Cloud Computing (BSc CSIT, CSC465): the questions likely to come
26 analyzed questions from 7 past papers (2074-2081), grouped by syllabus unit — each with its probability, how often it's been asked, and where to study the answer.
Explain the concepts of scalability and elasticity in cloud computing. Discuss load balancing techniques and auto-scaling mechanisms with examples.
Scalability and Elasticity
Scalability is the ability of a cloud system to handle increasing workload by adding resources. It is a planned, long-term capability.
- Vertical scaling (scale up): Add more power (CPU, RAM) to an existing machine.
- Horizontal scaling (scale out): Add more machines/instances to share the load.
Elasticity is the ability to automatically and dynamically provision and de-provision resources in real time to match the current workload, so the system uses (and pays for) only what it needs. Elasticity is short-term and automatic; scalability is the underlying capacity that makes elasticity possible.
Load Balancing Techniques
A load balancer distributes incoming requests across multiple servers to avoid overloading any single server, improving throughput, availability and response time. Common techniques:
- Round Robin: Requests sent to servers in rotation.
- Weighted Round Robin: Stronger servers get proportionally more requests.
- Least Connections: New requests go to the server with the fewest active connections.
- Least Response Time: Server with lowest latency is chosen.
- IP Hash: Client IP is hashed to pick a server (session affinity).
Example: AWS Elastic Load Balancer (ELB) spreads web traffic across several EC2 instances.
Auto-Scaling Mechanisms
Auto-scaling automatically adjusts the number of running instances based on demand, implementing elasticity.
- Reactive / dynamic scaling: Adds/removes instances when a monitored metric (e.g., CPU > 70%) crosses a threshold.
- Scheduled scaling: Scales at known peak times (e.g., business hours).
- Predictive scaling: Uses forecasting/ML to provision capacity before demand arrives.
Example: An AWS Auto Scaling Group launches extra EC2 instances when average CPU > 70% and terminates them when CPU < 30%, while ELB load-balances across them.
Conclusion: Scalability provides the capacity, elasticity uses it on demand, and load balancing + auto-scaling together deliver elastic, highly available services.
Cloud Computing Architecture
Explain the concepts of scalability and elasticity in cloud computing. Discuss load balancing techniques and auto-scaling mechanisms with examples.
Explain the layered architecture of cloud computing. Discuss the role of the cloud broker, cloud carrier and the cloud reference model.
What is a Service Level Agreement (SLA)? Explain the components of an SLA and discuss how Quality-of-Service (QoS) is managed and monitored in cloud environments.
Discuss the security issues and challenges in cloud computing. Explain data security, identity and access management, and the techniques used to ensure confidentiality and integrity of cloud data.
What is cloud computing? Explain the essential characteristics of cloud computing and discuss the service models (IaaS, PaaS, SaaS) and deployment models (public, private, hybrid, community) with examples.
Differentiate between IaaS, PaaS and SaaS with examples.
Differentiate between public, private and hybrid cloud deployment models.
What is a Service Level Agreement (SLA)? List its key components.
Discuss the major security issues in cloud computing.
What is elasticity in cloud computing? How does it differ from scalability?
Explain the challenges involved in migrating an application to the cloud.
Explain the architecture of a cloud data center.
What is multi-tenancy? Explain its implementation issues in the SaaS model.
Explain the pay-as-you-go billing and metering model in cloud computing.
How is fault tolerance and high availability achieved in cloud computing?
Explain the essential characteristics of cloud computing.
Sit a probable paper
A full mock exam built from the most likely questions, mirroring the real paper's structure. Every slot is a real past question.
Most Probable Paper
Mirrors the real structure · 60 marks · based on 7 past papers
- 1.[10 marks]
Explain the concepts of scalability and elasticity in cloud computing. Discuss load balancing techniques and auto-scaling mechanisms with examples.
This question has recurred in 3 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
- 2.[10 marks]
Explain the layered architecture of cloud computing. Discuss the role of the cloud broker, cloud carrier and the cloud reference model.
This question has recurred in 3 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
- 3.[10 marks]
What is a Service Level Agreement (SLA)? Explain the components of an SLA and discuss how Quality-of-Service (QoS) is managed and monitored in cloud environments.
This question has recurred in 3 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
- 1.[5 marks]
Differentiate between IaaS, PaaS and SaaS with examples.
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
- 2.[5 marks]
Differentiate between public, private and hybrid cloud deployment models.
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
- 3.[5 marks]
What is a Service Level Agreement (SLA)? List its key components.
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
- 4.[5 marks]
Discuss the major security issues in cloud computing.
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
- 5.[5 marks]
What is virtualization? Explain its role in cloud computing.
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Virtualization) appears in 100% of years.
- 6.[5 marks]
What is a hypervisor? Differentiate between Type 1 and Type 2 hypervisors.
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Virtualization) appears in 100% of years.
- 7.[5 marks]
Explain the MapReduce programming model with a suitable example.
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Concurrent, High-Throughput and Data-Intensive Computing) appears in 86% of years.
- 8.[5 marks]
Write short notes on the Hadoop Distributed File System (HDFS).
This question has recurred in 4 of 7 years; so far only in internal assessments, not the board; and its topic (Concurrent, High-Throughput and Data-Intensive Computing) appears in 86% of years.
- 9.[5 marks]
What is elasticity in cloud computing? How does it differ from scalability?
This question has recurred in 3 of 7 years; so far only in internal assessments, not the board; and its topic (Cloud Computing Architecture) appears in 100% of years.
Behind the numbers
The raw evidence the predictions are computed from: marks per unit per year, syllabus weights, trends, and coverage.
Show the heatmap, topic table and coverage analysis
The receipt: marks per unit, per year
Each row is a syllabus unit, each column an exam year, each cell the marks that unit earned that year. Click any cell to see the actual questions behind it.
| # | Syllabus unit | Probability | Appeared | Avg marks | Syllabus weight | Exam vs syllabus | Trend | Questions |
|---|---|---|---|---|---|---|---|---|
| 1 | U4Cloud Computing Architecture | Very likely100% | 47.1 | 15%8 lecture hrs | Over-examinedexam 63% · syllabus 15% | Steady | 16 recurring16 total | |
| 2 | U3Virtualization | Very likely100% | 12.1 | 15%8 lecture hrs | Balancedexam 16% · syllabus 15% | Steady | 4 recurring4 total | |
| 3 | U6Concurrent, High-Throughput and Data-Intensive Computing | Very likely86% | 11.7 | 15%8 lecture hrs | Balancedexam 13% · syllabus 15% | Steady | 3 recurring3 total | |
| 4 | U7Cloud Platforms in Industry and Cloud Applications | Possible43% | 10 | 11%6 lecture hrs | Balancedexam 6% · syllabus 11% | Steady | 2 recurring2 total | |
| 5 | U1Introduction | Occasional29% | 5 | 13%7 lecture hrs | Under-examinedexam 2% · syllabus 13% | Rising | 1 recurring1 total | |
| 6 | U2Principles of Parallel and Distributed Computing | Occasional0% | 0 | 15%8 lecture hrs | Under-examinedexam 0% · syllabus 15% | Steady | None | |
| 7 | U5Aneka, Cloud Application Platform | Occasional0% | 0 | 11%6 lecture hrs | Under-examinedexam 0% · syllabus 11% | Steady | None | |
| 8 | U8Advanced Topics in Cloud Computing | Occasional0% | 0 | 7%4 lecture hrs | Under-examinedexam 0% · syllabus 7% | Steady | None |
Study smart, not hard
Drag the slider: studying the top 3 units in priority order covers ~92% of all observed marks.
- ~80% line
Lecture time vs exam marks
Where the exam pays more than the curriculum spends: ● lectures vs ● exam marks, as a share of the whole course. A long teal-leading bar = high-yield unit.