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Automate the running of containers at scale: placement, scaling, healing, networking.
Quick Definition
Container orchestration automates the deployment, scaling, networking, and lifecycle management of containers across a cluster. Kubernetes is the dominant orchestrator, handling scheduling, self-healing, and load balancing so teams can run containerized applications reliably at scale.
Running five containers by hand is easy. Running five thousand is not. Container orchestration automates the operational work: deciding which machine each container runs on, restarting failures, scaling with demand, and wiring networking between services.
Kubernetes won this category and is now the default orchestrator almost everywhere. Orchestration matters for cost as much as for operations: the orchestrator's placement decisions determine how tightly workloads are packed, and packing efficiency directly sets how many billed machines you need.
Example. Without orchestration, an ops team manually restarts crashed services at night and over-provisions everything to be safe. With it, failures self-heal in seconds and capacity follows demand, cutting both pager noise and the standing bill.
This introduction to container orchestration covers the fundamentals, and the Kubernetes Cost Management Guide covers what the orchestrator means for your bill.
It is the dominant one. Alternatives such as Nomad and managed simpler services exist, but Kubernetes is the industry standard.
Scheduling, scaling, self-healing, rolling deployments, service discovery, and configuration distribution.
Its scheduling decisions set node utilization. Good configuration packs tightly and scales down; defaults often leave large idle margins.