligns with security standards to minimize risks from local development.

One of the best ways to make sure your web apps work well in different environments is to containerize them. Containers let you work in a more controlled way, which makes development and deployment easier. This guide will show you how to containerize a Django web app with Docker and explain why it’s a good idea.

We will walk through creating a Docker container for your Django application. Docker gives you a standardized environment, which makes it easier to get up and running and more productive. This tutorial is aimed at those new to Docker who already have some experience with Django. Let’s get started!

Why containerize your Django application?

Django apps can be put into containers to help you work more productively and consistently. Here are the main reasons why you should use Docker for your Django project:

• Creates a stable environment: Containers provide a stable environment with all dependencies installed, so you don’t have to worry about “it works on my machine” problems. This ensures that you can reproduce the app and use it on any system or server. Docker makes it simple to set up local environments for development, testing, and production.
• Ensures reproducibility and portability: A Dockerized app bundles all the environment variables, dependencies, and configurations, so it always runs the same way. This makes it easier to deploy, especially when you’re moving apps between environments.
• Facilitates collaboration between developers: Docker lets your team work in the same environment, so there’s less chance of conflicts from different setups. Shared Docker images make it simple for your team to get started with fewer setup requirements.
• Speeds up deployment processes: Docker makes it easier for developers to get started with a new project quickly. It removes the hassle of setting up development environments and ensures everyone is working in the same place, which makes it easier to merge changes from different developers.

Getting started with Django and Docker

Setting up a Django app in Docker is straightforward. You don’t need to do much more than add in the basic Django project files.

Tools you’ll need

To follow this guide, make sure you first:

• Install Docker Desktop and Docker Compose on your machine.
• Use a Docker Hub account to store and access Docker images.
• Make sure Django is installed on your system.

If you need help with the installation, you can find detailed instructions on the Docker and Django websites.

How to Dockerize your Django project

The following six steps include code snippets to guide you through the process.

Step 1: Set up your Django project

1. Initialize a Django project. 

If you don’t have a Django project set up yet, you can create one with the following commands:

django-admin startproject my_docker_django_app
cd my_docker_django_app

2. Create a requirements.txt file. 

In your project, create a requirements.txt file to store dependencies:

pip freeze > requirements.txt

3. Update key environment settings.

You need to change some sections in the settings.py file to enable them to be set using environment variables when the container is started. This allows you to change these settings depending on the environment you are working in.

  # The secret key
  SECRET_KEY = os.environ.get("SECRET_KEY")

  DEBUG = bool(os.environ.get("DEBUG", default=0))

  ALLOWED_HOSTS = os.environ.get("DJANGO_ALLOWED_HOSTS","127.0.0.1").split(",")

Step 2: Create a Dockerfile

A Dockerfile is a script that tells Docker how to build your Docker image. Put it in the root directory of your Django project. Here’s a basic Dockerfile setup for Django:

# Use the official Python runtime image
FROM python:3.13  

# Create the app directory
RUN mkdir /app

# Set the working directory inside the container
WORKDIR /app

# Set environment variables 
# Prevents Python from writing pyc files to disk
ENV PYTHONDONTWRITEBYTECODE=1
#Prevents Python from buffering stdout and stderr
ENV PYTHONUNBUFFERED=1 

# Upgrade pip
RUN pip install --upgrade pip 

# Copy the Django project  and install dependencies
COPY requirements.txt  /app/

# run this command to install all dependencies 
RUN pip install --no-cache-dir -r requirements.txt

# Copy the Django project to the container
COPY . /app/

# Expose the Django port
EXPOSE 8000

# Run Django’s development server
CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]

Each line in the Dockerfile serves a specific purpose:

• FROM: Selects the image with the Python version you need.
• WORKDIR: Sets the working directory of the application within the container.
• ENV: Sets the environment variables needed to build the application
• RUN and COPY commands: Install dependencies and copy project files.
• EXPOSE and CMD: Expose the Django server port and define the startup command.

You can build the Django Docker container with the following command:

docker build -t django-docker .

To see your image, you can run:

docker image list

The result will look something like this:

REPOSITORY      TAG       IMAGE ID       CREATED          SIZE
django-docker   latest    ace73d650ac6   20 seconds ago   1.55GB

Although this is a great start in containerizing the application, you’ll need to make a number of improvements to get it ready for production.

• The CMD manage.py is only meant for development purposes and should be changed for a WSGI server.
• Reduce the size of the image by using a smaller image.
• Optimize the image by using a multistage build process.

Let’s get started with these improvements.

Update requirements.txt

Make sure to add gunicorn to your requirements.txt. It should look like this:

asgiref==3.8.1
Django==5.1.3
sqlparse==0.5.2
gunicorn==23.0.0
psycopg2-binary==2.9.10

Make improvements to the Dockerfile

The Dockerfile below has changes that solve the three items on the list. The changes to the file are as follows:

• Updated the FROM python:3.13 image to FROM python:3.13-slim. This change reduces the size of the image considerably, as the image now only contains what is needed to run the application.
• Added a multi-stage build process to the Dockerfile. When you build applications, there are usually many files left on the file system that are only needed during build time and are not needed once the application is built and running. By adding a build stage, you use one image to build the application and then move the built files to the second image, leaving only the built code. Read more about multi-stage builds in the documentation.
• Add the Gunicorn WSGI server to the server to enable a production-ready deployment of the application.

# Stage 1: Base build stage
FROM python:3.13-slim AS builder

# Create the app directory
RUN mkdir /app

# Set the working directory
WORKDIR /app 

# Set environment variables to optimize Python
ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1 

# Upgrade pip and install dependencies
RUN pip install --upgrade pip 

# Copy the requirements file first (better caching)
COPY requirements.txt /app/

# Install Python dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Stage 2: Production stage
FROM python:3.13-slim

RUN useradd -m -r appuser && \
   mkdir /app && \
   chown -R appuser /app

# Copy the Python dependencies from the builder stage
COPY --from=builder /usr/local/lib/python3.13/site-packages/ /usr/local/lib/python3.13/site-packages/
COPY --from=builder /usr/local/bin/ /usr/local/bin/

# Set the working directory
WORKDIR /app

# Copy application code
COPY --chown=appuser:appuser . .

# Set environment variables to optimize Python
ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1 

# Switch to non-root user
USER appuser

# Expose the application port
EXPOSE 8000 

# Start the application using Gunicorn
CMD ["gunicorn", "--bind", "0.0.0.0:8000", "--workers", "3", "my_docker_django_app.wsgi:application"]

Build the Docker container image again.

docker build -t django-docker .

After making these changes, we can run a docker image list again:

REPOSITORY      TAG       IMAGE ID       CREATED         SIZE
django-docker   latest    3c62f2376c2c   6 seconds ago   299MB

You can see a significant improvement in the size of the container.

The size was reduced from 1.6 GB to 299MB, which leads to faster a deployment process when images are downloaded and cheaper storage costs when storing images.

You could use docker init as a command to generate the Dockerfile and compose.yml file for your application to get you started.

Step 3: Configure the Docker Compose file

A compose.yml file allows you to manage multi-container applications. Here, we’ll define both a Django container and a PostgreSQL database container.

The compose file makes use of an environment file called .env, which will make it easy to keep the settings separate from the application code. The environment variables listed here are standard for most applications:

services:
 db:
   image: postgres:17
   environment:
     POSTGRES_DB: ${DATABASE_NAME}
     POSTGRES_USER: ${DATABASE_USERNAME}
     POSTGRES_PASSWORD: ${DATABASE_PASSWORD}
   ports:
     - "5432:5432"
   volumes:
     - postgres_data:/var/lib/postgresql/data
   env_file:
     - .env

 django-web:
   build: .
   container_name: django-docker
   ports:
     - "8000:8000"
   depends_on:
     - db
   environment:
     DJANGO_SECRET_KEY: ${DJANGO_SECRET_KEY}
     DEBUG: ${DEBUG}
     DJANGO_LOGLEVEL: ${DJANGO_LOGLEVEL}
     DJANGO_ALLOWED_HOSTS: ${DJANGO_ALLOWED_HOSTS}
     DATABASE_ENGINE: ${DATABASE_ENGINE}
     DATABASE_NAME: ${DATABASE_NAME}
     DATABASE_USERNAME: ${DATABASE_USERNAME}

     DATABASE_PASSWORD: ${DATABASE_PASSWORD}
     DATABASE_HOST: ${DATABASE_HOST}
     DATABASE_PORT: ${DATABASE_PORT}
   env_file:
     - .env
volumes:
   postgres_data:

And the example .env file:

DJANGO_SECRET_KEY=your_secret_key
DEBUG=True
DJANGO_LOGLEVEL=info
DJANGO_ALLOWED_HOSTS=localhost
DATABASE_ENGINE=postgresql_psycopg2
DATABASE_NAME=dockerdjango
DATABASE_USERNAME=dbuser
DATABASE_PASSWORD=dbpassword
DATABASE_HOST=db
DATABASE_PORT=5432

Step 4: Update Django settings and configuration files

1. Configure database settings. 

Update settings.py to use PostgreSQL:

  DATABASES = {
       'default': {
           'ENGINE': 'django.db.backends.{}'.format(
               os.getenv('DATABASE_ENGINE', 'sqlite3')
           ),
           'NAME': os.getenv('DATABASE_NAME', 'polls'),
           'USER': os.getenv('DATABASE_USERNAME', 'myprojectuser'),
           'PASSWORD': os.getenv('DATABASE_PASSWORD', 'password'),
           'HOST': os.getenv('DATABASE_HOST', '127.0.0.1'),
           'PORT': os.getenv('DATABASE_PORT', 5432),
       }
   }

2. Set ALLOWED_HOSTS to read from environment files. 

In settings.py, set ALLOWED_HOSTS to:

   # 'DJANGO_ALLOWED_HOSTS' should be a single string of hosts with a , between each.
   # For example: 'DJANGO_ALLOWED_HOSTS=localhost 127.0.0.1,[::1]'
   ALLOWED_HOSTS = os.environ.get("DJANGO_ALLOWED_HOSTS","127.0.0.1").split(",")

3. Set the SECRET_KEY to read from environment files.

In settings.py, set SECRET_KEY to:

   # SECURITY WARNING: keep the secret key used in production secret!
   SECRET_KEY = os.environ.get("DJANGO_SECRET_KEY")

4. Set DEBUG to read from environment files.

In settings.py, set DEBUG to:

 # SECURITY WARNING: don't run with debug turned on in production!
 DEBUG = bool(os.environ.get("DEBUG", default=0))

Step 5: Build and run your new Django project

To build and start your containers, run:

docker compose up --build

This command will download any necessary Docker images, build the project, and start the containers. Once complete, your Django application should be accessible at http://localhost:8000.

Step 6: Test and access your application

Once the app is running, you can test it by navigating to http://localhost:8000. You should see Django’s welcome page, indicating that your app is up and running. To verify the database connection, try running a migration:

docker compose run django-web python manage.py migrate

Troubleshooting common issues with Docker and Django

Here are some common issues you might encounter and how to solve them:

• Database connection errors: If Django can’t connect to PostgreSQL, verify that your database service name matches in compose.yml and settings.py.
• File synchronization issues: Use the volumes directive in compose.yml to sync changes from your local files to the container.
• Container restart loops or crashes: Use docker compose logs to inspect container errors and determine the cause of the crash.

Optimizing your Django web application

To improve your Django Docker setup, consider these optimization tips:

• Automate and secure builds: Use Docker’s multi-stage builds to create leaner images, removing unnecessary files and packages for a more secure and efficient build.
• Optimize database access: Configure database pooling and caching to reduce connection time and boost performance.
• Efficient dependency management: Regularly update and audit dependencies listed in requirements.txt to ensure efficiency and security.

Take the next step with Docker and Django

Containerizing your Django application with Docker is an effective way to simplify development, ensure consistency across environments, and streamline deployments. By following the steps outlined in this guide, you’ve learned how to set up a Dockerized Django app, optimize your Dockerfile for production, and configure Docker Compose for multi-container setups.

Docker not only helps reduce “it works on my machine” issues but also fosters better collaboration within development teams by standardizing environments. Whether you’re deploying a small project or scaling up for enterprise use, Docker equips you with the tools to build, test, and deploy reliably.

Ready to take the next step? Explore Docker’s powerful tools, like Docker Hub and Docker Scout, to enhance your containerized applications with scalable storage, governance, and continuous security insights.

Learn more 

• Subscribe to the Docker Newsletter. 
• Learn more about Docker commands, Docker Compose, and security in the Docker Docs. 
• Find Dockerized Django projects for inspiration and guidance in GitHub. 
• Discover Docker plugins that improve performance, logging, and security.
• Get the latest release of Docker Desktop.
• Have questions? The Docker community is here to help.
• New to Docker? Get started.