Title: Midterm Exam
Course: AIINFRA 101: Applied Infrastructure & Containerization > Section: Week 07 — Kubernetes Workloads: Deployments, Services, Config

📝 Midterm Exam (100 pts)

Note: the answer key below is for instructor reference only and is hidden from the student-facing view of this exam. This exam covers all material from Weeks 1–6: containerization fundamentals, Docker images and Dockerfiles, container registries, Docker Compose, container networking/storage, and core Kubernetes concepts (cluster architecture, Pods, and scheduling basics).

Part A — Applied Scenario (40 pts)

You're supporting a small team that has been running a FastAPI-based iris-classifier inference service (from Week 3) as a single Docker container on one developer's laptop using docker run. The team wants to hand this off to you to containerize properly and get it running reliably on a small Kubernetes cluster, in preparation for adding replicas and a stable network endpoint next week. Describe, step by step, how you would take this from "container running ad hoc on a laptop" to "image built, pushed to a registry, and a single Pod running on the cluster," and explain what could go wrong at each step and how you'd verify it worked. → Model answer: (1) Write/confirm a Dockerfile with a minimal base image, copy in the FastAPI app and dependencies, expose the correct port, and set the correct CMD/entrypoint — verify by building locally with docker build and running with docker run -p to confirm the API responds. (2) Tag the image appropriately (e.g., registry/iris-classifier:v1) and push it to a container registry — verify by pulling it fresh on another machine or docker rmi + re-pulling to confirm it's not relying on local build cache. (3) Write a Pod manifest (or minimal Deployment) referencing the pushed image, apply it with kubectl apply -f, and use kubectl get pods / kubectl describe pod / kubectl logs to confirm it reaches Running status and the app logs show successful startup. Common failure points: forgetting to expose/bind the right port, pushing to a registry the cluster can't authenticate to or pull from (ImagePullBackOff), and forgetting resource requests, which the course has emphasized are needed for the scheduler to place the Pod sensibly.

Part B — Weeks 1–6 Review (60 pts, 5 pts each)

1. (MC) What is the primary difference between a container and a virtual machine?

a) Containers require a full guest OS; VMs don't b) Containers share the host OS kernel; VMs each run their own full OS c) Containers are always slower to start than VMs d) There is no meaningful difference → b

1. (TF) A Docker image and a Docker container are the same thing.

→ False — an image is the immutable template; a container is a running (or stopped) instance created from that image.

1. (Short answer) What Dockerfile instruction is used to specify the command that runs when a container starts?

→ CMD (or ENTRYPOINT)

1. (MC) Why do we use multi-stage builds in a Dockerfile?

a) To make builds slower for security b) To keep the final image small by excluding build-time-only dependencies c) To run multiple containers at once d) To avoid using a registry → b

1. (TF) Layers in a Docker image are cached, so reordering Dockerfile instructions can significantly speed up rebuilds.

→ True

1. (Short answer) What is the purpose of a container registry (e.g., Docker Hub, a private registry)?

→ It stores and distributes container images so they can be pulled and run on other machines/clusters.

1. (MC) In Docker Compose, what is the main benefit of defining multiple services in one docker-compose.yml?

a) It removes the need for images b) It lets you define and run a multi-container application together with shared networking/volumes as one unit c) It replaces Kubernetes entirely d) It only works for databases → b

1. (TF) By default, containers on the same user-defined Docker network can reach each other by container/service name.

→ True

1. (Short answer) What is the smallest deployable unit in Kubernetes?

→ The Pod

1. (MC) Which Kubernetes component is responsible for deciding which node a new Pod should run on?

a) kubelet b) etcd c) the scheduler d) the Service → c

1. (TF) A single Pod can contain more than one container that share the same network namespace and can communicate over localhost.

→ True

1. (Short answer) Why is persistent storage (e.g., a volume) needed for stateful workloads in Kubernetes, given that container filesystems are ephemeral by default?

→ Because any data written to a container's writable layer is lost when the container/Pod is deleted or rescheduled; a volume decouples data from the Pod's lifecycle so it survives restarts/rescheduling.