The Kubernetes architecture allows for the deployment of applications quickly and predictably, scaling applications on the fly, easily rolling out new features, and limiting hardware usage to required resources only. This has made Kubernetes a standard tool for DevOps practices, supporting practices like microservices, continuous integration, and continuous delivery (CI/CD).
What Are Containers?
Containers are lightweight, executable software packages that include everything needed to run a piece of software, including the code, runtime environment, libraries, and system settings. Unlike traditional virtual machines, containers do not bundle a full operating system — only the components necessary to make the software function, allowing for efficient use of system resources.
Containers encapsulate the application environment, making development, testing, and deployment processes more consistent and predictable across different environments. They offer a logical packaging mechanism, reducing the gap between what is developed and what is deployed, enabling continuous delivery and deployment.
In this article:
- Kubernetes vs. Docker Containers: What Are The Differences?
- Core Concepts of Kubernetes Container Management
- What Are the Benefits of Managing Containers with Kubernetes?
- Best Practices for Managing Kubernetes Containers
Kubernetes vs. Docker Containers: What Are The Differences?
Kubernetes and Docker serve different but complementary roles in the container ecosystem. Docker is a containerization platform that enables developers to package applications into containers—standardized executable components combining application source code with the operating system (OS) libraries and dependencies required to run that code in any environment.
Kubernetes does not build or run containers by itself. Instead, it is a container orchestration platform that manages containers created by Docker or other container runtime environments. Kubernetes provides the infrastructure for deploying, scaling, and managing containerized applications at scale. It focuses on the coordination of containers running on multiple hosts.
Core Concepts of Kubernetes Container Management
Pods
Pods are the smallest, most basic deployable objects in Kubernetes. A pod represents a single instance of a running process in your cluster. Pods contain one or more containers, such as Docker containers. When a pod runs multiple containers, Kubernetes manages the containers as a single entity, facilitating shared resources like networking and storage.
This architecture allows closely related containers to share the same lifecycle—for example, an application container and its helper containers. When packaging containers in pods, they should be as lightweight as possible, focusing on a single responsibility per container for modularity and scalability.
Controllers
Controllers are control loops that watch the state of your cluster, then make or request changes where needed. They aim to move the cluster’s current state closer to the desired state in a managed, predictable way. Controllers utilize pods and nodes to ensure that your application runs efficiently and resiliently.
Various types of controllers exist within Kubernetes, including ReplicaSets, Deployments, and StatefulSets. Deployments, for example, manage the deployment and scaling of a set of pods and ensure that the number of actual replicas matches the desired state defined by the user.
Services
Services in Kubernetes provide a stable endpoint for accessing the set of pods that comprise an application. While pods may come and go, the service ensures that network traffic can be directed to the appropriate pods at any given time. This is crucial for maintaining a consistent access point and enabling service discovery within the cluster.
Services match a set of pods using labels and selectors, allowing users to manage pods effectively. They act as load balancers, distributing incoming requests across all available pods to maintain optimal performance and availability.
Namespaces
Namespaces provide a mechanism for isolating groups of resources within a single Kubernetes cluster. They can be seen as a layer of abstraction added to the cluster to allow multiple teams or projects to share the cluster without overlapping. Namespaces help manage resources by dividing the cluster’s parts into smaller, more manageable pieces.
This division supports scenarios where multiple teams or projects are using a single cluster. By isolating their resources, namespaces help improve security, efficiency, and management of the cluster, allowing for detailed access control and resource allocation.
Storage
Kubernetes abstracts and manages storage to provide containers with a consistent, accessible, and dynamic resource. PersistentVolume (PV) and PersistentVolumeClaim (PVC) are two key concepts in Kubernetes storage. PVs are storage units provisioned by the administrator, while PVCs are requests for storage by users. Kubernetes binds PVCs to PVs, ensuring that storage is available to containers as needed.
This separation of storage from the detailed management layer enables Kubernetes to automate the provisioning of storage based on the application’s requirements. It supports a variety of storage backends, including local storage, public cloud providers, and network-attached storage (NAS).
What Are the Benefits of Managing Containers with Kubernetes?
Containerization is a flexible and scalable approach to application development and deployment. Using Kubernetes as the container orchestration engine offers the following benefits:
Effective Management of Large Numbers of Containers
Kubernetes excels in managing large-scale container deployments, offering a highly efficient way to orchestrate vast numbers of containers across multiple hosts. Its architecture is designed to facilitate easy scaling, monitoring, and management of containerized applications, regardless of their complexity.
This capability is especially beneficial in environments where applications need to scale dynamically in response to changing demand, ensuring that resources are optimally utilized and costs are kept in check.
Automating the Application Lifecycle
Kubernetes automates various aspects of the application lifecycle, from deployment and scaling to updating and maintenance. It provides robust mechanisms for deploying new versions of applications, managing configuration changes, and maintaining application health.
Kubernetes also automates the process of scaling applications up or down based on demand, helping to manage resource consumption efficiently. This automation extends to self-healing capabilities, where Kubernetes can detect and replace non-responsive or failing containers, ensuring high availability and reliability of applications.
Easier Application Deployment and Updates
Kubernetes streamlines the deployment and updating of applications through its robust orchestration capabilities. By abstracting away the complexity of managing the underlying infrastructure, it allows developers and operations teams to deploy applications and roll out updates with minimal effort.
Kubernetes achieves this through declarative configuration and automation, enabling seamless updates and rollbacks. This means that changes, including new features and bug fixes, can be introduced rapidly and safely, significantly reducing the time-to-market for new versions. The platform’s ability to manage multiple versions of an application enables canary deployments and A/B testing, further enhancing the flexibility and reliability of application updates.
Environmental Consistency Across Machines and Clouds
Kubernetes offers a consistent environment for applications across different hosting scenarios, whether on-premises, in public clouds, or a hybrid approach. This consistency simplifies operations, as developers can work with the same tools and processes regardless of the underlying infrastructure.
Resource Isolation and Predictable Performance
Kubernetes provides mechanisms to isolate resources, ensuring that each container has access to the required resources without affecting others. This isolation improves security and resource utilization, leading to predictable application performance. By specifying resource requests and limits for each container, Kubernetes can make intelligent scheduling decisions, optimize resource allocation, and prevent any single application from monopolizing system resources.
Related content: Read our guide to Kubernetes architecture
Best Practices for Managing Kubernetes Containers
Here are a few best practices that can help you effectively manage containers in Kubernetes.
Create Lightweight Containers
The smaller the container image, the faster it can be pulled from a registry and started, reducing deployment and scaling times. Optimize container images by including only the necessary binaries and dependencies. Use multi-stage builds in Dockerfiles to remove unnecessary artifacts before the final image is created.
Use Multi-Container Pods Sparingly
While Kubernetes pods can contain multiple containers, it’s generally best to keep pods focused on a single responsibility. Using multi-container pods can increase complexity, making pods harder to manage and scale. Reserve multi-container patterns for tightly coupled application components that must share resources.
Specify CPU and Memory Requests and Limits
Requests specify the minimum amount of resources needed, ensuring the container has enough to function. Limits prevent containers from consuming excessive resources, which could impact other applications. Properly configured requests and limits enable Kubernetes to make informed scheduling decisions, placing containers on the most appropriate nodes and maintaining cluster efficiency.
Utilize Rolling Updates for Deployments
Rolling updates allow you to update a set of pods gradually with new container images. This method ensures that the application remains available during the update, minimizing downtime and risk. By default, deployments in Kubernetes use rolling updates to replace old pods with new ones. This strategy can be controlled and fine-tuned with the deployment’s configuration, enabling you to specify the speed and method of the update.
Minimize Container Privileges
Containers should run with the least privileges necessary for their operation, restricting their capabilities within the system. Use security contexts to enforce security settings and minimize the risk of security breaches. Limiting privileges includes running containers as non-root users, disabling privilege escalation, and using read-only filesystems when possible.
Learn more in our detailed guide to Kubernetes management
Secure Kubernetes with Aqua
Aqua tames the complexity of Kubernetes security with KSPM (Kubernetes Security Posture Management) and advanced agentless Kubernetes Runtime Protection.
Aqua provides Kubernetes-native capabilities to achieve policy-driven, full-lifecycle protection and compliance for K8s applications:
- Kubernetes Security Posture Management (KSPM) – a holistic view of the security posture of your Kubernetes infrastructure for accurate reporting and remediation. Helping you identify and remediate security risks.
- Automate Kubernetes security configuration and compliance – identify and remediate risks through security assessments and automated compliance monitoring. Help you enforce policy-driven security monitoring and governance.
- Control pod deployment based on K8s risk – determine admission of workloads across the cluster based on pod, node, and cluster attributes. Enable contextual reduction of risk with out-of-the-box best practices and custom Open Policy Agent (OPA) rules.
- Protect entire clusters with agentless runtime security – runtime protection for Kubernetes workloads with no need for host OS access, for easy, seamless deployment in managed or restricted K8s environments.
Open Source Kubernetes Security – Aqua provides the most popular open source tools for securing Kubernetes, including Kube-Bench, which assesses Kubernetes clusters against 100+ tests of the CIS Benchmark, and Kube-Hunter, which performs penetration tests using dozens of known attack vectors.
