What Is Kubernetes? The Ultimate Guide to Scalable App Management

I’ve always wanted to build a sprawling mushroom farm and set up a stellar eCommerce platform for it. Let’s say you have a dream to build your own eCommerce platform.

In this case, I recommend breaking your codebase into microservices (such as user authentication, product catalog, and payment processing) for enhanced scalability, flexibility, and maintainability (a single, unified codebase can be a pain).

You can package these microservices into lightweight environments like containers and automate their deployment, scaling, and management through Kubernetes.

Kubernetes is an open-source platform that helps you manage containerized workloads.

You may be thinking, isn’t using a hypervisor a better option? If you deploy the online shop using virtual machines (VMs) managed by a hypervisor, scaling may require more manual intervention, and there is more overhead involved since each VM runs its own operating system (OS).

Bear in mind that VMs are better suited for certain application types, like those in financial or healthcare systems, where complete isolation is necessary. Due to its orchestration capabilities, Kubernetes is a solid option for applications that require dynamic scaling, continuous deployment, and, importantly, resource efficiency.

Put on your daydreaming cap once again. A few months have passed by, and your sales are through the roof.

If you take my advice and use Kubernetes to manage your containerized microservices, it can automatically spin up additional containers when traffic spikes during peak hours. When traffic decreases, it can scale down to save resources.

I can only imagine the searing headaches you’d have if you opted for manual container management or, God forbid, virtual machines! If you aren’t acquainted with the basics of virtualization through containers, read on.

Once you’re done, you might have to reread from the top to put two and two together. After all, revision is a key component of learning.

What are Containers?

When you book a room at a lavish hotel, you might find a welcome basket on the coffee table or at the foot of the bed. These baskets typically include items of convenience (and luxury), such as snacks, beverages, personal care items, and fresh fruit.

You can compare a container to these baskets — they’re lightweight, portable units that conveniently include everything you need to run a software application, including the code, runtime, libraries, and system tools.

Here’s the moment you’ve been waiting for: a comparison table highlighting the key differences between containers and virtual machines. Well, your wish is my command:

In a nutshell, containers are favored for modern application development, while VMs are suitable for traditional applications needing full OS environments.

The Challenge of Managing Containers

While you can manually manage a handful of containers with ease, orchestrating hundreds or thousands of containers across multiple environments can become inefficient and error-prone.

You need automation through Kubernetes (Amazon Elastic Container Service (ECS) is a fascinating alternative — more on that soon) to scale containerized applications. And this isn’t up for debate.

Why Kubernetes?

Kubernetes automates container orchestration, making it easier for you to manage, deploy, and scale complex, distributed applications. This doesn’t mean you can sit back and put your feet on the desk (don’t do it; it’s bad manners).

Initially, you’ll need to set up the Kubernetes cluster (more on that in the next section), specify resource requests and limits, set up monitoring and logging tools, and handle upgrades and maintenance.

Here are some of the things you won’t have to worry about:

• Reliability: Ensures high availability through self-healing capabilities. This means if a container fails, it’ll distribute traffic across healthy instances.
• Scalability: I already highlighted this. Let’s just say it ensures efficient resource utilization and cost management.
• Efficiency: Runs multiple containers on the same host operating system while maintaining isolation.

In summary, Kubernetes is an ideal choice for modern, agile app development practices.

A typical Kubernetes cluster consists of a control plane, master node, worker nodes, and pods. Some sources might use “control plane” and “master node” interchangeably, but they’re actually a bit different — trust me!

Let’s take a look at these core components before we move on to the key concepts of Kubernetes.

Nodes

You can think of the control plane as the brain of Kubernetes. It includes components such as the API server, scheduler, control manager, and managing all aspects of the cluster (like the cluster’s state, workload scheduling, and application scaling).

This brings me swiftly to the master node — the physical machine (like a computer system with sufficient resources or a server) or virtual machine that hosts the Kubernetes control plane components.

Clearly, these are distinct concepts.

Last but not least, the worker nodes (AKA nodes) actually do all the work (they run your applications). While you can run the master node and worker nodes on the same physical or virtual machine in a single-node Kubernetes cluster, this isn’t recommended, as it could lead to resource contention and a lack of high availability.

I recommend running them on separate servers or VM instances. It turns out containers and VMs can coexist!

Pods

You may think containers are the smallest deployable units in a Kubernetes cluster. While they’re definitely the smallest units, pods are actually the smallest deployable units and contain one or more containers.

When worker nodes receive instructions from the control plane, they run pods accordingly. Mind you, containers are the actual units of execution, while pods group containers that need to work closely together (like a database and backup service).

Services

Your end users want a seamless experience — they want to use your product without worrying about the underlying infrastructure. In Kubernetes, pods can be created, destroyed, and moved around frequently, which means their IP addresses can change.

If a pod fails and is replaced, for example, its new IP address would be different, and your end users would lose access to the app until they obtain the new IP.

Since your end users aren’t trained to handle network configurations, they’re unlikely to return if they face such issues. That’s where Kubernetes services come in.

A Kubernetes service provides a stable IP address and DNS-based service discovery for microservices running across multiple pods (replicas).

If one pod is busy handling requests or is experiencing issues, the service automatically redirects traffic to other healthy pods, ensuring continuous access for your users. When you create a service, you simply define which pods the service should route traffic to using labels.

Deployments and ReplicaSets

Wait a minute! Before you can create a service for a microservice (sounds confusing, right?), you first need to create a deployment.

As the name suggests, a deployment specifies the number of pods (replicas) you want for your microservices. It manages the lifecycle of these pods, ensuring the desired number of replicas is always running.

The deployment works closely with the ReplicaSet, which is responsible for automatically replacing any failed pods by creating new ones.

Namespaces

Namespaces are like country borders — they’re virtual partitions within a Kubernetes cluster. They help isolate resources and workloads and are particularly useful in environments where different teams or projects require isolation.

For example, you can have namespaces for development, testing, and production, each with its own resources, such as pods, services, and deployments.

ConfigMaps and Secrets

Everyone has secrets. In the case of applications, configuration data should be kept secure. Luckily for you, Kubernetes offers resources like ConfigMaps and Secrets to safeguard this data.

ConfigMaps are used to store less secretive information, like key-value pairs (do labels ring a bell?). Secrets, on the other hand, are specifically designed to securely store sensitive information such as passwords, API keys, and TLS certificates.

In the previous section, I mentioned the components of Kubernetes’s control plane. Now, I’ll break everything down and explain how the components work together, much like a well-run office.

Control Plane Components

To harness the full potential of Kubernetes, you need to understand how the control plane components work together to orchestrate the deployment, scaling, and operation of your applications.

You can also think of the control plane components as the office workers of Kubernetes, as they keep everything running smoothly.

• kube-apiserver: It’s at the forefront, acting as the main gateway for communication with the cluster, kind of like a receptionist. You can use kubectl, the command line tool for Kubernetes, to interact with the kube-apiserver and manage your cluster.
• etcd: While the kube-apiserver is at the forefront, etcd works behind the scenes as a reliable database, storing the cluster’s state and configuration data. This component is most similar to warehouse workers.
• kube-scheduler: Much like an HR manager, the kube-scheduler assesses available resources and scheduling policies to decide where to place a pod.
• kube-controller-manager: Lastly, the kube-controller-manager acts like a supervisor, ensuring that if a pod (employee) goes down, another one is quickly spun up to take its place.

Unlike employees, pods don’t bring unique skills and perspectives to their roles, so don’t let anyone call you a pod or say you’re dispensable! You’re amazing just the way you are.

Worker Node Components

I’m going to stitch together some of the information I’ve already shared with you so that you can better understand how worker nodes are assigned tasks.

Let’s start with something new: you can use the command “kubectl create deployment” to create a new deployment. Once you run this command, the request is processed by the kube-apiserver, which then hands over the baton to the ReplicaSet.

If there was any confusion earlier, let’s set things straight — the ReplicaSet handles the creation of pods based on the specifications you provided in the deployment. The kube-scheduler then assigns these pods to worker nodes.

Node components:

• kubelet: Kubelet is such a cute name! Every worker node can handle up to 110 pods by default, which means they have their work cut out. The kubelet, in particular, is a busy bee — it’s responsible for ensuring each container inside your pods is up and running.
• Container runtime: This is the software that actually runs your containers, with popular choices being Docker, containerd, and CRI-O. Mind you, Docker isn’t a Kubernetes alternative. Kubernetes is a container orchestration platform, while Docker provides the tools to create and manage containers. They complement each other like wine and soft cheese!
• kube-proxy: A good traffic cop can make a world of difference on a busy road. This is where kube-proxy comes into the picture. It manages network rules on each node, enabling communication between services and pods.

Note: In large clusters designed for high scalability, some worker nodes can support up to 1,000 pods. Running too many pods on a node can lead to performance issues, so be sure to find the optimal number of pods for your specific workloads.

How Scheduling Works

The kube-scheduler has an instrumental role to play in the grand scheme of things, as it schedules pods to the best available nodes by taking into account your resource requests.

Its job is to ensure all the pieces of the puzzle fit and resource utilization is optimal.

If a pod fails, the kube-controller-manager steps in to either restart it (sometimes restarting things, like your smartphone, can fix the problem) or create a new instance of it (with the help of the ReplicaSet).

If you prefer Android smartphones, I’m sure you compare the key features of dozens of models across brands before selecting one to purchase. Before I switched to iOS, I tried around seven different Android smartphone brands!

The truth is, we rarely buy any digital product without thoroughly weighing its pros and cons first.

If you’re on the hunt for a compelling “virtualization” solution (Kubernetes isn’t technically a virtualization platform), you’re in the right spot.

Here are the key features and benefits of Kubernetes:

• Scalability: One of the coolest things about Kubernetes is that it can scale your applications automatically based on metrics such as CPU utilization or custom-defined conditions. For example, if you create a deployment with three replicas and configure the Horizontal Pod Autoscaler (HPA) to scale up when CPU usage exceeds 70%, the HPA might decide to add more pod replicas to the deployment if there’s a sudden traffic spike.
• High Availability and Self-Healing: If a pod or node fails, Kubernetes automatically reschedules the workload on another available node to ensure continuity. Kubernetes is like Wolverine in this aspect (I know you’ve watched Deadpool and Wolverine).
• Rolling Updates and Rollbacks: If you need to update your application, Kubernetes can perform a rolling update without downtime.
• Resource Management: Rest assured, Kubernetes will efficiently allocate CPU, memory, and other resources across your nodes, ensuring optimal performance.
• Declarative Configuration and Automation: You can specify the desired state of your cluster and applications using configuration files in YAML or JSON format, and Kubernetes will automatically maintain that state, reducing manual intervention.

In many ways, once you configure Kubernetes, you can sit back and relax while Kubernetes takes care of much of the operational work for you.

If you haven’t realized it already, Kubernetes offers significant advantages over virtual machines, especially in cloud and hybrid environments.

For starters, Kubernetes runs containers, which are more lightweight than VMs. Additionally, Kubernetes is designed for dynamic scaling.

Features like rolling updates, self-healing, and rapid application deployment are the icing on the cake — but that’s not all. It’s time to add some sprinkles.

Kubernetes as a Multicloud Solution

Your imaginary online business is most certainly a popular eCommerce platform by now. Let’s say it’s deployed on Amazon Web Services (AWS). Over time, you may realize your costs are increasing, especially during peak shopping hours.

Thanks to Kubernetes, you can migrate those specific microservices to a more cost-effective cloud provider (this is by no means a dig at AWS) without significant rework, saving on cloud costs.

In other words, Kubernetes is vendor-neutral or cloud-agnostic.

Hybrid Cloud With Kubernetes

Kubernetes offers you the flexibility to run applications in hybrid environments, combining on-premise infrastructure with public cloud resources.

This means you can run certain workloads in an on-premises data center and others across multiple cloud vendors (if necessary).

For example, you can run user data and data processing microservices, which require strict compliance and security, in your on-premises data center and other microservices that require dynamic scaling in a cloud environment.

Managed Kubernetes Services

While Kubernetes automates the orchestration of your containers, you still need to set up and configure the cluster, monitor and troubleshoot, and apply regular upgrades and patches. And that’s just scratching the surface — managing your own Kubernetes clusters isn’t easy.

Managed Kubernetes services take care of these operational complexities, come with built-in security features, make scaling easier, and are deeply integrated with the cloud provider’s ecosystem.

Simply put, a managed Kubernetes service is a great option for your team, especially if you have heavy pockets.

Here’s an overview of popular managed Kubernetes services:

• Google Kubernetes Engine (GKE): Google Cloud birthed Kubernetes, so quite naturally, GKE is a fascinating option. It integrates perfectly with the Google Cloud Platform (GCP) and is the best managed Kubernetes service for advanced Kubernetes features and ease of use.
• Amazon Elastic Kubernetes Service (EKS): If you prefer the AWS suite, EKS may just be your new bestie. You’ll be happy to know it also offers strong security features.
• Azure Kubernetes Service (AKS): Now, if you’re looking for a cost-effective managed Kubernetes service, AKS is your guy. It offers simplified Kubernetes management and robust enterprise features.

In my opinion, you can’t go wrong with Google Kubernetes Engine. Amazon Elastic Kubernetes Service is an equally enterprising choice.

While managed Kubernetes services take a lot of the heavy lifting off your plate, according to me, managing your own Kubernetes cluster can be a rewarding experience, especially if you’re a control freak (again, no offense) and have a large, experienced team at your disposal.

Kubernetes’s suite of tools will help you get the most out of your Kubernetes environments, so read on!

Helm

Let’s just say Helm keeps you at the “helm” of things — it’s aptly named.

Instead of creating separate configuration files for each of your microservices (like for the frontend, backend, and database), you can create a single Helm chart for your application, bundling these microservices together.

With Helm, you can then deploy your app with a single command, easily change configurations, and roll back changes if necessary. In other words, Helm is the package manager you need.

Prometheus and Grafana

You need to keep a close eye on your Kubernetes cluster, and tools like Prometheus and Grafana are the closest things to private detectives you’ll get. The best part? These “detectives” come at no cost!

Prometheus acts like the field agent, collecting all relevant metrics, such as cluster health, resource usage, and application performance.

Grafana uses this information to create a “presentation,” but in the form of dashboards and visualizations, of course.

Kubectl

Kubectl’s command line syntax is your gateway to managing your Kubernetes cluster — simple as that. I can’t list every kubectl command (you’d be here for ages), but here are some of the most essential ones:

• “kubectl get nodes”: List all nodes.
• “kubectl drain –ignore-daemonsets –delete-local-data”: Drain a node.
• “kubectl get pods”: List all pods.
• “kubectl delete pod ”: Delete a pod.
• “kubectl scale deployment –replicas=”: Scale a deployment.
• “kubectl get services”: List all services.
• “kubectl delete service ”: Delete a service.
• “kubectl cluster-info”: View the cluster status.

I trust you to fill in the blanks where necessary!

Service Mesh (Istio, Linkerd)

Kube-proxy isn’t the only answer to network traffic management. Service mesh tools like Istio and Linkerd are designed to work at a higher level and are ideal for complex microservice environments.

They offer advanced features like observability, security, and traffic management for your microservices. If kube-proxy is like a traffic cop, then service mesh tools are like a high-tech traffic management system.

When it comes to managing complex applications, Kubernetes is like a Swiss Army knife — it’s multifaceted and bound to make your life easier.

From running your microservices to automating your CI/CD pipelines and tackling big data and machine learning (ML) workloads, Kubernetes makes the “cut.” Let’s start with its most obvious use case — simplifying the management of your microservices.

If you’re a beginner, you may find it difficult to set up and maintain a Kubernetes cluster. And that’s not the only challenge you might face. Resource management can prove tricky, and security is another critical area that could overwhelm you.

Of course, if you have the backing of a team — no matter their level of experience — you could learn on the go and make things work. I’m not here to discourage you but rather to empower you.

• Complexity: Kubernetes has a steep learning curve and requires expertise to set up and manage effectively, especially in production environments. If you don’t have a team available and need to run containerized applications at scale, I recommend purchasing a managed Kubernetes solution.
• Resource Overhead: While Kubernetes is a magnificent tool for managing large-scale containerized applications, it consumes significant resources (just think of all its working components). This overhead makes it inefficient for smaller workloads, where a simpler orchestration tool might be better suited. Alternatively, you could just run containers directly on a host.
• Security Management: Oh boy, where do I start? Kubernetes requires careful configuration to ensure secure communication, authentication, and authorization. Much like in real life, managing secrets and compliance in a Kubernetes cluster, in particular, can be complex without proper tooling and policies. I mean, it’s very easy for sensitive information to slip through the cracks if your security posture has any gaps.

There’s no doubt Kubernetes affords immense power and flexibility, but you know the saying: “With great power comes great responsibility.” If you’re determined to use Kubernetes, roll up your sleeves and put in the hours to learn everything you should know — and more.

It’s clear Kubernetes can be a game changer for managing containerized apps at scale. Sure, it’s complex, and its learning curve can feel steep at times, but it’s worth the effort.

Just think about it this way: once you master Kubernetes, the investment will pay off in returns no financial institution could guarantee (unless it’s a scam, of course).

The fact is, the more you learn, the more power you will have in your hands. Kubernetes isn’t just a tool; It’s a key that opens up new possibilities in your application development journey.

And I know it sounds like I’m trying extra hard to sell Kubernetes, but you already know what the truth is. Kubernetes is an offer that’s too good to refuse.