The open-source container orchestration system for automating software deployment, scaling, and management has earned a bad rep for being too complicated.
In this post, let’s explore whether that reputation is well deserved.
The Steep Learning Curve
Kubernetes brings with it an entirely new vocabulary engineers who deploy applications must learn. Terminology like Pods, Deployments, Services, and Ingress are just a starting point. Without a grounding in distributed systems or containerization, it’s easy to get lost in the myriad concepts and how they all fit together.
Kubernetes Backstage
It’s true, Kubernetes has several layers of complexity.
Kubernetes solves the problem of managing extremely large workloads well at almost any scale. For the newcomers, that’s enough to feel completely overwhelmed.
Where App Complexity Comes From
Real-world software infrastructure systems often feature many servers and many people who operate them. They must handle authentication and authorization (AuthN and AuthZ) for many web applications, background tasks, message queues, and message consumers, all running simultaneously.
Coordinating updates, rolling back changes, and automatically recovering from crashes may seem daunting. Would it be a good idea to handle all those tasks manually? That would be too risky, and Kubernetes was built to solve the problem of many modern applications with automation.
Why Operate at Scale
Let’s take a look at industries where uptime and operating at scale are critical: ecommerce. This is not the only industry where scaling counts, but it’s one everyone can relate to.
Downtime equals lost revenue for online storefronts. High availability becomes critical, but adding more servers also adds costs and complexity. When you add servers, you need load balancing and possibly redundancy for the load balancer itself. Then there’s the question of user session data: how do you keep it consistent?
A Workload Scaling Example
A monolithic application like Magento or WooCommerce by WordPress work well for many small businesses. Yet as soon as you need higher availability to handle sudden spikes in traffic, a single-node system quickly hits its limits.
Imagine you’re an engineer responsible for scaling an ecommerce platform without using Kubernetes.
Let’s assume you try to do what Kubernetes does for reliable scaling without using Kubernetes.
Here is a conceptual diagram of the components a software engineer would need to implement manually to set up a more robust system with automated scaling, container lifecycle management, and better system reliability.
Kubernetes excels at exactly these tasks. Orchestrating containerized microservices, helping spread out workloads, seamlessly handling larger volumes of traffic, and maintaining uptime are all standard issues for Kubernetes.
The complexity involved is entirely worth it but presents a steep learning curve for newbies.
Distributed Systems to the Rescue
Beneath all of its abstractions, Kubernetes orchestrates a truly distributed system that can be managed effectively.
That same application architecture using a Kubernetes cluster would look like this:
What’s not shown is how Kubernetes spins up containers on different hosts, keeps track of their health, and responds to events such as hardware failures or traffic surges.
Hands-On Kubernetes Practice
To master Kubernetes you must get some practice with it.
Explore Kubernetes locally using Minikube. Then, graduate to a managed cloud solution, where you’ll inevitably encounter more issues and misconfigurations. While these moments can be frustrating, each one deepens your knowledge of how Kubernetes operates and how to set it up effectively.
Ecosystem and Tooling
Kubernetes is not a standalone tool, but an active tooling ecosystem that further extends the significant benefits. Each solves real problems but adds more layers of complexity and requires time and effort to master.
Tools like Helm and Kustomize assist with configuration management. Istio introduces service mesh capabilities for traffic management and security.
Argo CD enables continuous delivery and is a fantastic product for learning Kubernetes, but not just because it automates deployment and changes. It’s a great visualization tool, and it excels at showing how components connect, and the relations between them, helping to learn Kubernetes faster.
Kubernetes Takeaways
Kubernetes is not an easy tool to master, but for now it’s the best solution for many of the modern application development challenges.
As someone whose path to becoming a Kubestranaut started many, many years ago when I launched my first cluster on bare-metal, I can attest that mastering topics like network topologies, load-balancing methods, scaling approaches, and service discovery often poses the biggest challenge for all learners.
Kubernetes streamlines the administration of multiple machines with specialized roles by abstracting them under one umbrella. Building and coordinating these nodes is intrinsically complex, so any platform that promises simplicity must absorb that inherent complexity.
Kubernetes is rooted in a philosophy of helping you manage containerized workloads across multiple nodes by abstracting the underlying infrastructure. This power and versatility do not come without complexity. By gaining a firm grasp of distributed systems, methodically learning each Kubernetes concept, and continuously practicing in real settings, you can conquer the learning curve and unlock a robust, scalable environment for modern application deployment.
About the Author
Andrew Korolov is a Senior Solutions Architect and serial founder-entrepreneur. A key developer behind the original Magento ecommerce platform, Andrew is the founder of Maven Solutions, an IT infrastructure service provider that helped startups like Skillsetz and BuyerQuest scale and succeed. Andrew is also a founder of Transformatic, a DevEx platform for launching tech products in a day instead of months. Andrew is a recognized software industry voice published in Inc., Forbes, and software engineering industry publications.
About the Organization
Maven Solutions is a software engineer-founded, engineer-run IT services provider focused on helping companies achieve business goals with better technology infrastructure. Clients rely on Maven Solutions for Kubernetes Consulting, DevOps Consulting, AI Cloud Consulting, and Platform Engineering services.