Container Lifecycle

Introduction

Every container moves through a predictable lifecycle: created → running → paused/stopped → removed. Knowing the transitions helps you debug 'why did my container die?' confidently.

Purpose of this lesson

This lesson teaches Container Lifecycle as an engineering decision: what problem it solves, when to use it, how to implement it safely, and what signals tell you it is failing.

Understanding the topic

Use this in day-to-day container operations: pulling images, running processes, inspecting failures, publishing artifacts, and keeping the Docker host clean and predictable.

Core concepts to understand:

• create sets up filesystem + config but doesn't start.
• start launches the entrypoint; stop sends SIGTERM (then SIGKILL after 10s).
• pause/unpause freeze the process (rare in practice).
• rm deletes the writable layer; data in volumes survives.

Visual explanation

Architecture or command flow to keep in mind:

created ──start──▶ running ──stop──▶ stopped
                  │                       │
                  └────pause──▶ paused    │
                                          │
                                  ──rm──▶ removed

Step-by-step explanation

1. Run the command or manifest exactly once on a clean Docker host and read the output carefully.
2. Inspect the object Docker created: image, container, network, volume, port mapping, process, or registry tag.
3. Break one realistic assumption such as a missing port, bad tag, stopped daemon, wrong network, or deleted volume.
4. Use docker ps, logs, inspect, stats, and system df to locate the failure.
5. Write the final command or configuration into a repeatable script, Compose file, or CI job.

Informative example

Use the example below as a working baseline, then verify the runtime behavior instead of assuming the command or file is correct.

created ──start──▶ running ──stop──▶ stopped
                  │                       │
                  └────pause──▶ paused    │
                                          │
                                  ──rm──▶ removed

A production-minded check usually includes docker ps, docker logs, docker inspect, and one validation from outside the container such as curl, a database connection, or a registry pull.

# Verification loop for Container Lifecycle
docker ps -a
docker logs --tail=100 <container-name>
docker inspect <container-or-image-name>
docker system df

Real-world use

On graceful shutdown your app receives SIGTERM. If you don't handle it, in-flight requests get killed at the 10s deadline.

Enterprise use cases

In a mature engineering organization, Container Lifecycle is documented as a repeatable pattern with approved base images, ownership labels, CI checks, security expectations, rollback notes, and troubleshooting commands. The difference between a tutorial and production practice is that every container decision must be observable, reviewable, and reversible.

Best practices

• Trap SIGTERM in your app and shut down gracefully.
• Tune --stop-timeout if your workload needs >10s to drain.

Debugging tips

• Read logs before restarting; a restart often removes the timing context you need for root cause analysis.
• Use docker inspect to compare configured state with actual runtime state.
• Check daemon health, disk usage, image tags, exit code, and port mappings before blaming application code.

Optimization strategies

• Prefer explicit names, labels, tags, and networks so cleanup and debugging stay predictable.
• Pin versions for repeatability, then update intentionally through a scheduled base-image refresh.
• Use docker system df and targeted prune commands to control local and CI disk growth.

Advanced interview questions

Hands-on exercise

Create a small lab for Container Lifecycle: run the example, inspect the created Docker object, intentionally introduce one mistake, and record the command that reveals the failure. The goal is not just to make the happy path work; it is to build operational reflexes.

# Hands-on lab scaffold
mkdir -p docker-container-lifecycle-lab
cd docker-container-lifecycle-lab

# Add the Dockerfile, compose.yml, or command from this lesson.
# Then run one happy-path test and one broken-path test.
docker version
docker info
docker system df

Summary

Container Lifecycle matters because Docker is not only a packaging tool; it is a runtime, build, networking, storage, and delivery workflow. Treat each lesson as a production habit: make it repeatable, inspectable, secure, and easy to debug.