A container packages a program with everything it needs to run. When you have just a few, you can manage them manually. When you have dozens or hundreds, you need a system to manage it all: container orchestration.

How it works

You describe the desired state, for example "I want 3 copies of this application running". The orchestrator compares that desire with reality and acts to make them match.

The main functions are:

  • Scheduling: decide which server each container runs on, based on free CPU and memory.
  • Scaling: increase or decrease the number of copies according to demand.
  • Self-healing: restart a container that crashes or move work if a server fails.
  • Networking and discovery: let services find each other and split traffic between copies.
  • Rolling updates: swap the version without taking the service down.

The most used orchestrator is Kubernetes. Docker Compose handles smaller projects on a single machine, and there are other options.

Practical example

You have an API that calls an AI model and receives access peaks in the afternoon. With an orchestrator, you define the minimum and maximum number of copies, and the system creates more when usage goes up.

A simple example with Docker Compose, for one machine:

YAML · docker-compose.yml
services:
  api:
    image: minha-api:1.0
    ports:
      - "8080:8080"
    deploy:
      replicas: 3
    restart: always

In this file, restart: always restarts the container if it crashes. In a larger cluster, Kubernetes takes on similar functions, but with many more resources.

What it is for

It is for keeping applications available, scaling with demand and doing safe deploys. In AI, it is widely used to run inference servers, processing queues and GPU clusters that serve multiple models.

It also helps standardize environments: what runs in test runs the same in production.

Difference between container orchestration and agent orchestration

They are different things. Container orchestration takes care of infrastructure: where and how programs run. Agent orchestration takes care of work: how several AI agents split tasks and coordinate. One can run on top of the other, but they are not confused.

When not to use

Full orchestrators have a learning curve and maintenance cost. For a small site or a prototype, simple hosting or Docker Compose is usually enough. Adopt something bigger when the need really appears.