The Amazon company has been known to deploy code as often as every 11.6 seconds. How?
The process of creating and launching new applications has been streamlined significantly. No longer does a software release require a seemingly unending process spanning several months. Companies are now releasing new features and fixing problems incredibly fast. This is thanks to new ways of developing software, like DevOps and using special technologies called containers and Kubernetes. This rapid delivery directly impacts how quickly applications can be made available through web hosting and other online services.
In this blog post, we are going to explore what a container in the Kubernetes context means, where it fits into the architecture, what its defining features are, and why it matters for developers, DevOps engineers, and, most importantly, cloud-native deployments.
Table Of Content
Understanding Kubernetes: Overview
The efficiency gained from deploying new applications is offset by the complexities involved with managing microservices, distributed systems, and multi-cloud environments. To tackle these complexities, open-source tools like Kubernetes have been developed. Kubernetes is known for automating the deployment, scaling, and management of containerized applications. However, to understand the core features and capabilities that Kubernetes offers, we need to start with the building block of its architecture: the container and its benefits.
Kubernetes work by orchestrating containers, which are self-contained units that hold all necessary resources for an application’s operation. Each of these unit containers constitutes the underpinning blocks of Kubernetes scaffolds, schedules, and dynamically scales across your infrastructure.
Related Read: What is Kubernetes Monitoring?
What Are Containers (In General)?
Before defining containers within the context of Kubernetes, it is important to look at them through a wider lens first. One of the most irritating challenges as far as any developer is concerned is where the software, when deployed, behaves differently depending on the environment.
Containers address this challenge by providing a standardized, portable executable that runs uniformly on a developer’s laptop and in production settings.
Containers are self-sufficient units of software that can be executed. Each container encompasses all the resources required to execute an application, including its code, libraries, system tools, runtime, and dependencies. This encapsulation guarantees that an application will function identically wherever deployed.
Containers do not require an entire operating system per instance like virtual machines (VMs) do; they use the host OS kernel, which makes them more lightweight and quicker to start. Most resources can be used effectively because many containers can run simultaneously due to the efficiency of the systems.
Most of the container-based revolution comes from Docker, the most popular containerization platform. It simplified the building, packaging, and sharing of containers, enabling orchestration tools like Kubernetes to manage large systems.
Having this basic idea of containers is necessary to understand containers in Kubernetes and their role within the system.
What Are Containers In Kubernetes?
Let’s know in detail about what a Kubernetes container is. Kubernetes is built to control containers in large quantities. It doesn’t matter how the container is created using Docker or other tools. Kubernetes uses an industry-grade standard like Open Container Initiative to check container compliance and compatibility. As long as the container meets these standards, it can be orchestrated by Kubernetes without any hassle.
Related Read: Kubernetes vs Terraform: Decoding the Differences, Pros and Cons
Pods: The Basic Building Block of Kubernetes
A widespread misunderstanding is the use of Pods in Kubernetes. Kubernetes makes use of the Pods containing several containers. A respite is that a Pod works as a template that can be duplicated sometimes. A Pod is defined as the type of the lowest manageable block in the hierarchy of a Kubernetes cluster. It is the smallest quantifiable part of a distribution system.
The contents in a Pod share the same network namespace and IP address, making it possible to share storage and speed recharge drives. In simple terms, a container in Kubernetes is always found within a Pod.
Kubernetes considers a Pod instead of distinguishing a container as a unit, depending on which scheduling, counter, scale, and control features are used, as Pods are the best solution when multiple tightly coupled, long-living shared processes that have to use a single resource wrapper for threads, such as web server logging, are started and managed together.
– Container Runtime Interface (CRI)
Kubernetes does not run containers by itself; it relies on an abstraction layer called Container Runtime Interface (CRI), which communicates between the Kubernetes container orchestrator and container engines. The abstraction makes it possible for orchestrators like Kubernetes to operate with multiple container runtimes such as containers, CRI-O, and even Docker’s underlying runtime.
The abstraction layer also answers the question “Which containers does Kubernetes support?” Thanks to the CRI, any container runtime that adheres to the set standards will be supported – this modular design ensures adaptability as technology progresses.
Types of Containers in Kubernetes Pods
Now you have the answer to what a container is in Kubernetes, but there is a curious fact you must know: not every container in a Pod has the same objective. Within Pods, Kubernetes allow different types of containers to be nested, which, in collaboration, ensures operational efficiency and optimal resource utilization.
A. Main Application Containers
These containers will execute the application logic: web server, API, background job, and all that. Usually, a Pod contains one main container – the simplest deployment model. But advanced setups have more than one container per Pod, thanks to helper containers like sidecars.
B. Sidecar Containers
The sidecar pattern is associated with secondary containers that are separated from the main application container within the same Pod. These auxiliary containers add value to the primary container without changing its code. Other examples are log shippers, proxies, monitoring agents, or services that synchronize data between environments.
What are the benefits? Sidecars support modularity, language agnosticism, and reusability with ease, which aids in the development of flexible and easily maintainable applications.
C. Init Containers
What is an Init container in Kubernetes? As the name suggests, Init containers are special-purpose containers that run before any of the main application containers have started. They serve to perform setup activities such as:
- Waiting for a certain service to start
- Fetching configuration files
- Executing database migrations
- Conducting system checks
Related Read: Kubernetes Vs. OpenShift: Key Differences to Know
Comparison of Container Types in Kubernetes Pods
| Container Type | Purpose | Execution Order | Lifespan | Example Use Case | Shared Resources |
| Main Container | Runs the core application | After all Init containers have completed | Long-running | Hosting a Node.js app or API server | Yes (with other containers in the Pod) |
| Sidecar Container | Adds supporting functionality (logging, proxy, etc.) | Starts with the main container | Long-running | Fluentd for logging or Envoy proxy | Yes (network, volume) |
| Init Container | Performs setup tasks before the main app starts | Runs before main and sidecar containers (in sequence) | Run-to-completion | Waiting for a database to be ready | No (runs separately but shares volume/network once started) |
The Relationship Between Containers and Kubernetes
Let’s discuss how Kubernetes interacts with Pods in terms of deployment and runtime.
A. Image Pulling
Kubernetes fetches the container image from a container repository, such as Docker Hub, Google Container Registry (GCR), or Amazon ECR, as soon as you create a Pod. The image includes all the application code along with its dependencies. Kubernetes fetches the required image version as per the deployment manifest.
B. Creation and Life Cycle of Containers
Every node in a Kubernetes cluster has a Kubelet component that runs in the background. Kubelet connects to the container orchestrator, which may be containerd or CRI-O, and it communicates with the container runtime. Kubelet instructs the runtime to build and Initialize the container for the Pod. Liveness Probes, Readiness Probes, and Startup Probes for Kubernetes health monitoring are deemed as Liveness, Readiness, and Startup checks.
C. Managing Resources
It is possible to set a restriction on the amount of CPU and RAM that can be allocated to every container. These resources are designed as requests and limits. Requests guarantee that the specified amount is received, and limits ensure no excess consumption. This balance enables consistent performance while allowing Kubernetes to efficiently manage Pod distribution across nodes.
D. Networking
The containers in a single Pod can communicate with each other through localhost because they share the same network namespace. A unique IP address is allocated to each Pod, and it is the responsibility of Kubernetes to manage the networking so that the Pods communicate with each other and with services outside the Kubernetes system.
E. Storage
Although containers are not persistent and data is deleted every time, Kubernetes resolves this issue with Pods, which can utilize Volumes and Persistent Volumes. Log files, databases, and other data that need to be retained through restarts can now be reliably handled thanks to the Attachable containers that can hold data between restarts.
Kubernetes Container Lifecycle & Interaction Components
| Stage | Kubernetes Component | Description | Technical Notes |
| Image Pulling | Kubelet & Container Runtime | Pulls container images from registries like Docker Hub, GCR, or ECR | Respects imagePullPolicy (Always, IfNotPresent, Never) |
| Container Start | Kubelet & CRI-compatible runtime | Instructs runtime (containerd, CRI-O) to create and run the container | Works via the Container Runtime Interface (CRI) |
| Health Checks | Kubelet | Uses liveness, readiness, and startup probes to monitor container health | Failure in probes can trigger restarts or remove Pods from load balancer |
| Resource Enforcement | Scheduler & Kubelet | Enforces resource requests and limits (CPU, memory) per container | Overcommitting resources can lead to eviction |
| Networking | CNI Plugin & Kubernetes Network Model | Assigns Pod IPs and manages intra-Pod/container communication | All containers in a Pod share the same network namespace |
| Storage Mounting | Kubelet & Volume Plugins | Mounts persistent or ephemeral volumes to containers | Supports hostPath, NFS, cloud volumes (EBS, GCE, etc.) |
Benefits of Containerizing Applications for Kubernetes
Containers with Kubernetes across the application development lifecycle offer numerous advantages, from ease of management to enhanced reliability and speed of development.
– Consistency & Portability
The portability that comes alongside containers is unparalleled, as it is possible to build once and run on any developer’s laptop, Kubernetes cluster, staging server, or production cluster. This uniformity eliminates bugs caused by deploying to different environments and streamlines the entire deployment workflow.
– Isolation
Applications and other SDKs do not interfere with one another, owing to the independent containers that they are run in. This strengthens security and reduces cross-service dependency clashes.
– Scalability & Resilience
The efficiency that Kubernetes gives for the automatic scaling of applications with increasing traffic volume is unmatched in container orchestration. In addition to that, if any container crashes, Kubernetes is responsible for the replacement, which restores high availability with little hands-on effort.
– Unlimited DevOps
Kubernetes containers are an instrumental component in a modern DevOps ecosystem. They facilitate support for CI/CD pipelines, microservices adoption, and easier risk deployment updates and rollbacks.
Combining containers and Kubernetes bestows teams with the agility, speed, and dependability necessary to excel in the current cloud-native environment.
Containers serve as fundamental components for portable, reliable applications that Kubernetes orchestrates today. Through Pods, Kubernetes manages containers, enabling powerful and flexible deployment and maintenance of complex systems.
To leverage the full potential of container orchestration, it is important to understand the components of Kubernetes containers, including their workings inside Pods, main, sidecar, and Init containers.
FAQs
In what way do containers give the “portable” aspect for applications running in Kubernetes?
Kubernetes can execute an application on any infrastructure system as Pods because Containers comprise everything an application entails, like the code, libraries, and the environment—ensuring consistency during development, testing, and production.
Does Kubernetes build or create containers by itself, or does it depend on other tools?
Kubernetes needs external tools to build containers, such as Docker, Buildah, or any other OCI-compliant tools that create images. He then uses a container runtime like containers or CRI-O to pull and execute the images.
Why are Pods the smallest deployable unit in Kubernetes as opposed to individual containers?
Kubernetes works with Pods as they designate a container or containers to a single logical entity. The Pods have a shared network and storage context, making collaboration much tighter than what individual containers do.
