A container presents a process with a controlled view of its filesystem, networking and other resources. It is not simply a compressed virtual machine. Docker describes containers as isolated processes, while images supply the files and configuration from which those environments are created. The runtime and host operating system implement the isolation mechanisms and resource controls. [1]

An image is an immutable package assembled from layers and configuration. A container created from it can add a writable layer for changes made during execution. Several containers can use the same base image while having separate writable state. Changing a running container does not rewrite the original image into a new reproducible release automatically. [2][3]

Layers can share storage efficiently, but their presence does not mean every application dependency is safe or current. The image's origin and build inputs matter. A reproducible package can reproduce a vulnerability just as consistently as it reproduces correct behavior. Packaging and security review are complementary responsibilities. [7]

A registry stores and distributes images. Human-friendly tags help identify intended versions, while an immutable content digest identifies specific image content. A tag that can be reassigned is weaker evidence of exact identity than a digest. Recording only latest is especially ambiguous when trying to reproduce a deployment or investigate an incident. [5][2]

Containers generally share the kernel of the environment in which they run. The operating-system family and CPU architecture therefore matter. Docker's multi-platform guidance explains that a Linux AMD64 image is not automatically native code for an ARM64 host, and a Windows container is not simply a Linux process. Emulation or an intervening VM can provide another compatibility layer with its own behavior. [6]

A container can run inside a virtual machine. In that arrangement, the VM supplies a guest kernel and virtualized resources, while the container isolates the application process within that environment. This explains why VM versus container is often the wrong either-or question. A complete deployment can use both to solve different problems. [1]

Resource availability also remains physical. Packaging an application that requests 64 GB of memory does not supply that memory. CPU quotas, memory limits, storage and network configuration determine what the process can use. Reproducibility requires both the artifact and enough information about the execution environment to interpret its behavior.

A container's writable layer is tied to that container's lifecycle. Docker volumes provide a separate storage mechanism whose lifetime can extend beyond an individual container. Bind mounts expose selected host paths with another set of ownership and access considerations. Choosing a storage mechanism should be deliberate, because restart, recreation and deletion are different lifecycle events. [3][4]

Secrets also need their own lifecycle. Baking credentials into image layers can spread them wherever the image is copied. Use the platform's supported secret-delivery mechanism and least-privilege access. A deployment specification should identify which configuration is public, which is sensitive and how credentials are rotated without rebuilding unrelated application content.

GPU access requires devices and host support to be exposed through the runtime. NVIDIA Container Toolkit integrates those requirements for supported configurations; Container Device Interface provides a mechanism for describing device access in compatible runtimes. An image can carry application libraries without containing a substitute for the actual host driver and accelerator. [8][9]

An application may require several cooperating containers, storage services and network policies. Tools such as Docker Compose describe multi-container arrangements, while larger orchestration systems manage additional scheduling and lifecycle concerns. Starting one healthy process does not prove that its dependencies are reachable, migrations succeeded or user-facing requests work correctly. [10]

Build from identified inputs, scan and test the artifact, record its digest, supply runtime configuration explicitly and keep important state in a deliberately managed location. Test a fresh instance rather than only the long-lived development container. Measure resource use on the intended host architecture, and document the rollback artifact before replacing a production release.

The central distinction is package versus environment versus service. An image packages files, a runtime creates a constrained process environment, and a complete deployment connects that process to resources and dependencies. Containers make these boundaries easier to manage, but they do not remove them. Understanding what remains outside the image is essential to using it reliably.