Why monitoring containers matters in Docker - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the command to list all running Docker containers.

Docker

docker [1]

Drag options to blanks, or click blank then click option'

Arun

Bps

Cimages

Dstop

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'docker images' lists images, not containers.

Using 'docker run' starts a container, not lists them.

The docker ps command shows all running containers.

2fill in blank

medium

Complete the command to check the logs of a container named 'webapp'.

Docker

docker logs [1]

Drag options to blanks, or click blank then click option'

Awebapp

Bstart

Cstop

Dps

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'start' or 'stop' instead of the container name.

Using 'ps' which lists containers, not logs.

The docker logs webapp command shows the logs of the container named 'webapp'.

3fill in blank

hard

Fix the error in the command to monitor container stats continuously.

Docker

docker [1]

Drag options to blanks, or click blank then click option'

Aimages

Brm

Cstats

Dstop

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'stop' or 'rm' which stop or remove containers.

Using 'images' which lists images, not stats.

The docker stats command shows real-time resource usage of containers.

4fill in blank

hard

Fill both blanks to create a command that filters running containers by name 'db'.

Docker

docker ps --filter [1]=[2]

Drag options to blanks, or click blank then click option'

Aname

Bstatus

Cdb

Dimage

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'status' or 'image' as filter keys incorrectly.

Using wrong filter values.

The docker ps --filter name=db command lists containers with 'db' in their name.

5fill in blank

hard

Fill all three blanks to create a command that shows logs of container 'api' with timestamps and follows output.

Docker

docker logs [1] [2] [3]

Drag options to blanks, or click blank then click option'

A--timestamps

Bapi

C--follow

D--tail

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up option order or missing container name.

Using '--tail' without a number.

The command docker logs api --timestamps --follow shows live logs with timestamps for the 'api' container.

Practice

1. Why is monitoring Docker containers important in a production environment?

easy

A. To increase the size of the container images

B. To reduce the number of containers running

C. To detect performance issues and prevent downtime

D. To disable container networking

Solution

1. Step 1: Understand container monitoring purpose

   Monitoring helps track container health and performance to avoid failures.

2. Step 2: Identify key benefit in production

   Detecting issues early prevents downtime and keeps services running smoothly.

3. Final Answer:

   To detect performance issues and prevent downtime -> Option C

4. Quick Check:

   Monitoring = Prevent downtime [OK]

Hint: Monitoring helps catch problems early to avoid downtime [OK]

Common Mistakes:

• Thinking monitoring changes container size
• Believing monitoring reduces container count
• Assuming monitoring disables networking

2. Which Docker command shows real-time resource usage of running containers?

easy

A. docker ps

B. docker stats

C. docker images

D. docker logs

Solution

1. Step 1: Recall Docker commands for monitoring

   docker stats shows live CPU, memory, and network usage.

2. Step 2: Compare with other commands

   docker ps lists containers, docker images lists images, docker logs shows logs, none show live resource stats.

3. Final Answer:

   docker stats -> Option B

4. Quick Check:

   docker stats = live resource usage [OK]

Hint: Use docker stats for live container resource info [OK]

Common Mistakes:

• Using docker ps to check resource usage
• Confusing docker logs with stats
• Thinking docker images shows container info

3. What is the output of the command docker stats --no-stream?

medium

A. Error: invalid option

B. Continuous live updates of container stats

C. List of all running containers

D. A single snapshot of current container resource usage

Solution

1. Step 1: Understand --no-stream option

   This option disables continuous updates and shows only one snapshot.

2. Step 2: Identify output type

   The command outputs current CPU, memory, and network usage once, not continuously.

3. Final Answer:

   A single snapshot of current container resource usage -> Option D

4. Quick Check:

   --no-stream = single snapshot [OK]

Hint: --no-stream means show stats once, not live [OK]

Common Mistakes:

• Expecting continuous live updates
• Confusing with docker ps output
• Assuming it lists containers

4. You run docker stats but see no output even though containers are running. What is the likely cause?

medium

A. You ran the command without root or proper permissions

B. Docker daemon is not running

C. Containers are stopped

D. The docker stats command is deprecated

Solution

1. Step 1: Check container status

   Containers are running, so they are not stopped.

2. Step 2: Consider permissions

   docker stats requires permission; without it, no output appears.

3. Step 3: Verify Docker daemon

   If daemon was down, other commands would fail too.

4. Final Answer:

   You ran the command without root or proper permissions -> Option A

5. Quick Check:

   Permission issues cause no output [OK]

Hint: Run Docker commands with proper permissions or sudo [OK]

Common Mistakes:

• Assuming containers are stopped
• Thinking Docker daemon is off without checking
• Believing docker stats is deprecated

5. You want to monitor container resource usage and send alerts if CPU usage exceeds 80%. Which approach best fits this goal?

hard

A. Set up automated monitoring with tools like Prometheus and alert rules

B. Restart containers frequently to avoid high CPU

C. Use docker stats manually and check CPU usage occasionally

D. Increase container memory limits to reduce CPU usage

Solution

1. Step 1: Understand manual vs automated monitoring

   Manual checks are unreliable and slow for alerts.

2. Step 2: Identify best practice for alerting

   Automated tools like Prometheus collect metrics and trigger alerts automatically.

3. Step 3: Evaluate other options

   Restarting containers or increasing memory does not guarantee CPU stays below threshold.

4. Final Answer:

   Set up automated monitoring with tools like Prometheus and alert rules -> Option A

5. Quick Check:

   Automated monitoring + alerts = best practice [OK]

Hint: Use monitoring tools with alerting, not manual checks [OK]

Common Mistakes:

• Relying on manual docker stats checks
• Restarting containers without root cause analysis
• Assuming more memory fixes CPU spikes