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Top 15 Kubernetes Use Cases


Kubernetes has changed how organizations deploy, test, and scale their applications. Right now it’s the most popular container orchestration platform in the world, and being maintained by the Cloud Native Computing Foundation (CNCF), gives you the confidence of a massive community and active development.

In this article, we will explore the top use cases for Kubernetes, see where it truly shines, understand how it benefits your organization, and see when you shouldn’t use it.

What is Kubernetes?

Kubernetes (K8s) is an open-source container orchestration platform that was initially created by Google, and now it is available under CNCF’s umbrella. Its first release was in September 2014, just one year after Docker was initially released.

K8s uses YAML to declare its resources which makes it declarative by design, making it easy for you to describe the state of your Kubernetes clusters in YAML files, rather than running imperative commands. This key feature of K8s enables automation, scalability, and self-healing.

Let’s explore the core concepts of Kubernetes:

  • Nodes: These are your worker machines, which can be either virtual or physical that run your Kubernetes workloads. Each node has a kubelet (used to interact with the control plane), and a container runtime (such as containerd or CRI-O)
  • Cluster: This is a group of nodes managed by a control plane. The control plane includes the API server, scheduler, controller manager, and etcd (key-value database store for state).
  • Pods: These are the smallest deployable units in Kubernetes, encapsulating one or more containers, that share the same network and storage volumes
  • Controllers: With controllers you ensure that your cluster maintains the desired state of your K8s components
  • Services: These are used to expose your pods under a stable IP or DNS name. The can enable load balancing and reliable communication between different microservices that form your application.

Kubernetes Use Cases

Now that you have a high level idea of what Kubernetes is, and its main components, let’s see what are its use cases:

1. Working with Microservices

2. Auto-scaling Applications

3. Multi-Cloud and Hybrid Cloud Deployments

4. CI/CD pipeline integration

5. Batch processing and job management

6. High availability and disaster recovery

7. Getting into Tech

8. Machine learning and AI workloads

9. Development environment standardization

10. Legacy Application modernization

11. Edge Computing and IoT

12. Multi-Tenant SaaS platforms

13. Event driven and serverless computing

14. Implementing compliance

15. Content delivery and media processing

TL;DR?

1. Working with Microservices

When working with traditional monolithic applications, it is hard to maintain, scale, and deploy new versions of these apps as they grow. Different components might have different resource requirements and scaling needs, and it is very difficult to satisfy these needs in traditional software development, so in the end, you need to provide way more resources, which increase your overall costs.

Using microservices, and more specifically, using them from Kubernetes, helps you solve many of these issues, by splitting your applications into smaller pieces that are managed independently. In this way, you can ensure that your microservices receive exactly how many resources they need, and when they need them, and in case of failures, your application won’t be down, only a part of it will not function properly, ensuring some sort of reliability, even without high availability or disaster recovery enabled.

Kubernetes excels at managing microservices because it enables service discovery through built-in DNS and other abstractions, gives you the ability to scale individual services based on demand, enables rolling deployments which let you update services without any downtime, and gives you network policies that ensure secure communication between all of your services.

2. Auto-scaling Applications

Whenever you are working with applications in production, you will notice that their traffic patterns are almost unpredictable. Scaling the applications up or down manually, will make your processes inefficient and error-prone.

Kubernetes offers multiple scaling solutions such as:

  • Horizontal Pod Autoscaler (HPA): automatically scales your pods based on CPU usage, memory usage, or even custom metrics
  • Vertical Pod Autoscaler (VPA): adjusts resource requests and limits
  • Cluster Autoscaler: adds or remove nodes based on resource demands, reducing costs when your traffic is stale
  • Scaling through Keda: enables event-driven autoscaling
  • Scaling through Karpenter: autoscaling that gives you the ability to also use lower-cost spot instances

If you want to see how to manage AWS EKS at scale, check out this article.

3. Multi-Cloud and Hybrid Cloud Deployments

More and more organizations are shifting from using a single cloud vendor to multiple cloud vendors, or in some cases having a mixture of cloud and on-premise services. Enterprises with compliance or cost requirements are embracing hybrid setups, keeping their sensitive data in private data centers, while leveraging cloud’s elasticity.

Kubernetes enables you with portable workloads that can run anywhere K8s is available, making it easy to deploy your apps regardless of the infrastructure you are using. It has the same consistent APIs, so you don’t need to tweak your applications in order to accommodate your cloud provider APIs, as Kubernetes manifests and Helm charts act as universal blueprints.

4. CI/CD pipeline integration

Traditional CI/CD processes can be manual and slow, and you already know how many bottlenecks they create. The majority of the CI/CD pipelines you are using can leverage Kubernetes native workers. Apart from that, there are CI/CD tools like ArgoCD, Flux, Tekton, and Jenkins X that run natively on your Kubernetes clusters, automating all CI/CD processes.

Kubernetes helps you unlock:

  • GitOps workflows with ArgoCD and Flux transforming your version control system in a single source of truth
  • blue-green deployments to switch traffic between two environments with 0 downtime
  • canary deployments to test new releases on a subset of users before a full rollout
  • integration with your existing CI/CD tools such as Jenkins, GitHub Actions, GitLab CI/CD, or Circle CI

5. Batch processing and job management

Not all of your workflows need to run all the time. Some of your jobs need to run once, while others have to be scheduled to repeat on a cadence. Running these tasks which can also be data processing jobs, or even machine learning workloads, can be very challenging, especially when done at scale.

Kubernetes helps you with:

  • Job and CronJob resources for one time jobs and scheduled tasks
  • Resource quotas and limits to ensure your jobs are not consuming all of your cluster resources
  • Node affinity, taints, and tolerations to ensure your jobs run on the appropriate hardware
  • Integrations with workflow engines such as Kubeflow or Argo Workflows

6. High availability and disaster recovery

In software development, you should always ensure that your applications are highly available, and they can recover quickly from failures.

Kubernetes offers many built-in mechanisms to support high availability (HA) and disaster recovery (DR). You can leverage features such as replicate sets, multi-zone deployments, pod and node failure handling with automatic rescheduling, health checks, and self-healing capabilities.

By implementing HA and DR, you will reduce the risk of financial or reputational damage, ensuring thus a resilient and enterprise-grade system.

7. Getting into Tech

One of the biggest overlooked values of Kubernetes lies in its power to be installed locally by leveraging small distributions. This is very powerful because in this way, you will get everything you need to learn many interesting concepts that are related to engineering.

By running a couple of simple commands, you can have a Kubernetes cluster up and running, and from there, you can start learning Linux concepts, CI/CD workflows, networking, and even application deployment strategies.

Instead of being limited to theory, you gain a safe and reproducible playground where you can experiment, break things, and fix them again, exactly how real world experience is built.

You can use small distributions such as Minikube, k0s, kind, or k3s, as they lower the barrier to entry by reducing the complexity of installation.

8. Machine learning and AI workloads

In 2025, machine learning and AI have become non-negotiable. ML workloads have unique requirements including GPU access, distributed training, and model serving at scale.

To satisfy all of these demands, organizations are increasingly turning to Kubernetes as the foundation of their AI infrastructure. Kubernetes helps with:

  • GPU scheduling and resource management
  • Distributed training with frameworks like TensorFlow and PyTorch
  • Model serving with tools like KServe
  • Jupyter notebook environments

In addition to that, by enabling multi-tenancy and cost optimizations, you can share a common platform with isolated namespaces, reducing unnecessary costs.

9. Development environment standardization

If you are fed up with hearing “it works on my machine”, Kubernetes can easily help you overcome this syndrome where your apps are behaving differently across your environments.

With Kubernetes you can easily get consistent environments, namespace isolation, resources limits to prevent one team’s work from affecting the others, and easy environment replications by leveraging Infrastructure as Code (IaC).

The majority of successful organizations create Kubernetes-based development environments that replicate to production ones to enable developers to test their features in realistic conditions.

10. Legacy Application modernization

Many organizations still rely heavily on legacy applications that were not designed with cloud-native principles in mind. These systems continue to deliver business value, but they often have issues with scalability, maintainability, and integrations.

Kubernetes helps you modernize these applications by:

  • Implementing containerization of your existing apps without major code changes
  • Doing gradual migration by extracting services piece by piece
  • Integrating service meshes for advanced networking and observability
  • Relying on sidecar patterns for adding functionality without modifying application code

You shouldn’t think about this modernization as discarding the old, but rather think of it as enabling for the future.

11. Edge Computing and IoT

Edge computing has become more and more popular in the last few years, and deploying applications across these locations can be challenging.

Kubernetes is a natural fit for managing workloads in these distributed environments, and leveraging lightweight distributions such as k3s are specifically optimized for these kinds of devices.

From an IoT perspective, K8s helps you manage the scale and diversity of your devices. With thousands of endpoints generating streams of data, you need to implement orchestration to ensure that updates, patches, and new versions can be consistently deployed across your entire fleet.

If you think about AI and ML workloads, you can run inference models locally, at the edge, reducing the dependency on network connectivity and accelerating responses.

12. Multi-Tenant SaaS platforms

In SaaS environments, a single application instance serves multiple customers, so you need a way to provide secure environments for them, while efficiently sharing the underlying infrastructure.

Kubernetes helps you by:

  • Leveraging namespace-based isolation for multi-tenancy
  • Implementing network policies for secure tenant separation
  • Taking advantage of resource quotas to prevent tenant resource conflicts
  • Implementing RBAC integrations

With K8s you can build architectures that are secure and scalable, and are able to serve hundreds or thousands of customers without fragmenting their infrastructure or sacrificing agility.

13. Event driven and serverless computing

Modern applications are increasingly built around event-driven architectures, where systems respond to events in real time, rather than relying on fixed schedules. If you are trying to build applications to respond to events efficiently, you should always keep in mind that resource consumption during idle periods must be minimized.

With Kubernetes you can:

  • Use KEDA integrations for event-driven autoscaling
  • Leverage Knative for serverless workloads
  • Take advantage of scale-to-zero capabilities for cost optimization

If you think about banking systems, it’s pretty clear that most of them are using event-driven Kubernetes apps to process transactions, scaling from zero to thousands of instances based on the transaction volume.

14. Implementing compliance

Frameworks like GDPR, HIPAA, SOC 2, and others have strict requirements on how applications handle data, access control, and how auditability is implemented.

Kubernetes offers you RBAC, networking policy, and pod security standards to enforce the principle of the least privilege, and minimize the attack surfaces. In addition to that it integrates with logging and observability stacks (Prometheus/Grafana, ELK), Policy as Code (OPA Gatekeeper of Kyverno), and vulnerability scanner tools for your K8s configurations or images (Trivy).

You should always think of compliance as a continuous process, and enable checks into CI/CD pipelines, to ensure that your deployments align with the required standards.

K8s can be a strong enabler of compliance inside your organization, if you combine it with the right tools, processes, and implement compliance in your org’s culture.

15. Content delivery and media processing

The demand for digital content has increased significantly because of streaming platforms, online gaming, user-generated media, and even interacting events.

Kubernetes plays an important role for your digital assets, by orchestrating distributed workloads for tasks like video transcoding, image processing, and streaming optimization.

It helps you with:

  • GPU scheduling for video transcoding workloads
  • Horizontal scaling based on processing time, or even queue depth
  • Job scheduling for batch media processing

Getting started with Kubernetes

You should initially get familiar with containers and containerized applications, and after that you will be ready to jump into Kubernetes.

Here’s a cheatsheet on how to get started with Kubernetes:

  1. Before diving into installing Kubernetes and running different Kubernetes commands, get familiar with all the core concepts mentioned in the beginning of this article (clusters, pods, nodes, controllers, services, etc.)
  2. Choose a local setup that you can easily install, break, and reinstall such as Minikube, Kind, MicroK8s, or Docker Desktop
  3. Install kubectl – this is the command line tool for interacting with your cluster. You should install it from the official docs, and explore what you can do with it by running kubectl -h
  4. Deploy your first hello world application. Example here.
  5. Learn how to write Kubernetes manifests for the basic components: namespaces, pods, deployments, services, configmaps, secrets.
  6. Inspect your resources with get/describe/logs commands
  7. Explore other core features (scaling, probes, ingresses, resource requests and limits)
  8. Learn by experimenting – build your own applications and deploy them in Kubernetes, use ingress controllers for real routing, observe self-healing
  9. Once your comfortable explore managed services (AWS EKS, AKS, GKE), Helm/Kustomize, observability tools, and GiOps

To make everything even more accessible, you should give Lens Kubernetes IDE a try, as it will help you easily visualize everything that you are trying to learn.

When not to use Kubernetes?

Even though Kubernetes may seem the right choice for every workload, it is not always true. There are a couple of reasons for why you should not use Kubernetes such as:

  • You have a small and simple application – in this case, you don’t need all the complexity that is associated with Kubernetes, you can get by keeping things simple
  • Your team doesn’t have container experience – they should first build a solid foundation in the container world. Starting with Docker or Podman is often a better path before diving into Kubernetes.
  • You have strict resource constraints – in small environments where hardware is limited, the overhead of keeping Kubernetes up and running might outweigh the benefits
  • You don’t need high scalability of availability – if you are running, for example, a static website, it will be easier to just use Route53 + S3 buckets, GitHub Pages, or Vercel. Think of building a portfolio application, this will most likely have low-traffic, and will not require high availability, so a simpler model will help you save costs

Kubernetes shines when your organization needs scalability, resilience, and flexibility, so if you are a small shop, it can become an unnecessary burden.

On the other hand, using K8s in personal projects can help you get better with it, and be prepared for real-world challenges.

How does Lens Kubernetes IDE help you with Kubernetes?

Lens Kubernetes IDE provides a graphical interface that helps you visualize and manage all of your cluster resources without needing to memorize every kubectl command. You can view all your namespaces, pods, services, and deployment in real time, along with their logs, events, and resource usage.

This is extremely useful, especially if you are managing multiple clusters, as it gives you an easy way to juggle through them, and see at a glance, if you have any issues related to your resources. Lens also offers powerful features such as an integrated terminal access, ability to attach to your pods, connect to their shells and view their logs. It transforms abstract concepts into something tangible, as you can see, at a glance, pods getting created, scaled up, or even restarted when failures occur.

By leveraging the one-click AWS EKS integration, you can easily connect to all of your EKS clusters, based on the permissions you have. You can also take advantage of built-in AI capabilities using Lens Prism. With Lens Prism you get a context-aware AI assistant that enables you to solve issues faster, understand their root cause, and even help you learn Kubernetes faster.

If you want to see what you can do with Lens Kubernetes IDE in detail, check this article.

Key points

In this article we’ve explored Kubernetes’ top use cases and how it can help your organization achieve scalability, resilience, and flexibility. From managing microservices, AI workloads, edge computing, to even helping you get into tech, Kubernetes provides the infrastructure needed to support diverse and demanding use cases.

It is a not one-size-fits-all solution, as for small projects, its complexity may outweigh its benefits, and in such cases lightweight alternatives or simpler architectures may be more effective.

Kubernetes shines when you need to implement scalability, reliability, and innovation. With the right tools, such as Lens Kubernetes IDE, Kubernetes can empower both individuals and enterprises to unlock the full potential of clout native development.

If you want to see Lens Kubernetes IDE in action, download it today.