6.1 Containers and Docker
You can containerise an application and have it run identically on your laptop and a server.
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The same thing, three names
One idea, sold under a different brand by each provider. Learn it once and you can read any job advertisement.
- On AWS
- ECR + ECS
- On Azure
- Azure Container Registry + Container Apps
- On Google Cloud
- Artifact Registry + Cloud Run
A container packages an application with everything it needs, so it runs identically on a laptop and a server — this is the topic where works on my machine stops being a sentence. Images, layers, registries, and a Dockerfile that is small and cacheable are the craft; ports, volumes and environment configuration are the seams to the outside. It opens the containers module because Kubernetes assumes all of it. The common confusion is containers as lightweight virtual machines; they share the host kernel, which is why they start in milliseconds and isolate more weakly.
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Images, layers, containers and registries
An image is a stack of read-only layers, a container is a running instance of one, and a registry is where images are stored and fetched from. These four words carry the whole model.
Writing a Dockerfile that is small and cacheable
A well-written build file produces a small image and reuses cached layers, which affects both how fast your pipeline runs and how much surface an attacker has. Both improvements come from the same habits.
Ports, volumes and environment configuration
Containers are isolated from the host until you deliberately connect them, through published ports, mounted volumes and environment settings. Those three connections are where configuration lives.
Why 'works on my machine' stops being a sentence
Shipping the environment with the application is what removes the class of bug that only appears on someone else's machine. This item is the payoff for the three above it.
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