Computer Science
Grade 11
20 min
Containerization: Docker and Kubernetes
Introduce containerization technologies like Docker and Kubernetes.
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1
Introduction & Learning Objectives
Learning Objectives
Define containerization and explain its benefits over traditional virtualization.
Differentiate between a Docker image and a Docker container.
Identify the core components of a Dockerfile (FROM, RUN, COPY, CMD).
Explain the role of Kubernetes as a container orchestrator.
Distinguish between the functions of Docker and Kubernetes in a cloud environment.
Interpret a basic Kubernetes Deployment manifest (YAML file).
Ever wonder how apps like Netflix or Spotify update constantly without you even noticing any downtime? 🤔 The magic behind this is a technology that packages applications into tiny, self-contained boxes.
This lesson introduces containerization, a fundamental concept in modern cloud computing. We will explore Docker, the tool for creating these &...
2
Key Concepts & Vocabulary
TermDefinitionExample
ContainerA lightweight, standalone, executable package of software that includes everything needed to run it: code, runtime, system tools, system libraries, and settings. It's like a standardized shipping container for software.A single running instance of a Nginx web server, isolated from all other processes on the host machine.
ImageA read-only template with instructions for creating a container. It's the blueprint or recipe. An image is built from a set of instructions in a file called a Dockerfile.A `python:3.9-slim` image contains the Python 3.9 runtime and a minimal Linux operating system, ready to run a Python script.
DockerA platform and tool for building, shipping, and running containers. It provides the 'Docker Engine,' a runtime that ma...
3
Core Syntax & Patterns
Dockerfile Basic Syntax
FROM <base_image>
WORKDIR /app
COPY . /app
RUN <command>
CMD ["executable"]
This pattern is used to create a Docker image. `FROM` specifies the starting image. `WORKDIR` sets the working directory. `COPY` adds files from your host. `RUN` executes build commands. `CMD` provides the default command to run when the container starts.
Kubernetes Deployment Manifest Structure
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
spec:
replicas: 3
selector:
matchLabels:
app: my-app
template:
metadata:
labels:
app: my-app
spec:
containers:
- name: my-app-container
image: my-app-image:1.0
This YAML structure defines a desired state in Kubernetes. `apiVersion` and `kind` spe...
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Challenging
Consider this Dockerfile snippet:
1: FROM python:3.9-slim
2: WORKDIR /app
3: COPY . .
4: RUN pip install -r requirements.txt
5: CMD ["python", "app.py"]
What is the primary performance issue with this Dockerfile, and how can it be fixed to leverage Docker's build cache more effectively?
A.The `WORKDIR` command is slow; it should be placed at the end. Fix: Move line 2 after line 4.
B.The `COPY . .` command invalidates the cache whenever any file changes. Fix: Copy `requirements.txt` first, run `pip install`, then copy the rest of the code.
C.The `CMD` instruction should use single quotes instead of double quotes for better performance. Fix: Change line 5 to `CMD ['python', 'app.py']`.
D.The `python:3.9-slim` image is too large. Fix: Use a smaller base image like `alpine`.
Challenging
A developer argues that for their small, single-container web application, they only need Docker and not Kubernetes. Under which scenario is their argument most valid, and at what point does Kubernetes become essential?
A.The argument is never valid; Kubernetes is always required to run a Docker container.
B.Valid for development on a single machine. Kubernetes becomes essential when needing high availability, automatic scaling, and management across multiple servers.
C.Valid for applications with high traffic. Kubernetes is only needed for applications with very low traffic.
D.Valid only if the application has no dependencies. Kubernetes is required as soon as `pip install` is used.
Challenging
A Kubernetes cluster consists of 3 Nodes. A Deployment is created with `replicas: 5`. Assuming each Node has sufficient resources, what will be the state of the cluster, and what is the primary risk if one Node fails?
A.The Deployment will fail because there are more replicas than Nodes. The risk is that no Pods will run.
B.Only 3 Pods will be scheduled (one per Node). The risk is that the desired state of 5 replicas is not met.
C.5 Pods will be scheduled, with some Nodes running one Pod and others running two. The risk is that a Node failure could cause a temporary dip below the desired replica count.
D.5 Pods will be scheduled across the 3 Nodes. The risk is that if a Node running two Pods fails, the application will lose more than one-third of its capacity until the Pods are rescheduled.
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