Modern applications rarely consist of a single process running on one machine. They typically include several components, such as an API, user interface, database, and background processes, that need to operate reliably across different environments. Containers make it easier to package and run these components, but managing them becomes more complex as the infrastructure grows.

As workloads increase, teams also need to consider scaling, failure recovery, resource allocation, and the deployment of new versions without unnecessary downtime. This is where the difference between Docker and Kubernetes becomes important. The two technologies solve different problems, and the right choice largely depends on the application's scale and requirements.

What Is Containerization and Why Is It Used?

Applications depend on libraries, runtime environments, system packages, and configuration. Differences between development, testing, and production environments can cause the same application to behave differently. Containerization solves much of this problem by packaging the application and its required dependencies into a portable, standardized environment.

A Consistent Application Environment

A container image contains the application code and its required dependencies. It can be built once and then used across development, testing, and deployment without manually recreating the environment on each machine.

Dependency Isolation

Different applications may use different versions of the same libraries and components. Containers isolate them from one another, reducing the risk of conflicts and allowing each application to use the dependencies it requires.

More Predictable Deployments

Using the same container image across different stages makes deployments more predictable. Configuration, sensitive data (secrets), network settings, and persistent data still need to be managed separately, but the application's runtime environment remains consistent.

When Are Containers No Longer Enough?

Packaging and running an application is only part of managing it. As the number of containers grows, additional tasks need to be handled, including workload scheduling, service connectivity, scaling, failure recovery, and deploying updates.

In smaller environments, these processes can be relatively easy to manage. However, when applications run across multiple machines, and the number of containers increases, coordinating them becomes significantly more complex. This is where orchestration tools such as Kubernetes become necessary.

What Is the Difference Between Docker and Kubernetes?

Docker and Kubernetes are often compared as alternatives, but they serve different roles. Docker focuses on creating and running containers, while Kubernetes manages and coordinates containerized applications across a cluster.

Docker Creates and Runs Containers

Docker packages an application and its dependencies into a container image that can be used to start containers. It also provides the tools needed to manage them on a single host. For simpler applications, this is often sufficient because services, networking, and persistent data can be managed without adding an orchestration layer.

Kubernetes Manages Containers Across a Cluster

Kubernetes adds another level of management when containerized applications need to run across multiple machines. Instead of managing each instance manually, operators define a desired state that Kubernetes automatically maintains. The platform can schedule workloads across different machines, maintain the required number of replicas, recover failed components, and manage updates.

Practical Example: A Restaurant with One or Multiple Kitchens

Imagine a restaurant where every dish is prepared at a workstation organized with all the necessary ingredients, tools, and instructions. Docker plays a similar role for applications: it provides a standardized environment where each component has what it needs to run.

If the restaurant has only one kitchen and relatively few orders, managing the operation is straightforward. Now imagine a chain with several kitchens and hundreds of orders. Someone needs to decide which kitchen should handle each order, redirect work when a problem occurs, add capacity during busy periods, and ensure that the required number of workstations is always available.

This is the role Kubernetes plays. Docker provides the environment in which individual applications can run, while Kubernetes coordinates multiple workloads and determines where and how they should run.

How Does Docker Work in Practice?

Docker allows an application to be packaged into a container image and then run consistently across different environments. The process involves several basic steps.

Creating a Container Image

A Dockerfile describes how the container image should be built, including the required environment, dependencies, and application files. The image can then be stored in a container registry and used for development, testing, or production.

Running and Managing Containers

Docker Engine uses container images to create and manage containers. They can be easily started, stopped, or replaced with a new version without modifying the application directly on the host.

Connecting Services and Storing Data

Docker provides networks for communication between services and volumes for persistent data storage. For example, an application can communicate with a database without the stored data depending on the lifecycle of a specific container.

Managing Multiple Services with Docker Compose

When an application includes several connected services, Docker Compose allows them to be defined and managed together. A single Compose file can define containers, networks, volumes, and their main settings so that the entire environment can be started as a unit.

The Restaurant Example

Returning to the restaurant example, a Dockerfile can be compared to the instructions for setting up a workstation: what equipment, ingredients, and tools are required. The container image is the ready-made model of that workstation, while Docker allows it to be created and used consistently.

When the restaurant needs several connected workstations, for example for main dishes, drinks, and desserts, Docker Compose defines how they should be organized and work together. This approach works well as long as everything can be managed within a single kitchen.

How Does Kubernetes Manage Containers Across a Cluster?

When containers run across multiple machines, they need to be scheduled, connected, scaled, and recovered when problems occur. Kubernetes automates much of this work by maintaining the predefined state of the applications.

Maintaining the Desired State

In Kubernetes, you define the desired state of the application, including the container image, the required number of replicas, and the resources it needs. If the actual state changes, the platform takes action to restore it.

Scheduling Workloads

Kubernetes distributes workloads across the available machines (nodes) in the cluster based on resource requirements and defined rules. This eliminates the need to place each instance manually.

Scaling and Recovery

Kubernetes can maintain the required number of replicas, replace failed Pods, and move workloads between different nodes. Actual resilience, however, also depends on the application's architecture, configuration, and infrastructure.

Connecting Services

Kubernetes Services provide a stable way for applications to communicate, even when individual Pods are replaced or moved, and their IP addresses change.

Controlled Updates

Kubernetes can gradually replace running instances with new versions through rolling updates. If a problem occurs, the deployment can be rolled back to a previous version without manually managing every container.

The main advantage of Kubernetes is this automated coordination. Instead of requiring the team to manage each container individually, the platform helps keep applications in the cluster running in line with predefined requirements.

This automation, however, comes with additional complexity. Kubernetes requires cluster management, networking, security, monitoring, and resource management. For smaller applications, that additional complexity may not always be justified.

How Do Docker and Kubernetes Work Together?

Docker and Kubernetes can be part of the same workflow. Docker is used to create and test the container image, which can then be stored in a container registry and deployed to a Kubernetes cluster.

Dockerfile → Image → Registry → Kubernetes → Pod

In other words, Docker prepares the application to run in a container, while Kubernetes manages where and how it runs within the cluster.

The Restaurant Example

Continuing with the restaurant analogy, Docker defines how each workstation should be set up, while Kubernetes organizes those workstations across different kitchens. One standardizes the individual environment, while the other coordinates operations at a larger scale.

Does Kubernetes Still Use Docker?

Not as a built-in container runtime. Support for dockershim was removed in Kubernetes 1.24, and the platform uses the Container Runtime Interface (CRI) to work with runtimes such as containerd and CRI-O.

This does not mean that container images created with Docker can no longer be used. They remain compatible with Kubernetes, so Docker can still be used to create the images while Kubernetes handles their deployment and management within the cluster.

When Should You Choose Docker, Docker Compose, or Kubernetes?

The choice mainly depends on the complexity of the application and how it needs to be managed.

Choose Docker When:

• you are working with individual containers;
• the application can run reliably on a single host;
• you do not need automated cluster-level management.

Choose Docker Compose When:

• the application includes several connected services;
• you want to manage containers, networks, and volumes as a single environment;
• all services can run on a single host.

Choose Kubernetes When:

• workloads need to be distributed across multiple machines;
• you need automated scaling and failure recovery;
• the application requires cluster-level management and updates.

Kubernetes is not necessarily the next step after Docker or Compose. If a simpler solution already meets the application's performance, availability, and scaling requirements, adding a cluster may only introduce unnecessary complexity.

Conclusion

For containerized applications, a more complex solution is not always better. For many projects, Docker or Docker Compose provides everything required, while Kubernetes makes sense when the scale and requirements call for automated management of multiple workloads. The key is to choose infrastructure that meets the application's actual needs without adding unnecessary complexity.

When those needs call for Kubernetes but you do not want to take on the full operational burden of managing the cluster, Delta.BG offers Managed Kubernetes. The service covers cluster design and deployment, as well as monitoring, security, updates, and ongoing maintenance. It can be deployed in our public cloud, on dedicated servers, in a colocation environment, or on your own on-premises infrastructure.

If you are considering Kubernetes for your applications, contact us at support@delta.bg or +359 2 4 288 288 to discuss your requirements.