The Why, What, And How Of Containerisation

Containerisation has revolutionised software development by offering lightweight, portable, and scalable solutions for application deployment. Containers empower teams to deploy applications faster and more reliably in diverse environments. Let’s find out how and why they work so well.

In the modern era of software development, agility, scalability, and portability have become essential for building and deploying applications. Enter containerisation—a technology that has revolutionised the way developers package, deploy, and manage applications across various environments. From microservices architecture to DevOps pipelines, containerisation is now a cornerstone of cloud-native development.

Why containerisation?

The need for containerisation arises from the challenges developers and operations teams face when building, deploying, and maintaining software in diverse environments. Let’s dive deeper into the reasons.

The “It works on my machine” problem: This age-old problem arises when code that runs perfectly on a developer’s local system fails in staging or production environments. This discrepancy is usually due to differences in:

• Operating system versions (e.g., Ubuntu 18.04 vs 22.04)
• Missing or different versions of dependencies (e.g., Python 3.6 vs 3.10)
• System libraries or tools
• Environment variables and configuration files

Containers fix this by encapsulating the application along with all its dependencies, libraries, and environment settings into a single, consistent unit. As a result, the containerised application behaves the same way—regardless of where it is deployed, be it a developer’s laptop, a test server, or a public cloud.

Example: A Flask web app containerised with Python 3.9 and specific libraries will run identically on all systems with Docker installed.

Slow and inefficient deployment with VMs: Traditional virtual machines (VMs) emulate entire operating systems. While VMs provide good isolation, they are resource-intensive:

• Require gigabytes of storage per instance
• Take minutes to boot
• Need separate OS licences and patching

Containers, on the other hand, share the host OS kernel and require only the minimal runtime (binaries and libraries) needed by the application. This makes them:

• Lightweight (usually measured in megabytes)
• Fast to start (milliseconds)
• More efficient in resource usage, enabling higher density on a single host

Example: While a server might host 5-10 VMs, it could run 50-100 containers depending on the workload.

Complex application architectures: Modern applications are increasingly built using microservices architecture, where functionalities are split into loosely coupled services. For instance:

• Frontend UI
• REST APIs
• Authentication service
• Message queues (e.g., RabbitMQ)
• Databases (e.g., PostgreSQL)

Managing and deploying such architectures using traditional tools is complex and error prone.

Containers simplify this by allowing each service to run in its own isolated environment. Teams can:

• Develop, test, and deploy services independently
• Reuse base images across multiple services
• Rollback individual services without affecting the whole system

Example: An e-commerce site could have separate containers for user authentication, product catalogue, cart service, and payment gateway.

Cloud-native development and scalability: Cloud providers favour containers because they are portable, stateless, and easily scalable. With container orchestrators like Kubernetes, teams can:

• Automatically scale services based on demand
• Perform rolling updates with zero downtime
• Handle service discovery and load balancing
• Recover from failures automatically

Containers enable cloud-native practices such as Infrastructure as Code (IaC), autoscaling, blue-green deployments, and canary releases.

Example: An image-processing service could automatically scale to 10 containers during high load and shrink to 2 during off-hours, optimising costs.

Improved CI/CD workflows: In modern DevOps practices, continuous integration and continuous deployment (CI/CD) are crucial for fast and reliable software delivery.

Containers enhance CI/CD pipelines by providing:

• Immutable builds – once a container image is built, it won’t change.
• Reproducibility – testing in containers ensures the same results in production.
• Simplified testing – each stage of the pipeline (build, test, deploy) uses the same container image.

This leads to fewer surprises in production and faster iterations.

Example: A Jenkins pipeline could build a Docker image from source, run unit tests, security scans, and then deploy it to a staging cluster—all using the same image.

What is containerisation?

Containerisation is the technique of packaging an application along with all its dependencies, libraries, configuration files, and runtime environment into a single executable unit called a container.

This ensures that the application behaves the same regardless of where it is run—on a developer’s laptop, a test server, or in production. The key concepts are:

• Container: A runnable instance of an image, including application code, libraries, dependencies, and configuration files.
• Image: A static specification (blueprint) of what the container should include and how it should run.
• Docker: The most widely used platform to create, manage, and run containers.
• Orchestration tools: Platforms like Kubernetes manage deployment, scaling, and networking of containers at scale.

Key characteristics of containers

Feature	Description
Lightweight	Containers share the OS kernel, unlike VMs, making them efficient.
Portable	A container can run anywhere a container engine (like Docker) is installed.
Isolated	Each container operates in its own isolated environment.
Immutable	Once created, containers do not change, ensuring consistency.
Fast boot-up	Containers start almost instantly.

 

Components of containerisation

Component	Role
Container engine	Software like Docker or containerd that runs and manages containers.
Container image	A template that contains everything required to run an application.
Dockerfile	A script that defines the steps to create a container image.
Container registry	Repositories (like Docker Hub, Amazon ECR, GitHub Packages) that store and distribute container images.
Orchestration tool	Tools like Kubernetes or Docker Swarm that manage deployment, scaling, and networking of containers.

How does containerisation work?

Let’s go step-by-step through the container lifecycle.

Writing a Dockerfile: A Dockerfile is a blueprint to build your container image.

Example: Dockerfile for a Python App:

dockerfile
# Use an official Python runtime as a base image
FROM python:3.10
# Set the working directory
WORKDIR /app
# Install dependencies
RUN pip install -r requirements.txt
# Run the application
CMD [“python”, “app.py”]

Building the container image: Use the Docker CLI to build the image:

docker build -t my-python-app .

This generates a container image named my-python-app.

Running a container: You can start a container from the image:

docker run -d -p 5000:5000 my-python-app

This runs the app in the background and maps port 5000 of the host to the container.

Container registries: To share the image, use:

docker tag my-python-app username/my-python-app

docker push username/my-python-app

Now others can pull it with:

docker pull username/my-python-app

Container orchestration: Once applications grow, you’ll need to manage multiple containers. Use orchestrators, of which Kubernetes is the most popular. With it, you can:

• Deploy and scale containers automatically
• Monitor container health
• Manage networking between containers
• Load balance and update containers with zero downtime

Real-world use cases

Microservices architecture: Each microservice can be containerised and deployed independently. For example, a travel app can have separate containers for booking, payments, and notifications.

Hybrid cloud deployments: Containers can run on AWS, Azure, GCP, or on-premises. This makes it easy to move workloads across providers.

Continuous integration/Continuous delivery (CI/CD): Containers allow for repeatable builds and tests, making them ideal for automation pipelines.

Development sandboxes: Developers can use containers to replicate production-like environments on their local machines without conflicts.

Advantages and disadvantages of containers

Advantages

• Rapid deployment and scaling
• Efficient use of system resources
• Simplified dependency management
• Faster development cycles
• Easy rollbacks and version control

Disadvantages

• Persistent storage is complex
• Security needs careful handling
• Learning curve for orchestration (e.g., Kubernetes)
• Container sprawl if not managed well

Popular tools in the container ecosystem

Tool	Purpose
Docker	Build and run containers
Podman	Docker-compatible, daemonless container engine
Kubernetes	Container orchestration
Helm	Kubernetes package manager
Docker Compose	Define multi-container apps
Harbor	Secure container registry
Prometheus + Grafana	Monitoring container environments

Containerisation bridges the gap between development and operations, driving agility and innovation. As organisations continue to embrace cloud-native architectures, mastering containers remains a critical skill for the future of DevOps.