Cloud Computing (CS-802 (B)) Unit 5 Notes

How unit 5 is examined

This unit covers the problems and platform-level topics of cloud computing; QoS, data migration, mobile cloud, inter-cloud, sky computing, monitoring and platform features carry the marks, and every 7-mark question is a plain "explain".

Issues in cloud computing

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Definition. Cloud issues are the technical, security and management problems that reduce the performance, trust or portability of cloud services.

Key points.

Security and data privacy: data sits on shared infrastructure owned by a provider, so breaches, insider access and weak isolation are the biggest worries.
Vendor lock-in and compliance: proprietary APIs make leaving a provider costly, and laws on data location restrict where data may be stored.
Latency, bandwidth limits and cost management: remote data centres add delay, and unmonitored resources inflate the bill.
Performance improvement: use a CDN, spread data centres geographically, apply load balancing, caching and auto-scaling, place VMs wisely, use containers, and keep monitoring and tuning.

Asked: [? marks] (May 2024) What are the issues in cloud computing? How to improve the performance of cloud platforms?

Implementing real time application

Definition. A real-time cloud application must process and answer data within a strict time limit, so the cloud must give low latency and elastic capacity.

Key points.

Stream processing engines and messaging queues (Kafka, Kinesis, Pub/Sub) ingest events and process them as they arrive, not in batches.
Edge integration moves computation close to the device, which cuts round-trip delay.
Auto-scaling adds servers during load spikes so response time stays within the deadline.
Use cases are IoT sensor monitoring, stock trading and online gaming, supported by real-time analytics services.

Asked: [7 marks] (Jun 2025) Explain how cloud computing is used for real-time applications.

QoS issues in cloud

Definition. Quality of Service (QoS) is the measurable level of performance, availability and reliability a provider promises, and it is written into the Service Level Agreement (SLA).

<mark>QoS is the guaranteed level of response time, throughput, latency and availability that a cloud provider commits to in the SLA, and its issues are the factors that make it hard to keep.</mark>

Key points.

QoS matters because the SLA is a contract: a missed target means penalties for the provider and lost users for the customer.
Response time is the time from request to first reply, and throughput is the number of requests served per unit time; heavy load lowers throughput and raises response time.
Latency is the network delay between user and data centre; distance, congestion and limited bandwidth increase it.
Availability is the percentage of time the service is up, $\text{Availability} = \frac{MTBF}{MTBF+MTTR}\times 100$; 99.9% allows about 8.76 hours of downtime a year.
Performance variability arises from multi-tenancy, since neighbouring tenants compete for the same CPU, disk and network.
Reliability, provisioning delays and weak monitoring make it hard to prove SLA compliance.
Trade-offs exist: higher availability needs redundancy (more cost), and higher throughput can raise latency.
Management approaches are auto-scaling, load balancing, replication across zones, resource reservation and continuous SLA monitoring.

Answer frame. Open with the QoS and SLA definition; draw a small table of parameters (response time, throughput, latency, availability) with meaning and cause of degradation; develop points 2-5 as the parameters, then 5-6 as issues; close with management approaches and the trade-off line.

Asked: [7 marks] (May 2022, May 2023) Discuss QoS issues in cloud computing. Why is QoS important? List the issues of QoS and explain. Asked: [7 marks] (May 2026) Analyze various QoS parameters including response time, throughput, latency and availability in cloud environments.

Dependability

Definition. Dependability is the trustworthiness of a cloud service, meaning it keeps delivering correct service despite faults.

Key points.

Its attributes are reliability, availability, safety, integrity and maintainability.
Fault tolerance through replication, checkpointing and failover raises dependability.
Reliability is measured by MTBF, and availability by $\frac{MTBF}{MTBF+MTTR}$.
Backups and multi-zone deployment protect against data-centre failure.

Data migration

Definition. Data migration is the process of moving data, applications and workloads from on-premises systems (or one cloud) to a cloud (or another cloud) with minimum disruption.

<mark>Data migration in the cloud is the planned transfer of data and applications to the cloud, and its main challenges are downtime, data loss, compatibility, bandwidth, security and cost.</mark>

Key points.

Types are storage migration, database migration, application migration and cloud-to-cloud migration.
Phases are assessment and planning, data preparation and cleansing, transfer, validation and testing, and cut-over.
Downtime and data loss are the main risks, since the source system may change or fail during transfer.
Compatibility problems arise from different formats, schemas and APIs between source and target.
Bandwidth limits make large transfers slow, so bulk devices such as AWS Snowball are used.
Security, compliance and cost issues include exposing data in transit and paying transfer and dual-running charges.
Techniques are lift-and-shift (move as is), replication (continuous copy until cut-over), phased migration (move in stages) and live migration (move running workloads without stopping them).
Tools include AWS Database Migration Service, Azure Migrate and Google Transfer Service; enterprises with many sites use phased migration and replication to keep downtime near zero.

Answer frame. Open with the definition; draw the phase flow as a table or line (plan, prepare, transfer, validate, cut-over); develop points 3-6 for challenges questions, or 7-8 for techniques questions; close with the mitigation line (encryption, backups, phased cut-over).

Asked: [7 marks] (Jun 2025) Discuss the challenges associated with data migration in cloud computing. Asked: [7 marks] (May 2026) Describe data migration techniques in cloud computing and explain their applications in distributed enterprise environments. Asked: [7 marks] (May 2022) Write brief notes: Sky computing; Data migration. Asked: [7 marks] (Dec 2024) Write short notes (any two): Sky computing; Cloud middleware; Data migration.

Streaming in cloud

Definition. Cloud streaming delivers continuous data such as video, audio or events to users as it is produced, without waiting for the full file.

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Key points.

Ingestion collects the live or stored stream into cloud storage or a message queue.
Processing transcodes the stream into several bit rates so each device gets a suitable quality.
Delivery uses a CDN, which caches content on edge servers close to viewers to cut latency.
The cloud scales servers up with audience size, and examples are video on demand, live broadcasts and music.

Asked: [7 marks] (Jun 2025) How does streaming technology work in cloud-based applications?

Cloud middleware

Definition. Cloud middleware is the software layer between cloud infrastructure and applications that lets services communicate and be coordinated.

Key points.

It hides differences in hardware and platforms, giving applications one abstraction.
It provides resource management, service discovery, messaging and integration.
Examples are message queues, application servers and API gateways.
It reduces development effort and helps portability between clouds.

Asked: [? marks] (May 2024) What is cloud middleware? What is the importance of sky computing? Asked: [7 marks] (Dec 2024) Write short notes (any two): Sky computing; Cloud middleware; Data migration.

Mobile cloud computing

Definition. Mobile cloud computing (MCC) uses cloud storage and processing to run mobile applications, offloading heavy work from resource-limited phones to the cloud.

<mark>The purpose of mobile cloud computing is to overcome the limited battery, processing power and storage of mobile devices by offloading computation and data to the cloud.</mark>

Key points.

Purpose: extend cloud capability to mobile devices so that a small phone can run demanding applications.
Computation offloading sends heavy tasks to the cloud, which saves battery and speeds up execution.
Storage offloading keeps data in the cloud, giving ubiquitous access from any device.
Elasticity and context awareness let the service scale and adapt to location, network and device state.
Device shortcomings are limited battery, CPU and storage, plus intermittent connectivity and variable bandwidth.
Distance-cloud shortcomings are high latency because of geographic distance, more network traffic and energy use for communication, poor QoS for real-time applications, and security and privacy risk from remote storage.
Architecture has mobile devices, a network (3G/4G/Wi-Fi) through a base station, and cloud servers that serve requests.

Answer frame. Open with the MCC definition and purpose; draw the mobile - network - cloud block figure; develop points 2-4 as features and benefits; close with challenges (points 5-6) and the note that nearby cloudlets reduce distance latency.

Asked: [7 marks] (May 2023) What is the purpose of mobile cloud computing? Explain its features. Asked: [? marks] (May 2024) Describe the shortcomings of mobile device and distance clouds for mobile cloud computing.

Inter cloud issues

Definition. Inter-cloud (federated cloud) is the interconnection of several independent clouds so that they can share and exchange resources and workloads.

<mark>Inter-cloud issues are the interoperability, portability, security, governance and lock-in problems that arise when workloads span clouds of different providers.</mark>

Key points.

Interoperability: providers use different APIs, formats and standards, so clouds cannot talk to each other easily.
Portability: moving data and VMs between clouds is hard because of incompatible images, storage models and large data volumes.
Security and compliance: identities, encryption and data-location laws differ between providers, which widens the attack surface.
Vendor lock-in: proprietary services make switching expensive, so standards such as OVF and open APIs are needed.
SLA and governance: each cloud gives a separate SLA, so end-to-end guarantees, billing and responsibility are unclear.
Management complexity: monitoring, load balancing and resource scheduling across clouds needs a common broker layer.

Answer frame. Open with the inter-cloud definition; develop points 1-6 in order, one sentence each with a mitigation; close with the role of standards and brokers. For the May 2024 combined question, add the platform functions listed under Features and functions.

Asked: [7 marks] (Jun 2025) What are the major inter-cloud issues faced by enterprises? Asked: [? marks] (May 2024) What are the inter cloud issues? Describe functions of cloud platforms.

A grid of clouds, Sky computing

Definition. Sky computing is an interoperation layer that lets an application use resources from many cloud providers at once, so several clouds behave like one; a grid of clouds is the same idea of clouds joined into a grid.

<mark>Sky computing is a multi-cloud environment in which a broker layer combines resources from several independent providers into one virtual, provider-neutral cloud.</mark>

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Key points.

A broker or middleware layer hides each provider's API and places the workload on the best cloud.
It avoids vendor lock-in, since the application is not tied to one provider.
It enables load balancing and fault tolerance, because work can move to another cloud when one fails or is overloaded.
It lowers cost by choosing the cheapest or best service from each provider.
Challenges are incompatible APIs, network and security setup across clouds, and data movement cost.

Basis	Traditional cloud	Sky computing
Providers	Single provider	Many providers
Lock-in	High	Avoided
Fault tolerance	Limited to one provider	Fails over to another cloud
Cost choice	Fixed provider pricing	Best price across clouds
Management	Provider's own tools	Broker layer over all
Complexity	Low	Higher

Answer frame. Open with the definition; draw the broker figure; for the comparison question give the table then benefits (points 2-4); for importance questions list points 2-4, and close with challenges.

Asked: [7 marks] (May 2022) Write brief notes: Sky computing; Data migration. Asked: [7 marks] (Jun 2025) What is Sky computing? How is it different from traditional cloud computing? Asked: [? marks] (May 2024) What is cloud middleware? What is the importance of sky computing?

Load balancing

Definition. Load balancing distributes incoming requests across several servers so that none is overloaded and resources are used evenly.

Key points.

A load balancer (hardware, software or DNS-based) sits in front of the servers and forwards each request.
Algorithms include round robin, least connections, weighted and IP hash.
Health checks remove failed servers automatically, which improves availability.
Auto-scaling adds or removes servers with demand, and scheduling places tasks on the least loaded node.

Asked: [7 marks] (Dec 2024) How does a cloud environment balance the work load?

Resource optimization

Definition. Resource optimization is using the fewest cloud resources that still meet performance targets, so utilization rises and cost falls.

Key points.

Round robin and least-connection balancing spread load evenly, and auto-scaling matches capacity to demand.
Case study: an online shop runs 10 servers at 20% CPU; with load balancing and auto-scaling it runs 4 servers at about 50% CPU and scales to 8 on sale days, so cost falls by more than half with the same response time.
The outcome is higher utilization, lower cost and better SLA compliance.

Asked: [7 marks] (Jun 2025) Provide a case study on cloud resource optimization and load balancing techniques.

Resource dynamic reconfiguration

Definition. Dynamic reconfiguration is changing the resources allocated to running workloads at run time, without stopping the service.

Key points.

Auto-scaling adds or removes VMs and resizes CPU and memory as demand changes.
Live migration moves a running VM to another host, so overloaded or failing hosts can be relieved without downtime.
Resource reallocation shifts idle capacity to busy applications.
Impact: higher utilization, lower cost, better performance and SLA compliance.

Asked: [7 marks] (Jun 2025) Discuss resource dynamic reconfiguration and its impact on cloud efficiency.

Monitoring in cloud

Definition. Cloud monitoring is the continuous collection and analysis of metrics, logs and traces from resources and applications to check health, performance and SLA compliance.

<mark>Cloud monitoring continuously measures metrics, logs and traces so that bottlenecks and faults are detected early and capacity is adjusted automatically to keep performance optimal.</mark>

Key points.

Metrics such as CPU use, memory, disk, network, response time and error rate show the state of each resource.
Mechanisms are agent-based (software inside the VM), hypervisor-level (no agent needed) and SLA monitoring (checks the promised targets).
Dashboards and analysis expose bottlenecks and anomalies before users notice them.
Alerts notify administrators, and thresholds trigger auto-scaling to add or remove capacity.
Fault management uses logs and traces to find the failing component and trigger recovery.
SLA assurance uses the data as proof of availability and as a basis for billing.
Continuous feedback lets the provider tune resources and improve performance.
Tools are Amazon CloudWatch, Azure Monitor, Google Cloud Monitoring and Nagios.

Answer frame. Open with the definition; draw a loop of resources - monitor - analysis - alert/auto-scale; develop points 1-6 in order; close with continuous optimization. For the mechanisms question stress points 2, 5 and 8.

Asked: [7 marks] (Jun 2025, May 2026) How does monitoring in cloud computing help in ensuring optimal performance? Examine monitoring mechanisms used in cloud systems and their applications in performance evaluation and fault management.

Installing cloud platforms and performance evaluation

Definition. Installing a cloud platform means deploying cloud management software such as OpenStack or Eucalyptus on servers, and performance evaluation measures how well it runs.

Key points.

Installation covers preparing hardware, installing the hypervisor and the controller, and configuring networking and storage.
Performance is evaluated using benchmarks and monitoring of response time, throughput, utilization and scalability.
Results are compared against SLA targets, and bottlenecks are then tuned.

Features and functions of cloud computing platforms

Definition. A cloud computing platform is the software and infrastructure that provides on-demand computing, storage and networking as services.

<mark>A cloud platform provides virtualization, scalability and service models, and its functions are provisioning, storage, networking, monitoring and security.</mark>

Key points.

Features: virtualization, elastic scalability, pay-per-use billing, multi-tenancy and IaaS/PaaS/SaaS service models.
Functions: resource provisioning, storage management, networking, load balancing, auto-scaling, billing, monitoring, security, disaster recovery and SLA enforcement.
Google App Engine is a PaaS: it runs applications in Google's data centres with automatic scaling, so the developer manages no servers.
App Engine features are auto-scaling with load balancing, a Datastore (NoSQL) for storage, versioning of applications with traffic splitting, and runtimes such as Python, Java, Go and PHP.
App Engine provides APIs for Datastore, Memcache, URL fetch, mail, task queues and user authentication; applications run in a sandbox, and billing is per use.

Layer	AWS	Azure	Google Cloud
IaaS	EC2, S3	Virtual Machines, Blob Storage	Compute Engine, Cloud Storage
PaaS	Elastic Beanstalk, Lambda	App Service, Functions	App Engine, Cloud Functions
SaaS	WorkMail, Chime	Office 365	Google Workspace, Gmail

Salesforce is also a SaaS example.

Answer frame. Open with the platform definition; for the App Engine question start with points 3-5, and for the general question give points 1-2; use the layer table for the offerings question; close with the benefit of no infrastructure management.

Asked: [7 marks] (May 2022) Describe the major cloud features of Google App Engine. Explain features and functions of cloud computing platforms. Asked: [? marks] (May 2024) Briefly list the representative cloud service offerings at each cloud layer from the major cloud providers.

Last-minute revision

QoS = guaranteed response time, throughput, latency and availability, fixed in the SLA.
Availability = MTBF / (MTBF + MTTR); 99.9% is about 8.76 hours downtime a year.
Data migration phases: plan, prepare, transfer, validate, cut-over.
Migration techniques: lift-and-shift, replication, phased, live migration.
Sky computing = broker layer over many clouds; avoids lock-in, adds fault tolerance and cost choice.
Inter-cloud issues: interoperability, portability, security, lock-in, SLA governance.
MCC offloads computation and storage from phones to save battery; distance clouds add latency.
Load balancing algorithms: round robin, least connections, weighted, IP hash.
Live migration moves a running VM with no downtime.
Monitoring tools: CloudWatch, Azure Monitor, Nagios; agent-based, hypervisor-level, SLA monitoring.
Google App Engine: PaaS with auto-scaling, Datastore, versioning.

Memory hooks

QoS parameters: R-T-L-A (Response, Throughput, Latency, Availability).
Inter-cloud issues: I-P-S-L (Interoperability, Portability, Security, Lock-in).
Sky = "sky over the clouds", a broker on top.
Migration techniques: L-R-P-L (Lift, Replicate, Phase, Live).
Streaming path: Ingest, Process, Deliver via CDN.

Coverage checklist

Issues in cloud computing: May 2024 issues and performance question.
implementing real time application: Jun 2025 real-time question.
QOS Issues in Cloud: May 2022, May 2023, May 2026 questions.
Dependability: not asked, covered.
data migration: Jun 2025, May 2026, May 2022 note, Dec 2024 note.
streaming in Cloud: Jun 2025 question.
Cloud Middleware: May 2024 and Dec 2024 questions.
Mobile Cloud Computing: May 2023, May 2024 questions.
Inter Cloud issues: Jun 2025, May 2024 questions.
A grid of clouds, Sky computing: May 2022, Jun 2025, May 2024, Dec 2024 questions.
load balancing: Dec 2024 question.
Resource optimization: Jun 2025 case study.
Resource dynamic reconfiguration: Jun 2025 question.
Monitoring in Cloud: Jun 2025, May 2026 questions.
Installing cloud platforms and performance evaluation: not asked, covered.
Features and functions of cloud computing platforms: May 2022, May 2024 questions.

Account

Cloud Computing (CS-802 (B)) - Unit 5 Short Notes

How unit 5 is examined

Issues in cloud computing

Implementing real time application

QoS issues in cloud

Dependability

Data migration

Streaming in cloud

Cloud middleware

Mobile cloud computing

Inter cloud issues

A grid of clouds, Sky computing

Load balancing

Resource optimization

Resource dynamic reconfiguration

Monitoring in cloud

Installing cloud platforms and performance evaluation

Features and functions of cloud computing platforms

Last-minute revision

Memory hooks

Coverage checklist