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Kubernetes manages containerized applications by comparing the cluster’s actual state with the state you declare and working to bring them into line. It is a powerful part of the cloud-native ecosystem, but it is not a complete application platform: teams still need to plan for releases, data, networking, observability, security, and the operation of the underlying infrastructure.

What does Kubernetes do?

The Kubernetes project describes Kubernetes as a portable, extensible, open-source platform for managing containerized workloads and services through declarative configuration and automation. In practical terms, you describe the outcome you want—such as how many copies of an application should run—and Kubernetes controllers continually work to move the cluster toward that desired state.

The platform provides mechanisms for service discovery and load balancing, storage orchestration, controlled rollouts and rollbacks, self-healing, and scaling. These capabilities can help keep an application running through changes or failures, but they do not guarantee availability. Application design, capacity, dependencies, storage, and infrastructure all affect whether a service stays available.

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Kubernetes is also extensible: organizations can select integrations for networking, storage, logging, monitoring, alerting, and other needs rather than relying on one mandatory stack.

How is a Kubernetes cluster organized?

A cluster consists of a control plane and worker machines called nodes. The control plane makes cluster-wide decisions and responds to events; nodes host Pods, the units in which application containers run. This is a reference model, not a fixed physical layout: component placement varies by cluster setup and requirements.

Control-plane components

  • API server: Exposes the Kubernetes API through which users and other components interact with the cluster.
  • etcd: Stores cluster data.
  • Scheduler: Selects a node for a Pod that has not yet been assigned one.
  • Controllers: Act on particular parts of cluster state, working to bring actual state toward the declared intent.

Node components

  • kubelet: Ensures that the containers specified in Pods are running on the node.
  • Container runtime: Manages container execution.
  • Networking support: kube-proxy may implement part of Service behavior; some network plugins provide an equivalent implementation.

Production control planes commonly run across multiple computers. A managed Kubernetes service may operate the control plane and may also manage nodes or supporting infrastructure. The exact division of responsibility depends on the service, so check its current documentation before deciding what your team must operate.

Which workload resource should you use?

Applications run in Pods, but most teams use workload resources to create and manage Pods rather than managing individual Pods directly. A Pod has its own lifecycle: if its node fails, the Pod can end, and a replacement is needed for recovery. Workload controllers act on your declared intent and maintain the relevant Pods.

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Resource Typical fit What to know
Deployment Stateless workloads with interchangeable Pods A common way to manage an application’s Pods; a Deployment uses a ReplicaSet to maintain the desired set.
StatefulSet Related Pods that need stable identity or persistent volumes It can associate Pods with persistent volumes, but does not by itself make application data safe. Data protection and recovery still need their own design.
DaemonSet Node-local facilities Runs Pods on each node that matches its scope, such as for a networking plugin or node-management component.
Job A task that runs to completion Defines work intended to finish rather than remain continuously running.
CronJob A task that should run repeatedly on a schedule Defines scheduled Jobs.

How applications are reached

A Service provides a way to make an application available within the cluster or to other consumers, depending on its configuration. For web applications, Ingress can provide an entry point for access. These networking resources do not remove the need to choose and configure the networking integrations that fit the cluster.

What does “cloud-native” mean beyond Kubernetes?

The CNCF Cloud Native Glossary describes cloud-native technologies as technologies for building applications in dynamic public, private, and hybrid cloud environments. Taken together, it says, these technologies support loosely coupled systems that are resilient, manageable, and observable. Cloud-native is therefore broader than using Kubernetes or hosting an application with a cloud provider; it describes an ecosystem and an approach to building and operating applications.

Kubernetes is one project in the wider CNCF ecosystem, not the whole ecosystem. A useful way to map the surrounding technologies is by the problems they address:

  • Packaging and runtime: How application components are packaged and run as containers.
  • Networking and storage: How workloads communicate and use persistent data.
  • Deployment and configuration: How teams declare, release, and change workloads.
  • Observability: How teams collect the signals needed to understand system behavior.
  • Security: How teams protect software, access, workloads, and infrastructure.
  • Managed platforms: How infrastructure providers take on some cluster-operating responsibilities.

There is no single required stack for these categories. The choices depend on the application, operating environment, and the responsibilities a team is prepared to own.

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What Kubernetes does not provide for you

Kubernetes documentation explicitly says it is not a traditional, all-inclusive platform as a service. It does not build source code, prescribe a CI/CD workflow, mandate one logging, monitoring, or alerting solution, or provide every application service—such as databases and message buses—as a built-in service. Instead, it offers building blocks and integrations.

That boundary has practical consequences. Before adopting Kubernetes, decide who will operate the control plane and nodes; how applications will be packaged and released; how data will be backed up and recovered; which networking and storage integrations meet your needs; how monitoring and alerting will be assembled; and how software and cluster access will be secured. A managed service may take on some infrastructure work, but it does not automatically settle every application or operational decision.

What security work remains?

Kubernetes security is lifecycle work, not a single setting. Official Kubernetes security guidance covers software integrity and trusted artifacts, deployment restrictions, API authentication and authorization, TLS, workload isolation, and the security of the infrastructure beneath the cluster. A practical starting checklist is:

  1. Control API access: Decide who can reach the API and what each identity is authorized to do. Review the use of ServiceAccounts as well as human access.
  2. Restrict deployments: Set rules for what workloads may be deployed and where they may run.
  3. Validate software: Scan images and artifacts, and establish how trusted software is distributed.
  4. Limit workload privileges: Apply isolation and privilege settings appropriate to each workload.
  5. Protect secrets and keys: Decide how sensitive values and encryption keys are stored, accessed, and protected.
  6. Prepare for runtime incidents: Plan monitoring and response for the environment, including the infrastructure that supports the cluster.

This checklist is a starting point, not a complete security standard or audit. The right controls depend on the workloads and the infrastructure they run on.

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Should you use managed or self-managed Kubernetes?

The main distinction is operational responsibility, not a different workload model. With self-managed Kubernetes, your organization operates the components it deploys, including the relevant control-plane and node infrastructure. With a managed service, the provider takes responsibility for some parts of that work; the scope varies, and a provider may manage the control plane, nodes, and supporting infrastructure to different degrees.

Before choosing, establish exactly which components the service operates and which remain yours. Also consider how much infrastructure and networking integration is abstracted, what portability constraints apply, and how the service’s cost model fits your needs. The architecture alone does not establish a provider’s current service scope, regional availability, or pricing.

How should you think about Kubernetes documentation over time?

Kubernetes documentation is live and features can change between releases. Check the documentation for the version you plan to use before relying on version-specific behavior or instructions. The basic mental model—declared intent, controllers, Pods, and cluster components—helps orient you, but the current version and service documentation should guide implementation.

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