Deploying your first application to Kubernetes involves creating a deployment that runs your containerized application, then exposing it through a service so users can access it. You need a working Kubernetes cluster, the kubectl command-line tool, and a Docker image of your application. This guide answers the most common questions about getting your first application running on Kubernetes and troubleshooting issues that arise.
What do you need before deploying an application to Kubernetes?
You need four foundational components before deploying to Kubernetes: a working cluster (local or cloud-based), the kubectl command-line tool installed and configured, a containerized application packaged as a Docker image, and basic understanding of how containers work. These prerequisites ensure you can successfully create and manage your deployment.
Your Kubernetes cluster can run locally using tools like Minikube or kind for development purposes, or you can use a cloud-based cluster for production workloads. The cluster provides the infrastructure where your application runs, managing resources and orchestrating containers across multiple nodes.
The kubectl tool acts as your interface to the cluster. You'll use it to send commands, check application status, and troubleshoot problems. Installing kubectl involves downloading the binary for your operating system and configuring it to connect to your cluster using a configuration file (typically stored at ~/.kube/config).
Your application must be packaged as a Docker container image and stored in a container registry where Kubernetes can access it. This could be Docker Hub, a private registry, or a cloud provider's container registry. The image contains your application code, dependencies, and runtime environment bundled together.
Understanding containers helps you grasp how Kubernetes manages your application. Containers provide isolated environments for applications to run, and Kubernetes orchestrates these containers across your cluster, handling scaling, networking, and recovery automatically.
How do you create a Kubernetes deployment for your application?
You create a Kubernetes deployment using either kubectl commands directly or by applying a YAML configuration file that describes your desired application state. The deployment manages replicas of your application, ensuring the specified number of pods are always running and handling updates smoothly. YAML files provide a declarative approach that's easier to version control and reproduce.
The imperative approach uses commands like kubectl create deployment my-app --image=my-image:tag to quickly create a deployment. This method works well for testing and learning, but it doesn't provide a record of your configuration that you can store in version control or easily replicate.
The declarative approach uses a YAML file that specifies your deployment configuration. Here's what a basic deployment file includes:
- API version and kind: Defines the resource type (Deployment)
- Metadata: Names your deployment and adds labels for organization
- Spec section: Specifies replica count, pod template, and container details
- Container image: Points to your Docker image location
- Resource requirements: Defines CPU and memory limits
You apply a YAML file using kubectl apply -f deployment.yaml. This command creates the deployment if it doesn't exist or updates it if it does. Kubernetes then creates the specified number of pod replicas, each running your container image.
The deployment controller continuously monitors your pods. If a pod fails or gets deleted, the controller automatically creates a replacement to maintain your desired replica count. This self-healing behaviour makes your application more reliable without manual intervention.
You can modify your deployment after creation by editing the YAML file and reapplying it, or by using commands like kubectl scale deployment my-app --replicas=5 to change the number of running instances. This flexibility allows you to adjust resources as your application needs change.
How do you make your application accessible after deploying to Kubernetes?
You expose your application using a Kubernetes Service, which provides a stable network endpoint for accessing your pods. Services handle traffic routing to your application replicas and offer different exposure methods: ClusterIP for internal access only, NodePort for external access through node IP addresses, and LoadBalancer for cloud-based load balancing. The service type you choose depends on where your users are and your infrastructure setup.
ClusterIP creates an internal IP address accessible only within the cluster. This works for backend services that other applications in your cluster need to reach but external users don't. It's the default service type and provides basic service discovery between applications.
NodePort exposes your application on a specific port (30000-32767) on every cluster node. You can access your application using any node's IP address plus the assigned port. This approach works for development environments or small deployments where you can manage node IP addresses manually.
LoadBalancer provisions an external load balancer through your cloud provider. This gives you a single IP address or hostname that distributes traffic across your application pods. It's the most common choice for production applications that need to serve external users reliably.
Creating a service requires specifying which pods to target (using label selectors), which ports to expose, and the service type. You can create a service using kubectl expose deployment my-app --port=80 --type=LoadBalancer or by applying a service YAML file.
After creating the service, verify it's working by running kubectl get services to see the assigned IP address or hostname. For LoadBalancer services, it may take a few minutes for the cloud provider to provision the load balancer. You can then test access by sending requests to the service endpoint.
| Service Type | Access Method | Best For |
|---|---|---|
| ClusterIP | Internal cluster IP | Backend services, internal APIs |
| NodePort | Node IP + specific port | Development, testing environments |
| LoadBalancer | External IP/hostname | Production applications, public services |
What should you do if your Kubernetes deployment fails?
Start troubleshooting by checking pod status with kubectl get pods to identify which pods are failing. Common issues include image pull errors (wrong image name or authentication problems), resource constraints (insufficient CPU or memory), configuration mistakes (incorrect environment variables or volume mounts), and networking problems (service misconfiguration or port conflicts). The kubectl commands for describing resources and viewing logs help you identify problems quickly.
Use kubectl describe pod pod-name to see detailed information about a failing pod. The Events section at the bottom shows what happened during pod creation and startup. Image pull errors appear here with messages indicating whether the image wasn't found or authentication failed.
View application logs using kubectl logs pod-name to see what your application is reporting. If your application is crashing, logs often reveal the cause, such as missing configuration files, failed database connections, or uncaught exceptions. For pods with multiple containers, specify the container name with kubectl logs pod-name -c container-name.
Resource constraint problems show up when pods remain in Pending status. The describe command reveals if the scheduler can't find nodes with enough CPU or memory. You can either reduce your resource requests in the deployment configuration or add more capacity to your cluster.
Configuration mistakes often cause pods to start but immediately crash. Check that environment variables are set correctly, volume mounts point to valid locations, and any required secrets or config maps exist. Use kubectl get configmaps and kubectl get secrets to verify these resources exist.
Networking issues prevent services from reaching your pods. Verify that service selectors match pod labels using kubectl get pods --show-labels and comparing with your service configuration. Test connectivity from within the cluster using kubectl run -it --rm debug --image=busybox --restart=Never -- wget -O- http://service-name:port.
When you've identified and fixed the problem, apply your corrected configuration with kubectl apply -f deployment.yaml. Kubernetes will roll out the changes, creating new pods with the updated configuration whilst maintaining application availability.
Deploying your first application to Kubernetes becomes straightforward once you understand these fundamental concepts. Start with a simple application, verify each step works correctly, and gradually add complexity as you become comfortable with the deployment process. At Falconcloud, we provide managed Kubernetes environments that simplify cluster setup and maintenance, allowing you to focus on deploying and running your applications rather than managing infrastructure.