An applied Swiss-inspired curriculum combining algorithmic rigour, systems architecture, digital trust and practical engineering capability for modern technology leaders.
The MSc in Cloud Computing at Brookfield School of Computing is engineered to provide deep competency across core computer science, systems design, and targeted domain applications. Students develop fluency in software craftsmanship, distributed architectures, algorithm optimization, and data governance.
Instruction balances rigorous theoretical foundations with practical code repositories, laboratory simulations, and ethical technology review aligned with modern international computing standards.
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| CLD711 | Advanced Distributed Systems Principles & Consensus Theory in Cloud Computing | Theory | Evaluate CAP theorem, PACELC tradeoffs, formal consensus proofs (Paxos, Raft) and distributed clocks in Cloud Computing. |
| CLD712 | Distributed Systems Architecture & Cluster Engineering Lab | Practical | Implement distributed state machines, leader election algorithms and gossip protocols in Go/Rust. |
| CLD713 | Software-Defined Networking & Advanced Cloud Protocols | Theory | Deconstruct BGP routing, VXLAN overlays, DPDK packet acceleration and software-defined WAN architectures. |
| CLD714 | High-Performance Cloud Networking & eBPF Datapath Lab | Practical | Configure Cilium CNI, write eBPF network datapath programs and optimize kernel packet throughput. |
| CLD715 | Distributed Storage Systems, LSM-Trees & Block Storage Design | Theory | Model distributed object storage (Ceph), LSM-tree storage engines (RocksDB) and consistent hashing rings. |
| CLD716 | Distributed Key-Value Store & Storage Engine Workshop | Practical | Engineer a high-throughput distributed key-value storage engine featuring Write-Ahead Logs (WAL) and compaction. |
| CLD717 | Empirical Distributed Systems Benchmarking & Methodology | Theory | Design rigorous latency percentile (p99/p99.9) benchmarking, network partition simulations and reproducibility. |
| CLD718 | Multi-Cloud Infrastructure Automation Lab (Terraform / Pulumi) | Practical | Author reusable Infrastructure-as-Code modules managing complex multi-region AWS and Azure cloud deployments. |
| CLD719 | Cloud Governance, Swiss Data Residency & Transnational Compliance | Theory | Audit cloud data flows against Swiss Federal Data Protection Act, CLOUD Act implications and data sovereignty. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| CLD721 | Cloud-Native Microservices, Event Sourcing & CQRS in Cloud Computing | Theory | Architect event-driven enterprise microservices using Apache Kafka, transactional outbox patterns and CQRS. |
| CLD722 | Kubernetes Internals & Custom Resource Operator Engineering | Practical | Build custom Kubernetes operators using Kubebuilder and Go to automate stateful distributed application lifecycles. |
| CLD723 | Serverless Architectures, Knative & Edge Function Computing | Theory | Analyze cold-start latency mitigation, WebAssembly (Wasm) runtimes and event-driven serverless orchestration. |
| CLD724 | Serverless Microservices & Low-Latency Edge Lab | Practical | Deploy serverless functions with Knative and Cloudflare Workers integrating distributed caching and KV stores. |
| CLD725 | Cloud Observability, Distributed Tracing & OpenTelemetry | Theory | Model distributed context propagation, high-cardinality metrics storage and algorithmic anomaly detection. |
| CLD726 | OpenTelemetry, Jaeger & Prometheus Distributed Tracing Studio | Practical | Instrument large-scale microservice clusters, visualize distributed traces in Jaeger and build SLO dashboards. |
| CLD727 | Cloud Financial Operations (FinOps) & Workload Rightsizing | Theory | Formulate cloud unit economics, spot instance orchestration algorithms and multi-tenant resource quotas. |
| CLD728 | Chaos Engineering & Cloud Fault Injection Lab (Chaos Mesh) | Practical | Simulate cloud availability zone failures, cross-region packet drops and DNS blackholes to verify resilience. |
| CLD729 | Enterprise Multi-Cloud Case Study & Production Architecture Review | Practical | Deliver a comprehensive disaster-tolerant multi-cloud architectural design addressing real-world workloads. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| CLD731 | Frontiers in Edge Computing, Fog Architectures & 5G Integration | Theory | Critically evaluate ultra-reliable low-latency communication (URLLC), edge intelligence and fog offloading. |
| CLD732 | Edge Intelligence & Low-Power Cluster Workshop (K3s) | Practical | Deploy lightweight K3s clusters on edge nodes with local inference offloading and intermittent sync. |
| CLD733 | Strategic Cloud Leadership, Enterprise Modernization & Vendor Strategy | Theory | Formulate enterprise cloud migration business cases, negotiate cloud provider contracts and mitigate vendor lock-in. |
| CLD734 | High-Performance Computing (HPC) & InfiniBand Cluster Lab | Practical | Configure MPI clusters, GPU interconnects (NVLink) and SLURM workload schedulers for parallel computing workloads. |
| CLD735 | Confidential Computing, Enclaves & Zero-Trust Cloud Infrastructure | Theory | Evaluate AMD SEV, Intel SGX hardware enclaves, memory encryption and attestation in untrusted cloud environments. |
| CLD736 | MSc Cloud Computing Thesis Proposal Colloquium & Defense | Practical | Author and defend a formal scientific master's research proposal specifying distributed system testbeds. |
| CLD737 | Cloud Venture Creation, SaaS Economics & Technology Transfer | Theory | Examine SaaS business models, customer acquisition unit economics, API monetization and venture funding. |
| CLD738 | Pre-Thesis Distributed Architecture Prototyping & Pilot Lab | Practical | Construct initial experimental distributed system prototypes and gather preliminary validation metrics. |
| CLD739 | Industry Cloud Platform Practicum & Large-Scale Deployment | Practical | Deploy and benchmark software system prototypes within simulated production cloud infrastructure. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| CLD741 | MSc Cloud Computing Dissertation: Empirical Methodology & Distributed Testbed Setup | Practical | Establish the multi-node distributed testbed, fault-injection harnesses and benchmark metrics in Cloud Computing. |
| CLD742 | MSc Cloud Computing Dissertation: System Architecture & Distributed Engineering | Practical | Engineer the complete distributed computational platform embodying the novel research contribution in Cloud Computing. |
| CLD743 | MSc Cloud Computing Dissertation: Empirical Scalability & Fault Tolerance Validation | Practical | Execute rigorous multi-region scalability benchmarks, network partition stress tests and statistical evaluations. |
| CLD744 | Critical Literature Synthesis & State-of-the-Art Analysis in Cloud Computing | Theory | Synthesize academic publications from OSDI, SOSP, EuroSys and NSDI conferences. |
| CLD745 | Scalability Benchmarking, Telemetry Hardening & Audit Lab | Practical | Subject the dissertation platform to extreme workload spikes, resource exhaustion tests and automated audits. |
| CLD746 | Scientific Manuscript Preparation & Peer Review in Cloud Computing | Theory | Author a publication-ready academic manuscript adhering to IEEE/ACM distributed systems conference standards. |
| CLD747 | Executive Cloud Strategy & Enterprise Architectural Advisory | Theory | Translate cutting-edge cloud research into actionable C-suite technology strategies and infrastructure roadmaps. |
| CLD748 | Comprehensive Cloud Systems Portfolio & Reproducible Infrastructure | Practical | Package reproducible Terraform modules, Kubernetes manifests, benchmark scripts and technical documentation in Cloud Computing. |
| CLD749 | MSc Cloud Computing Thesis Oral Defense & Public Academic Examination | Practical | Defend the novel scientific thesis and distributed systems architecture before an academic examination committee. |
Recognized Bachelor Degree in computing, engineering, mathematics, quantitative discipline or relevant technical equivalence. English proficiency IELTS 6.5+ or equivalent.
Brookfield School of Computing is an independent private education institution in formation. Academic programmes, entry requirements, fees and awards are subject to institutional review and applicable Swiss legal regulations.