This course covers the concepts, architecture, and operational practice of cloud computing. Students work through the full stack a modern cloud application rests on — virtualization and containers, elastic compute, object and block storage, virtual networking, identity and access management, managed data services, and the distributed-systems ideas that make these services behave the way they do. The course is built around deployment: students provision, containerize, automate, and instrument real services on a public cloud provider, and are expected to account for the cost, security, and reliability consequences of every architectural decision they make.
Dial in: +1 318-519-1293 · PIN 274 415 158# · more numbers
Posted before the session they're used in and kept available all term. Each set is a self-contained page — read it, work the examples, and bring questions.
The schedule is aligned to the LIU Brooklyn academic calendar; any session affected by a University holiday or closure is adjusted and announced in class and on Brightspace. The current week is highlighted.
| Week | Sessions | Topic | Materials | To do |
|---|---|---|---|---|
| WK 1 | S1 · Sep 2 | Course overview. What the cloud is, service and deployment models, cloud economics | Notes 01 |
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| WK 2 | S2 · Sep 9 | Virtualization, hypervisors, instances, and the container model◦ Sep 7 — no class (Labor Day) | Notes 02 |
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| WK 3 | S3–S4 · Sep 14, Sep 16 | Compute: instance types, images, autoscaling, and serverless functions | Notes 03 |
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| WK 4 | S5–S6 · Sep 21, Sep 23 | Storage: object, block, and file. Durability, availability, and consistency | Notes 04 · soon |
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| WK 5 | S7–S8 · Sep 28, Sep 30 | Networking: VPCs, subnets, routing, load balancing, DNS, and CDNs Project 1 due |
Notes 05 · soon |
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| WK 6 | S9–S10 · Oct 5, Oct 7 | Identity and access management, secrets, encryption, shared responsibility | Notes 06 · soon |
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| WK 7 | S11–S12 · Oct 12, Oct 14 | Docker in depth: images, layers, registries, and build practice | Notes 07 · soon |
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| WK 8 | S13–S14 · Oct 19, Oct 21 | Container orchestration: Kubernetes concepts, services, and scaling Project 2 due |
Notes 08 · soon |
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| WK 9 | S15–S16 · Oct 26, Oct 28 | Managed data services: relational and NoSQL databases, caching | Notes 09 · soon |
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| WK 10 | S17–S18 · Nov 2, Nov 4 | Distributed systems: replication, partitioning, CAP, and consensus | Notes 10 · soon |
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| WK 11 | S19–S20 · Nov 9, Nov 11 | Messaging, queues, and event-driven architecture. Idempotency and retries | Notes 11 · soon |
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| WK 12 | S21–S22 · Nov 16, Nov 18 | Infrastructure as code with Terraform. CI/CD pipelines Project 3 due |
Notes 12 · soon |
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| WK 13 | S23–S24 · Nov 23, Nov 25 | Observability: logging, metrics, tracing, alerting, and SRE practice Capstone proposal due |
Notes 13 · soon |
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| WK 14 | S25–S26 · Nov 30, Dec 2 | Cost optimization, capacity planning, multi-cloud, and managed AI/ML services | Notes 14 · soon |
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| WK 15 | S27–S28 · Dec 7, Dec 9 | Cloud architecture review and trade-offs. Capstone presentations | Notes 15 · soon |
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| FINALS | Dec 14 – 21 | Final capstone deliverables due. No final examination. | ||
This course is graded entirely on four hands-on projects — there are no exams. Specifications and rubrics are released at least two weeks before each due date. Every project is submitted as a Git repository plus a written report; late work is reduced by 10% per calendar day.
Deploy a working web service to a public cloud provider using compute, object storage, and DNS, secured with TLS and scoped IAM roles. Deliverables are the live endpoint, an architecture diagram, and a written cost estimate at three traffic levels.
Containerize an application of at least three cooperating services plus a managed datastore, publish the images to a registry, and run the system under an orchestration platform with health checks and horizontal scaling. The written component analyzes the failure modes of each service.
Reproduce the entire Project 2 environment from version-controlled infrastructure code, with a pipeline that builds, tests, and deploys automatically on commit. The environment must be destroyable and rebuildable from scratch — the demonstration is a full teardown and rebuild.
Design and deploy a scalable, observable cloud-native application of your own choosing, incorporating asynchronous messaging, autoscaling, and full instrumentation. Deliverables are the running system, a technical report covering cost and reliability, and a live presentation during the final session block.
Every project is graded on the same four criteria. Each project rubric is released with its specification.
| Criterion | Weight | What is assessed |
|---|---|---|
| Correctness and completeness | 35% | The artifact does what the specification requires, and the required cases are handled. |
| Implementation quality | 20% | Structure, readability, and evidence of testing. Commit history shows sustained individual work. |
| Analysis and written report | 25% | The report explains the design, justifies the decisions, and reports results honestly, including what did not work. |
| Demonstration and defense | 20% | The student can run the artifact live and answer questions about any part of it. |
| Letter | Range % | GPA |
|---|---|---|
| A | 93–100 | 4.00 |
| A- | 90–92 | 3.67 |
| B+ | 87–89 | 3.33 |
| B | 83–86 | 3.00 |
| B- | 80–82 | 2.67 |
| C+ | 77–79 | 2.33 |
| C | 73–76 | 2.00 |
| C- | 68–72 | 1.67 |
| D | 60–67 | 1.00 |
| F | < 60 | 0.00 |
| Synchronous class sessions | 51 h |
| Review of posted notes | 30 h |
| Project 1 — First Cloud Deployment | 17 h |
| Project 2 — Containerized Application | 20 h |
| Project 3 — Infrastructure as Code and CI/CD | 20 h |
| Project 4 — Capstone and presentation | 22 h |
| Total | 160 h |
Programming proficiency in a language of your choice and basic familiarity with the command line, or permission of the instructor.
All class sessions are held live on Google Meet at the scheduled times. Students are expected to attend, to have their development environment running, and to be able to share their screen when demonstrating work. Every student presents current work and takes part in critique at each meeting.
Modes of communication are Brightspace (lms.liu.edu) and email; expect a reply within 24 hours. Virtual office hours are held by appointment — email the instructor to schedule.
All course notes, examples, and project specifications are distributed through the course repository and this site. Students are responsible for reviewing the current version before each session.
Every project is submitted through Brightspace as a link to the student's Git repository, together with the written report. Commit history is part of the evidence of individual work. Late work is reduced by 10% per calendar day. Extensions are granted only for a documented medical or family emergency, requested before the deadline by email.
Projects are individual work unless a specification explicitly designates a team deliverable. Discussing approaches is fine, but submitted code, models, and writing must be your own. Generative AI tools may be used as a learning aid and are treated like any other reference: any AI-assisted portion of a submission must be disclosed in the project report, and you must be able to explain and defend every line of what you submit.
Recording of class sessions by students is not permitted without the instructor's prior written consent.
Students with a documented disability/impairment who require reasonable accommodations should provide an Accommodation Letter from Student Support Services (Sloan Building, 1st Floor · 718-488-1044 · studentsupportservices@brooklyn.liu.edu · Mon–Fri 9am–5pm).
For issues with Brightspace, LIU email, Google Meet, or campus network access, contact IT: It@liu.edu · 718-488-3300 (Mon–Fri 9am–5pm).