Nov 16, 2023
Kubernetes Tutorial for 2023: Learning the Basics of Effective Container Management
Kubernetes, often abbreviated as K8s, is a great choice for container orchestration due to its scalability, flexibility, and robust features. Whether you’re a developer or a system administrator, mastering Kubernetes can simplify how you deploy, scale, and manage containerized applications.
In this article, we’ll guide you through Kubernetes, explaining its basic concepts, key features, as well as pros and cons. You’ll also discover how to set up a Kubernetes environment, deploy your first application, and troubleshoot common issues.
After reading this Kubernetes tutorial for beginners, you’ll know how to fully leverage the platform for efficient container management.
What Is Kubernetes?
Kubernetes is a powerful open-source container orchestration platform. Meanwhile, a Kubernetes environment simplifies the management of containerized applications. Simply put, the platform provides an efficient framework to deploy, scale, and manage applications, ensuring they run seamlessly across a cluster of machines.
The Kubernetes architecture offers a consistent interface for both developers and operators. This enables teams to focus on application development rather than getting bogged down by the underlying infrastructure complexities.
As a leading container orchestrator, this IT tool ensures that containerized applications run reliably, effectively managing the deployment and scaling requirements while abstracting the underlying hardware and network configurations.
How Kubernetes Work?
The platform operates through its control plane and core components, each with a specialized role to manage containerized applications across Kubernetes clusters.
Let’s go over these essential Kubernetes objects in more detail:
Nodes are individual machines forming the backbone of a Kubernetes cluster. These can be the master node or worker nodes that play a critical role in running multiple containers. In addition, nodes can work on physical or virtual private servers.
Pods are the smallest deployable units in this platform and act as the basic building blocks of Kubernetes applications. A pod can contain one or more containers, and Kubernetes ensures they’re scheduled together on the same node for optimal communication and load balancing.
Services enable the applications to be accessible online and handle load balancing. They provide a consistent way to access containerized services while abstracting the complexities of network connectivity.
The API server acts as the front end for the Kubernetes control plane, handling internal and external requests to manage various aspects of the cluster.
Beyond these core components, Kubernetes architecture introduces more advanced concepts to enhance its capabilities further, including:
Replication sets maintain a specified number of identical pods to guarantee high availability and reliability. If a pod fails, the replication set automatically replaces it.
An ingress controller acts as a gatekeeper for incoming traffic to your Kubernetes cluster. Ingress controllers manage access to services within the cluster, offering control over routing and simplifying external access.
Together, these components enable Kubernetes to efficiently manage the complexities of containerized workloads within distributed systems.
Key Features of Kubernetes
Kubernetes offers a robust set of features tailored to meet the specific needs of modern containerized applications. These features simplify deployment while enhancing both application efficiency and resilience.
Kubernetes provides seamless scaling possibilities for your application. It dynamically adjusts to demand, ensuring that your resources are optimally utilized. This adaptability helps you cut costs while maintaining a smooth user experience.
Load balancing is a core feature in the Kubernetes architecture, effectively distributing incoming traffic across multiple pods. This ensures high availability and optimal application performance, preventing overload on any specific pod.
Kubernetes’ self-healing capability minimizes downtime. If a container or pod fails, it’s automatically replaced, keeping your application running smoothly and maintaining consistent service delivery.
Service Discovery and Metadata
Service discovery is effortless in a Kubernetes environment, as it streamlines communication between different application components. Service metadata can be used to fine-tune these interactions, simplifying complexities in distributed systems.
Rolling Updates and Rollbacks
Kubernetes supports rolling updates, allowing for continuous service availability. Should an issue arise during an update, coming back to a stable version is quick and straightforward.
Kubernetes helps with precise resource management by allowing you to define resource limits and requests for pods. This ensures efficient use of CPU and memory.
ConfigMaps, Secrets, and Environment Variables
Kubernetes offers ConfigMaps and secrets to handle secure configuration management, including using environment variables. Store and securely manage sensitive data like API keys and passwords, protecting them from unauthorized access.
Replication Controllers and Ingress Controllers
For advanced control, Kubernetes introduces features like replication and ingress controllers. While replication controllers maintain the desired number of pods, ingress controllers manage external access to services within your Kubernetes cluster.
Kubernetes Pros and Cons
Weighing Kubernetes’ strengths and weaknesses is crucial to deciding whether it is the right platform for your container management needs.
Advantages of Kubernetes
Kubernetes brings various benefits, making it an attractive option for managing running containers. Here’s how it stands out:
Kubernetes eases the deployment of containers, ensuring your applications can expand or contract based on real-time demand. Here’s how it excels:
- Effortless scaling – Kubernetes can automatically deploy additional containers when demand increases without manual intervention.
- Zero downtime – as you deploy containers, Kubernetes employs a load balancer to distribute traffic across existing and new containers, ensuring continuous service.
A deployment object in Kubernetes contributes to high availability, a critical advantage for any organization. Here’s how Kubernetes achieves this:
- Automatic failover – if a container or node fails, Kubernetes redirects traffic to functional containers or nodes, reducing downtime.
- Load balancing – with its built-in load balancer, Kubernetes evenly spreads incoming traffic across multiple pods, enhancing performance and increasing availability.
Flexibility and Extensibility
Kubernetes excels in flexibility, enabling you to choose package software and custom-tailor solutions to your requirements.
Here are its main advantages:
- Custom resources and operators – Kubernetes helps you create custom resources and operators, extending its functionality to meet your business needs.
- Best of breed ideas – the open-source nature and community support create a rich ecosystem of extensions and tools. As a result, you can improve your Kubernetes environment with a wide array of add-ons for everything from monitoring to external access.
Disadvantages of Kubernetes
While Kubernetes is a robust platform, it has certain drawbacks you should consider. Let’s delve into them:
The steep learning curve in Kubernetes can be a hurdle, especially for new users. Expertise in managing Kubernetes clusters is essential to unlock its full potential.
Kubernetes requires a significant investment in server resources like CPU, memory, and storage. This might introduce more overhead than benefit for smaller applications, particularly if you are running lean-on resources.
Lack of Native Storage Solutions
Kubernetes does not offer built-in storage solutions, which can pose challenges, especially for applications that require persistent or sensitive data storage. To overcome this limitation, you must incorporate external storage options like network-attached storage (NAS), storage area networks (SAN), or cloud services.
How to Set up Kubernetes
Setting up Kubernetes is crucial for efficient container management. Your hosting environment plays a key role in this. Hostinger’s VPS hosting is geared toward the resources and stability required to run a Kubernetes cluster.
1. Choose a Deployment Method
Selecting the right Kubernetes deployments is one of the first decisions to make. Each option has its own use cases, for example, a single container is better for small projects, and multiple containers are more suitable for interfacing with the external world.
Deploying Kubernetes in a local machine is ideal for learning, testing, and development. Tools like Minikube and Kind (Kubernetes in Docker) simplify the setup and provide a local cluster for experimentation. As a result, using a local environment for Kubernetes is quick and convenient for individuals and small teams. However, it needs more resources than other methods.
Self-hosted deployments involve setting up and managing your Kubernetes cluster from scratch. While this provides more control and flexibility, it requires significant time and expertise.
For this reason, self-hosting suits larger organizations with complex infrastructure needs or specific compliance requirements.
Managed Kubernetes Services
For most production workloads and larger-scale projects, a managed Kubernetes service, such as Amazon EKS, Google Kubernetes Engine (GKE), or Azure Kubernetes Service (AKS), is a compelling choice. Managed services are highly recommended for their ease of use and robustness.
If you’re starting and want a hassle-free experience for learning and development, opt for a local environment. Self-hosted Kubernetes provides complete control but demands substantial time and expertise. Managed services best fit most production scenarios, offering scalability and reliability without the administrative overhead.
2. Install Kubernetes
This Kubernetes tutorial will guide you through setting up a Kubernetes environment on Hostinger using an Ubuntu 22.04 64-bit operating system. Follow these detailed steps:
- Log in to your VPS via SSH using a terminal client like PuTTY. Ensure your VPS is up to date with the following commands:
sudo apt-get update && sudo apt-get upgrade
- Kubernetes relies on a container runtime, such as Docker. Install Docker on your VPS with this command:
sudo apt install docker.io
- Activate and start Docker as a system service:
sudo systemctl enable docker sudo systemctl start docker
- Install the software properties to manage the repositories you’re installing from.
sudo apt-get install -y apt-transport-https
- Add Kubernetes’ official GPG key and repository with these Linux commands:
sudo curl -fsSLo /usr/share/keyrings/kubernetes-archive-keyring.gpg https://packages.cloud.google.com/apt/doc/apt-key.gpg echo "deb [signed-by=/usr/share/keyrings/kubernetes-archive-keyring.gpg] https://apt.kubernetes.io/ kubernetes-xenial main" | sudo tee /etc/apt/sources.list.d/kubernetes.list > /dev/null
- Now, you can install Kubernetes. Update the package list and install the Kubernetes packages.
sudo apt-get update sudo apt-get install -y kubelet kubeadm kubectl
- Kubernetes requires swap to be disabled. You can deactivate it using the following command:
sudo swapoff -a
- Finally, initialize the master node with the command below. Replace your-master-ip with the IP of your master node.
sudo kubeadm init --apiserver-advertise-address=your-master-ip
Once the installation is complete, you’ll get an output with instructions on how to join worker nodes to your cluster. Save this output, as you’ll need it later.
3. Configure Kubernetes
After successfully installing Kubernetes, the next crucial step in this Kubernetes tutorial is configuring your cluster. This involves setting up the nodes and pod metadata as well as implementing security measures to protect your cluster. Let’s dive in:
- Once your master node is up, join the worker nodes with the master using the command provided at the end of the Kubernetes installation:
sudo kubeadm join [your-master-ip]:[your-port] --token [your-token] --discovery-token-ca-cert-hash [your-hash]
- To set up the pod network, you can install a network plugin like Calico using the following command:
kubectl apply -f https://docs.projectcalico.org/manifests/calico.yaml
- To ensure everything is functioning correctly, run:
kubectl get nodes
Your Kubernetes cluster should now be operational on your VPS.
As for security, we recommend applying the following measures:
- Limit API access only to trusted IPs.
- Enable Role-Based Access Control (RBAC) to restrict permissions based on roles within your cluster.
- Regularly update all components of your Kubernetes cluster to avoid potential security vulnerabilities.
Here at Hostinger, we offer specialized features to further secure your VPS. These include a cloud-based firewall solution, safeguarding your virtual server from potential internet threats.
Additionally, our robust malware scanner, integrated with Monarx, enables proactive monitoring and security for your VPS by detecting, managing, and cleaning compromised and malicious files.
You can activate both features by accessing the VPS section on hPanel.
4. Set Up User Access and Navigate the Dashboard
Once your cluster is up and running, the next step is to manage user access and permissions based on roles or IP addresses. This ensures that only authorized individuals can make changes to your Kubernetes environment.
- For this tutorial, we will create a service account with the name john using the command below. Feel free to use another name.
kubectl create serviceaccount john
- Set up a role binding for john. Open the Nano editor to create the YAML file:
- Insert the following content, which sets john as a cluster admin, a predefined role in Kubernetes:
apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: john-cluster-admin-binding subjects: - kind: User name: john roleRef: kind: ClusterRole name: cluster-admin apiGroup: rbac.authorization.k8s.io
- Save and exit the editor.
- To set up Role-Based Access Control (RBAC) for john, run the following command:
kubectl apply -f john-role.yaml
- You can confirm the roles and permissions are applied correctly by running:
kubectl get roles kubectl get rolebindings
- For a more visual approach to managing your cluster, install the Kubernetes dashboard by using this command:
kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.0.0-beta8/aio/deploy/recommended.yaml
- Start the network proxy to access the dashboard:
- Open your browser and navigate to http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/ to access the dashboard.
Once you’ve successfully accessed the dashboard, you can use it to manage and monitor your Kubernetes cluster. This dashboard provides a graphical interface for various Kubernetes tasks, including resource management, log inspection, and cluster health checks.
How to Deploy Applications on Kubernetes
Deploying applications on a Kubernetes cluster is a critical step to harness the full potential of container orchestration.
Let’s proceed with getting your application up and running in this Kubernetes tutorial.
1. Prepare Your Application
Before deploying any application on Kubernetes, understanding the basics of containerization is crucial. You’ll need to package your application and its dependencies into a single container using Docker or any container engine.
This single-binary approach ensures that your application behaves consistently, whether it’s on a single node or multiple nodes, eliminating environment-specific issues. To create a Docker container, follow these steps:
- Create a file that contains commands for building a Docker image. This Dockerfile should specify the base image and outline the steps to package your application into one container.
# Use an existing Docker image as a base FROM node:14 # Set the working kube directory in the container WORKDIR /app # Copy the application code into the container COPY . /app # Install any needed packages RUN npm install # Specify the command to run on container start CMD ["npm", "start"]
- After creating the Dockerfile, navigate to the directory containing it. Run the following command to build the Docker image, replacing your-application-name with your actual application name:
docker build -t your-application-name .
2. Deploy the First Application
After containerizing your application, it’s time to deploy it onto your Kubernetes cluster. To accomplish this, you will need to create a Kubernetes deployment.
This tells the platform how to create and update instances of your containerized application organized into Kubernetes Pods. Here are the complete steps:
- Create the deployment in a file named your-app-deployment.yaml. This YAML file will specify that Kubernetes should run your Docker container image and expose a certain port. Replace your-application-name and your-docker-image accordingly.
apiVersion: apps/v1 kind: Deployment metadata: name: your-application-name spec: replicas: 2 selector: matchLabels: app: your-application-name template: metadata: labels: app: your-application-name spec: containers: - name: your-application-name image: your-docker-image ports: - containerPort: 80
- To apply this deployment, run the following command:
kubectl apply -f your-app-deployment.yaml
- Next, create another declarative YAML file named your-app-service.yaml. This will expose your deployment as a service, making your container accessible over the network.
apiVersion: v1 kind: Service metadata: name: your-application-name spec: type: LoadBalancer ports: - port: 80 selector: app: your-application-name
- To make your application accessible, execute this command:
kubectl apply -f your-app-service.yaml
- To ensure your Deployment is up and running, check with:
kubectl get deployments
- To find the exposed IP and port, run the following:
kubectl get services
3. Scale Your Application
Scaling in Kubernetes is straightforward, thanks to its robust built-in features like replica sets, which serve as logical units for scaling. These ensure that a predetermined number of identical pods are running, making it easier to adapt to varying workloads and user demands.
Here’s how to scale your containerized application using replication sets:
- To understand your current setup, execute the following command:
kubectl get deployments
- To increase the number of replicas, use the following command. Remember to replace your-deployment-name and number-of-replicas with your specific details:
kubectl scale deployments/your-deployment-name --replicas=number-of-replicas
- To confirm that the scaling operation was successful, revisit your deployments with the following command:
kubectl get deployments
Feel free to experiment with different numbers of replicas based on your application’s needs. Keep an eye on performance metrics and make adjustments as you go along.
4. Monitor and Manage Applications
Monitoring and managing your applications is vital when working with Kubernetes objects. Utilizing tools like Prometheus for collecting metrics and Grafana for data visualization can be game-changing. Here’s a rundown of how to monitor your application’s performance.
- Install Prometheus using Helm by executing this command:
helm install prometheus stable/prometheus
- Once Prometheus is up and running, proceed to install Grafana for a detailed look at your metrics:
helm install grafana stable/grafana
- With both tools in place, configure Grafana to pull metrics from Prometheus. Edit the ConfigMap with:
kubectl edit configmap grafana-datasources -n monitoring
Follow these steps to start monitoring:
- To initiate basic monitoring, use metric exporters. Apply your configuration with this command:
kubectl apply -f exporter-config.yaml
- Navigate to your Grafana dashboard to review various metrics for your containerized application.
Additionally, regularly updating your applications ensures optimal performance.
- To update your application without downtime, use the rolling update feature:
kubectl rolling-update your-old-controller your-new-controller
- If an update doesn’t go as planned, Kubernetes helps you roll back to a previous version. This is especially useful when working with new pods and containers.
kubectl rollout undo deployments/your-deployment-name
Kubernetes also lets you see the list of running pods, making it easier to manage new and existing containers. Feel free to use the command kubectl get pods to list pods as part of your monitoring routine.
Kubernetes Best Practices
Kubernetes is an open-source tool that offers plenty of advantages. To fully leverage its capabilities, it’s crucial to adhere to the best practices developed within the Kubernetes community.
Optimize Resource Management
Resource management is paramount in Kubernetes for the performance and stability of your applications. By defining resource limits and requests for different objects like pods, you create a stable environment to manage containerized applications.
Resource limits cap the CPU and memory usage to prevent resource hogging, while resource requests ensure that your containers have the minimum resources needed. Finding the balance between these two is key for optimal performance without resource waste.
Ensure Health Checks and Self-Healing
One of the core principles of Kubernetes is maintaining the desired state of your applications.
Health checks via readiness and liveness probes are indispensable for this. Readiness probes help manage incoming traffic by assessing if a container is ready for it, while liveness probes keep tabs on the container’s ongoing health.
Failed liveness probes trigger Kubernetes to replace the problematic container, maintaining the desired state of the containerized application without manual intervention.
Secure Configurations and Secrets
Security can’t be compromised, especially when dealing with sensitive data and configuration settings. Kubernetes provides robust solutions like ConfigMaps and secrets.
ConfigMaps store configuration data and secrets securely contain sensitive information like API keys and passwords. Implementing these encrypts your sensitive data and makes it accessible only to authorized users.
Execute Rolling Updates and Rollbacks
The dynamic nature of modern applications requires an efficient strategy for updates and rollbacks. Kubernetes excels in this with its rolling update strategy. Old containers are gradually phased out as new versions are introduced, ensuring a seamless transition and zero-downtime deployments.
This maintains uninterrupted service, ensuring a superior user experience even when significant changes occur in your containerized applications.
Troubleshooting Common Kubernetes Issues
In this section, we will navigate some common issues you might encounter with Kubernetes and show you how to diagnose and resolve them effectively.
These failures occur when pods cannot run as expected, causing their containers to fail in performing their intended tasks. These failures can disrupt the availability and performance of your applications.
Common reasons behind pod failures include:
- Resource constraints – pods may fail when they require more CPU, memory, or other resources than are available on the node. This can lead to resource exhaustion and cause the pod to terminate.
- Misconfigurations – incorrect configurations, such as specifying a wrong image name or mounting incorrect volumes.
- Image issues – problems with container images, such as missing dependencies or image pull failures, can lead to pod failures.
When a pod fails, follow these steps to identify and address the issue:
- Use the kubectl describe pod command to see detailed information about the pod, including events, logs, and configuration details. Look for error messages and events that can point you toward the cause of the failure.
- Review the pod’s resource requests and limits in its configuration. Ensure the pod’s resource requirements align with the node’s available resources.
- Use kubectl logs to inspect the logs of the pod’s containers. Container logs often contain valuable information about what went wrong.
- Check the pod’s image references, environment variables, volume mounts, and other configurations to ensure they are correct.
- Address any network-related problems, such as DNS configuration or connectivity issues, that may be causing the pod to fail.
- If the node is experiencing problems, address those issues or allow Kubernetes to automatically reschedule the pod to a healthy node.
Networking problems in a Kubernetes cluster can disrupt the communication between pods and services, impacting the functionality of your applications. Here are some network-related issues you might encounter:
- Service connectivity – when services can’t communicate with each other, applications may fail. Connectivity issues can stem from misconfigured service definitions, network policies, or underlying network problems.
- DNS resolution – DNS issues can cause problems with service discovery and communication. As pod-to-pod communication relies on DNS, improper DNS configuration can lead to failures.
- Network partitioning – in distributed systems, network partitioning occurs when network links are disrupted or nodes become isolated. This can lead to data inconsistency and service disruptions.
Here are the key steps to address networking issues in Kubernetes:
- Check your service definitions for correctness. Ensure that the service names and ports are accurate. The kubectl get services command can help you inspect service details.
- Review your network policies, which control the traffic flow between pods. Ensure that policies are appropriately configured to allow or deny the desired traffic.
- Confirm that DNS settings are correct within Kubernetes and at the cluster level. Kubernetes should automatically manage DNS configurations, but misconfigurations can occur.
- Tools like nslookup or dig can help diagnose DNS issues. Use them to test DNS resolution within your cluster.
- If you’re using a network plugin like Calico or Flannel, review their configurations and logs for potential network problems.
- Leverage kube-proxy to manage network communication between services and pods.
To enhance security in your Kubernetes cluster, consider implementing network policies. Network policies define how pods can communicate with each other and other resources. They help restrict traffic and protect your cluster from unauthorized access or unwanted network connections.
Persistent Storage Challenges
In Kubernetes, managing persistent storage is critical to running stateful applications. However, failure to manage storage effectively can lead to data loss, application disruptions, and degraded performance.
Common issues related to persistent storage include:
- Resource allocation – underestimating storage needs can lead to data loss, while overprovisioning can result in unnecessary costs.
- Persistent volume (PV) and storage class mismatches – misconfiguration between PVs and storage classes can lead to compatibility issues, making it difficult to attach the right storage to your pods.
- Data loss – it can occur for various reasons, such as pod crashes, deletions, or hardware failures.
When faced with persistent storage challenges in your Kubernetes environment, follow these steps to resolve them:
- Regularly assess your application’s storage requirements and adjust resource requests and limits. Use metrics and monitoring tools to identify under- or over-provisioned resources.
- Ensure that your PVs and storage classes match appropriately. Review your storage class configuration to guarantee it provides the desired characteristics, such as performance and access modes.
- Explore data recovery options like snapshots to recover lost or corrupted data. Backup solutions that integrate with your storage provider also help restore data.
- Automate the backup process to ensure regular and consistent data protection. Implement automated backup solutions or scripts that run at scheduled intervals.
- Choose a storage solution that can scale easily to accommodate growing storage needs. Implement storage systems that can dynamically expand as your containerized applications demand more storage.
Cluster Scaling and Performance
Scalability is a defining trait of Kubernetes, allowing applications to adapt to varying workloads. However, you may encounter scaling challenges and performance bottlenecks as your applications grow.
Common issues in this area include:
- Resource contention – competition for resources, such as CPU and memory, among different pods can lead to performance issues. Pods with resource constraints may not function optimally.
- Network congestion – increased traffic can saturate network bandwidth, leading to communication delays and performance degradation.
- Inefficient resource management – inefficient resource requests and limits can waste your resources.
To optimize cluster performance and address scaling challenges, consider the following strategies:
- Regularly review resource requests and limits for your pods. Adjust these values based on application requirements and resource availability.
- Implement Horizontal Pod Autoscaling (HPA) to enable dynamic scaling of pods based on resource utilization or custom metrics. This ensures that your applications can automatically handle traffic surges without manual intervention.
- Monitor network traffic and implement network policies to regulate traffic flow. Consider using a container network interface (CNI) and plugins to enhance network performance.
- Engage kube-controller-manager for automatic scaling of nodes based on resource demands.
- Review and optimize your containerized application code, ensuring efficient resource utilization. Consider using container orchestration best practices to improve performance.
- Periodically remove unused Docker images, containers, services, and volumes. You can use commands like docker system prune for Docker and kubectl delete for Kubernetes resources to clean up.
Kubernetes is a tool that helps manage and deploy applications, making them run smoothly on servers, both in local environments and in the cloud.
In this Kubernetes tutorial for beginners, we’ve covered the core components, key features, as well as pros and cons. We’ve shown you how to set up your Kubernetes environment and deploy applications.
With its dynamic scaling, self-healing abilities, and a wide range of extensions, Kubernetes is a powerful tool for managing containerized applications in a distributed setting.
By following the best practices, proactively tackling challenges, and encountering more advanced concepts like service discovery, you can unlock the full capabilities of this open-source system for your container management requirements.
Learn Other Deployment Tools
Kubernetes Tutorial FAQ
This section will answer the most common questions about Kubernetes.
What Is Kubernetes Used For?
Kubernetes is primarily used for container orchestration, automating containerized applications’ deployment, scaling, and management. It ensures efficient resource utilization, enhances scalability, and simplifies application lifecycle management in a cloud-native environment, making it an ideal choice for running modern, distributed applications.
Is Kubernetes the Same as Docker?
No, Kubernetes and Docker serve different purposes. Docker is a containerization platform that packages applications and their dependencies into containers. Meanwhile, Kubernetes is an orchestration platform that manages the deployment, scaling, and operation of those containers in a cluster. Kubernetes can orchestrate containers created using Docker and other container runtimes.
How Do I Start Learning Kubernetes?
To start learning Kubernetes, begin with its official tutorial and documentation. Next, install a Kubernetes cluster locally or on a cloud provider. Then, explore Kubernetes concepts such as pods, services, and deployments. Put your learning into practice by deploying and managing applications. Finally, join online forums and communities for support and guidance as you progress on your learning journey.
Is Kubernetes Suitable for Small Projects, or Is It Mainly for Large-Scale Applications?
Kubernetes is versatile and can be used for both small projects and large-scale applications. While it offers robust features for managing complex, large deployments, it can benefit small projects by providing containerization, scaling, and orchestration capabilities. However, the level of complexity in setup and maintenance may vary, so the choice depends on project requirements.