Explore containers & Kubernetes – Master how Linux, Ansible & OpenShift function together, as explained at Parul University!

The modern enterprise technology stack is often presented to students as a list of tools to learn. That framing makes it harder to understand, because each layer exists to solve a problem created by the previous one. Learned in that order, the stack is a sequence of reasonable decisions rather than an arbitrary collection of names.

This guide follows that sequence, from the operating system underneath to the platforms built on top.

Enterprise infrastructure and cloud platforms run predominantly on Linux. It is the operating system underneath most servers, most cloud instances and, as it happens, most containers, which makes it the foundation rather than one option among several.

Enterprise distributions such as Red Hat Enterprise Linux exist because organisations need something beyond the software itself: predictable long-term support, security patching over a defined lifecycle, certified compatibility with hardware and applications, and someone contractually responsible when something breaks. That is what distinguishes a commercially supported distribution from a freely available one, and it is why large organisations pay for it.

For a student, the consequence is that Linux competence is not a specialism within infrastructure work. It is the prerequisite for the rest of this article to make sense.

Software has always been vulnerable to its environment. An application that runs correctly on a developer’s machine may fail in testing or production because a library version differs, a configuration file is absent, or a dependency is missing. The failure has nothing to do with the code.

A container solves this by packaging the application together with everything it needs to run, its libraries, dependencies and configuration, into a single unit that behaves identically wherever it is started. The environment travels with the application instead of being reconstructed at each destination.

This is the comparison that clarifies what containers actually are, and it comes down to what is being duplicated.

A virtual machine emulates an entire computer, including a complete guest operating system running on virtualised hardware. Running ten virtual machines means running ten operating systems, each consuming memory and storage and taking time to boot.

A container shares the host’s operating system kernel and isolates only the application and its dependencies. Running ten containers means running one operating system and ten isolated application environments. The result is that containers start in a fraction of a second rather than a minute, consume substantially less memory and storage, and can be packed far more densely onto the same hardware.

The trade-off is the isolation boundary. Virtual machines are separated at the hardware level and can run entirely different operating systems; containers share a kernel, which makes them lighter and means the separation between them is weaker. That distinction matters for security architecture and for workloads with different operating system requirements.

A virtual machine duplicates the whole computer. A container duplicates only the application’s environment. That is the entire difference.

Containers solved packaging and created a new problem. A single container is straightforward to run by hand. As an organisation runs different containers across multiple machines, it cannot manage them manually and must decide where each runs, restart failures, scale numbers, streamline traffic between them, and replace them during major updates without disturbing the core system. Kubernetes is a system that does this, and here are the core functionalities:

1. Scheduling: This decides which machine in a cluster should run each container based on availability, resources and constraints.

2. Self-healing: It detects failed containers or machines and replaces what was lost automatically. This entire process is performed without human intervention.

3. Scaling: It increases or reduces the running copies of an application in response to load.

4. Frequent updates and rollback: It replaces a version gradually so services remain available and in sync. Besides this, it can also revert changes when the new version is not working properly.

This conceptual shift in Kubernetes is declarative management. Instead of instructing the system to perform a specific action, an engineer defines the desired state and the system works to match that description. If something drifts apart, Kubernetes identifies the difference and works towards restoring the intended state. Understanding this inversion is a core part of learning it.

Kubernetes is powerful and, by itself, incomplete for enterprise use. It is a platform for building platforms, and running it in production requires assembling and maintaining a considerable amount around it: authentication, network policy, image registry, monitoring, logging, developer workflow and update management.

OpenShift is Red Hat’s enterprise Kubernetes distribution, which supplies those components as an integrated, supported product. It is Kubernetes underneath, with security defaults, integrated developer tooling, an image registry, monitoring, and a supported upgrade path assembled around it.

The distinction commonly asked about is therefore not one of function but of scope and responsibility. Kubernetes is the orchestration engine and the organisation assembles everything else. OpenShift ships the assembled platform with support attached. Which is appropriate depends on whether an organisation wants to build and maintain that surrounding layer itself.

The layers above still run on machines that must be configured, and doing that by hand does not scale. Configuration management addresses this by describing the intended configuration in code, which can then be versioned, reviewed and applied repeatedly.

Ansible describes desired system state in readable text files called playbooks and applies them across many machines at once. Two design decisions account for much of its adoption. It is agentless, connecting over standard remote access rather than requiring software to be installed on every managed machine first. And its operations are designed to be idempotent, meaning running the same playbook repeatedly produces the same end state rather than repeating changes, so it is safe to apply routinely rather than only once.

The practical effect is that infrastructure configuration becomes a versioned artefact rather than institutional memory. A server can be rebuilt from its description rather than reconstructed from someone’s recollection, which is also why automation skills have become central to infrastructure hiring and why the current RHCE certification is built around Ansible.

Certain misunderstandings recur among students learning this stack, and they cause avoidable confusion later.

• Containers are not lightweight virtual machines: They are isolated processes sharing a kernel. The distinction is not pedantry. It explains why containers start almost instantly, why they cannot run a different operating system from the host, and why their isolation boundary is weaker than a virtual machine’s.
• Kubernetes is not a hosting platform: It does not provide servers. It orchestrates containers across machines that must already exist and be maintained, whether physical, virtual or cloud instances. Something still has to manage what runs underneath, which is why Linux and configuration management remain relevant rather than being abstracted away.
• Adopting Kubernetes is not automatically an improvement: It introduces substantial operational complexity, justified when an organisation runs many services at scale and frequently not justified when it runs a handful. Knowing when a technology is unnecessary is part of understanding it, and it is a distinction that separates engineers from enthusiasts.

• Linux provides the operating system that everything runs on.
• Ansible configures those Linux systems consistently and reproducibly, from code.
• Containers package applications so they run identically across environments.
• Kubernetes orchestrates those containers across many machines, keeping them running and scaled.
• OpenShift packages Kubernetes with the additional components an enterprise needs, as a supported platform.

Each layer assumes competence in the one beneath it, which is why the learning order matters and why Linux is not optional. The careers guide to cloud and DevOps roles sets out how these skills map onto jobs, and the Red Hat certification guide covers how they are formally validated.