Unit 3: Cloud storage and advanced topics
Cloud Computing notes · PTU syllabus (PGCA1937)
On this page
- Unit summary
- Provisioning cloud storage
- Virtual storage containers
- Cloud storage interoperability: CDMI and OCCI
- Database storage and resource management
- Energy efficiency in the cloud
- Market-oriented cloud computing
- Federated cloud computing
- Mobile cloud computing
- Fog computing
- Big data analytics and IoT basics
- Key terms
- Quick revision
- Important questions
Unit summary
Storage and resources are the heart of cloud services, and new models extend the cloud to markets, federations, mobiles and the edge. This unit covers provisioning cloud storage, virtual storage containers, interoperability with CDMI and OCCI, database storage and resource management, energy efficiency, market-oriented and federated clouds, mobile cloud computing, fog computing, and the basics of big data analytics and IoT.
After this unit you can
- Provision cloud storage and explain its interoperability standards
- Explain database storage, resource management and energy efficiency
- Explain market-oriented and federated cloud computing
- Explain mobile cloud, fog computing, big data and IoT
PTU syllabus topics
- Provisioning cloud storage
- virtual storage containers
- cloud storage interoperability (CDMI, OCCI)
- database storage and resource management
- energy efficiency
- market-oriented and federated cloud computing
- mobile cloud computing
- fog computing
- big data analytics and IoT basics
Cloud
Central data centres
Heavy analytics, storage
Fog
Local gateways near devices
Aggregating IoT data
Edge
On the device itself
Ultra-low latency
Topic 1
Provisioning cloud storage
Object storage
Objects with metadata in buckets, accessed over HTTP APIs; highly scalable
Amazon S3, Azure Blob, Google Cloud Storage
Block storage
Raw volumes attached to virtual machines
Amazon EBS, Azure Disks
File storage
Shared file systems over NFS or SMB
Amazon EFS, Azure Files
Archive storage
Cheap, slow-retrieval cold storage
S3 Glacier, Azure Archive
- Provisioning: choose type, region, capacity and performance tier; set access policies, encryption, versioning and lifecycle rules; storage grows automatically for object storage.
Topic 2
Virtual storage containers
- A virtual storage container is a logical unit of storage — a bucket, container or volume — that hides the physical devices behind it. Containers carry their own access controls, quotas, metadata and lifecycle policies, and can be replicated across zones or regions.
Topic 3
Cloud storage interoperability: CDMI and OCCI
Full form
Cloud Data Management Interface
Open Cloud Computing Interface
Body
SNIA (Storage Networking Industry Association); also ISO/IEC 17826
Open Grid Forum
Scope
Standard RESTful interface to create, read, update and delete data in cloud storage, with metadata and containers
RESTful API to manage IaaS resources — compute, storage, network
Goal
Move data between storage providers without lock-in
Manage infrastructure across clouds with one API
- In practice, the Amazon S3 API has become a de facto standard that many storage systems implement.
Topic 4
Database storage and resource management
Relational (DBaaS)
Managed SQL databases with automated backups, patching and scaling
Amazon RDS, Azure SQL Database, Cloud SQL
NoSQL
Key-value, document, wide-column or graph stores scaling horizontally
DynamoDB, Cosmos DB, Bigtable
Data warehouse
Columnar analytics stores
Redshift, BigQuery, Synapse
- Resource management: scheduling and allocating VMs, storage and bandwidth among tenants — admission control, load balancing, VM placement and consolidation, live migration — to meet SLAs at minimum cost.
Topic 5
Energy efficiency in the cloud
- Data centres consume large amounts of electricity for servers and cooling.
PUE
Total facility energy ÷ IT equipment energy
Ideal
1.0 (all energy used by IT equipment)
Example
1,500 kWh total for 1,200 kWh IT load → PUE 1.25
- Techniques: VM consolidation and switching off idle servers, dynamic voltage and frequency scaling, efficient cooling (free air, liquid cooling), renewable energy, and carbon-aware scheduling.
Topic 6
Market-oriented cloud computing
- Resources are traded like commodities: providers set prices and customers choose based on cost and quality of service, often through brokers and exchanges.
- Pricing models
- On-demand, reserved, spot (auction-like spare capacity), savings plans
- SLA-based admission
- Accept requests only if SLAs can be met
- Brokers
- Select the best provider for each request
- Accounting and billing
- Metering and charging
- Market exchange
- Matching buyers and sellers of resources
Topic 7
Federated cloud computing
- A federated cloud (inter-cloud) links several providers' clouds so workloads and data can move among them — for capacity bursting, geographic reach, resilience or compliance.
- 1Local cloud reaches capacity
- 2Federation broker finds partner clouds with free resources
- 3SLA and pricing are agreed
- 4Workload is deployed or migrated
- 5Usage is metered and settled
- Challenges: interoperable APIs, identity federation, data movement costs, consistent security policies. Multi-cloud management tools and Kubernetes ease portability.
Topic 8
Mobile cloud computing
- Mobile apps offload storage and processing to the cloud — sync, backup, streaming, AI features.
- Benefits: extends battery and storage, access anywhere, easy updates. Issues: latency, connectivity, data costs, privacy — edge computing processes data closer to users.
Topic 9
Fog computing
- Fog computing extends cloud services to the network edge — gateways, routers and local servers — so data from devices is processed nearby before (or instead of) going to the cloud.
Cloud
Central data centres
Massive storage and analytics
Fog
Local network nodes between devices and cloud
Low latency, local aggregation, bandwidth saving
Edge
On or next to the device
Instant response, offline operation
Example
A smart traffic system processes camera feeds at roadside fog nodes to change signals in milliseconds, sending only summary statistics to the cloud.
Topic 10
Big data analytics and IoT basics
- Five Vs of big data
- Volume, velocity, variety, veracity, value
- Cloud big data services
- Hadoop and Spark clusters (EMR, Dataproc, HDInsight), data lakes, serverless analytics
- IoT
- Sensors and devices connected to the internet producing data streams
- Cloud IoT platforms
- Device registry, messaging (MQTT), rules, analytics — AWS IoT Core, Azure IoT Hub
- Combined flow
- Devices → fog gateway → cloud ingestion → storage → analytics and dashboards
Key terms
- Object storage
- Storage of data as objects with metadata in buckets
- CDMI
- SNIA standard interface for cloud data management
- PUE
- Ratio of total facility energy to IT energy
- Federated cloud
- Interconnected clouds sharing resources
- Fog computing
- Processing at network nodes between devices and the cloud
Quick revision
- Object, block, file and archive storage; provisioning; virtual storage containers.
- CDMI (SNIA) for data; OCCI (OGF) for infrastructure; S3 API.
- DBaaS, NoSQL, warehouses; resource management.
- PUE and green techniques; market-oriented pricing; federation.
- Mobile cloud; fog vs edge vs cloud; big data Vs; cloud IoT platforms.
Important exam questions
Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).
Short-answer questions
- Q1.Distinguish object and block storage.
- Q2.What is CDMI?
- Q3.What does OCCI standardise?
- Q4.Calculate PUE for 2,000 kWh total and 1,600 kWh IT load.
- Q5.What is a spot instance?
- Q6.Distinguish fog and edge computing.
Long-answer questions
- Q1.Explain provisioning of cloud storage and interoperability standards.
- Q2.Explain database storage, resource management and energy efficiency in the cloud.
- Q3.Explain market-oriented and federated cloud computing.
- Q4.Explain mobile cloud computing, fog computing and cloud support for big data and IoT.
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