What is Kubernetes?
Kubernetes is an open-source container orchestration platform that automates deploying, scaling and managing containerised applications. It schedules containers across a cluster of machines, restarts failed ones automatically, and handles networking and scaling so that applications keep running reliably even at very large scale.
How does Kubernetes work?
Kubernetes, often abbreviated to K8s, is an open-source platform that automates the deployment, scaling and operation of containerised applications. Originally developed at Google and now maintained as a widely adopted open standard, it takes a fleet of machines - a cluster - and treats them as a single pool of resources. You describe the desired state of your application in configuration, and Kubernetes continuously works to make reality match that description, placing containers where there is capacity, replacing them when they fail, and shifting workloads when machines come and go.
Applications run inside containers, which are grouped into the smallest deployable unit, called a pod. A control plane decides where pods should run and monitors their health, while worker nodes do the actual running. If a node dies or a container crashes, Kubernetes reschedules the affected workloads automatically.
Why Kubernetes matters
Running a handful of containers by hand is manageable; running hundreds across many servers, with scaling, failover and rolling updates, quickly becomes impossible to do reliably by hand. Kubernetes automates that operational burden. It keeps applications available by restarting failed components, scales them up and down with demand, balances traffic between them, and enables zero-downtime deployments through controlled rollouts. For organisations adopting microservices, it has become the standard way to operate large numbers of containers consistently at scale.
What problems does Kubernetes solve?
Its core capabilities include:
- Self-healing - restarting or rescheduling failed containers automatically.
- Scaling - adding or removing instances based on load.
- Service discovery and load balancing - routing traffic to healthy pods.
- Rolling updates and rollbacks - releasing new versions without downtime.
- Declarative configuration - managing the cluster through version-controlled definitions.
Best practices for Kubernetes
Define everything declaratively and keep those definitions in version control, treating the cluster as infrastructure as code rather than something configured by hand. Set resource requests and limits so that workloads are scheduled sensibly and do not starve one another of memory or processing power. Use readiness and liveness health checks so that Kubernetes can detect and replace unhealthy containers automatically. Apply sensible security defaults and network policies from the start. Above all, be honest about whether you need Kubernetes at all, since its considerable power comes with real operational complexity that many smaller workloads simply do not justify carrying.
How PixelForce approaches Kubernetes
At PixelForce, the operational architecture is chosen during Phase 1 Scoping and Design, sized to what the product genuinely needs rather than to fashion. Our in-house Adelaide team uses Kubernetes where microservices and scale justify it, and recommends simpler managed approaches when they do not - honest, consequence-aware advice that avoids over-engineering. This orchestration work sits within our AWS DevOps consulting australia capability, and the containers Kubernetes manages are explained in containerisation.
Where this applies
The PixelForce services where Kubernetes matters most - explore how we put it to work in client products.
Frequently asked questions
They solve different problems and are often used together. Docker is a technology for building and running individual containers - it packages an application with its dependencies. Kubernetes orchestrates many containers across a cluster of machines, handling scheduling, scaling, networking and self-healing. In short, Docker creates and runs containers, while Kubernetes manages large numbers of them in production at scale.
No. Kubernetes shines when you run many containers across multiple servers and need automated scaling, failover and rolling updates - typically microservices at scale. For a small application or a single service, it can add significant operational complexity without proportional benefit. Simpler options such as managed container services or a single server may serve smaller workloads better, so the decision should match real needs.
A pod is the smallest deployable unit in Kubernetes. It wraps one or more closely related containers that share networking and storage and are always scheduled together. Most pods run a single container, but tightly coupled helpers can share a pod. Kubernetes manages pods rather than individual containers directly, creating, replacing and scaling them according to the desired state you declare.
Kubernetes is powerful but carries real operational complexity, including cluster setup, networking, security and ongoing maintenance. Managed services from cloud providers reduce this burden considerably by handling much of the control plane for you. Even so, teams need genuine expertise to run it well. For this reason, the decision to adopt Kubernetes should weigh its benefits honestly against the complexity it introduces.
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