The document discusses cloud economics and cost modeling. It notes that while cloud is often viewed as pay-as-you-go, the reality is that customers pay for what they provision, not just what they use. Utilization rates for physical, virtualized, and cloud infrastructure are typically around 30%, meaning costs can be optimized through rightsizing capacity. Myths around cloud being cheap, easier to migrate to, and fully managed are debunked. Resources for understanding cloud costs and models are provided.
The document describes a Semantic Post-It system that maps personal messages into an organized personal information space using ontologies and collective intelligence from sources like Wikipedia. It allows users to edit personal ontologies on their mobile devices and view relevant information extracted from messages in graph and table formats. Technologies discussed that enable the system include ontology construction from text and Wikipedia, information extraction using ontologies, and reducing the cost of ontology development and annotation.
The document discusses how semantic navigation can help improve search experiences on websites. It notes that search engines often struggle with vague keywords and must balance precision and recall. Semantic data can help drive site navigation, identify entities to use as search facets, smooth differences in categories and tags, and understand user context. Using semantic navigation can improve SEO, time spent on sites, and conversion rates. It provides an example of one company that saw a 22% increase in search usage, 25% more time spent, and greater drilling down after implementing semantic navigation technologies.
Semantic Technologies for Enterprise Cloud ManagementPeter Haase
This document discusses managing enterprise clouds through semantic technologies. It presents a vision of fully automated data center management from a single intuitive console. Key challenges include integrating heterogeneous IT resource data and enabling collaborative documentation. The proposed solution applies a semantic data model, wiki for documentation, and a flexible living user interface. Widgets, search, and visual analytics tools provide tailored access and insights. Experience shows semantic technologies scale well and the approach is highly reusable across domains.
The GAO report assessed the progress of 7 federal agencies in implementing the federal "Cloud First" policy. The agencies have made progress by incorporating cloud requirements into policies and processes and meeting deadlines to identify and implement cloud services. However, 2 agencies may not meet the June 2012 deadline and agency plans were missing key elements like estimated costs. The report also identified 7 common challenges agencies faced in implementing cloud computing, such as meeting security requirements and obtaining guidance. It concludes better upfront planning is needed for future cloud efforts to fully realize expected benefits of improved efficiencies and reduced costs.
The document discusses several initiatives related to cloud computing, open data, and semantic technologies in the federal government. It outlines the White House's cloud computing initiative through Apps.gov to help agencies quickly purchase cloud services. It also discusses the evolution of the federal enterprise architecture to incorporate semantic interoperability patterns and open linked data. Finally, it notes that Data.gov plans to provide guidance to help agencies semantically mark up their datasets so they can be better leveraged.
The document discusses the challenges of scale and complexity in modern systems and how semantic technologies can help provide governance. It proposes using a semantic governance repository with services, policies, taxonomies, and machine learning to classify and search services. Event processing and business rules would monitor for situations while semantic search allows discovery. The goal is an open source platform leveraging existing components to enable semantic intelligence for cloud enterprises.
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS Web image re ranking using query-sp...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
The document describes a Semantic Post-It system that maps personal messages into an organized personal information space using ontologies and collective intelligence from sources like Wikipedia. It allows users to edit personal ontologies on their mobile devices and view relevant information extracted from messages in graph and table formats. Technologies discussed that enable the system include ontology construction from text and Wikipedia, information extraction using ontologies, and reducing the cost of ontology development and annotation.
The document discusses how semantic navigation can help improve search experiences on websites. It notes that search engines often struggle with vague keywords and must balance precision and recall. Semantic data can help drive site navigation, identify entities to use as search facets, smooth differences in categories and tags, and understand user context. Using semantic navigation can improve SEO, time spent on sites, and conversion rates. It provides an example of one company that saw a 22% increase in search usage, 25% more time spent, and greater drilling down after implementing semantic navigation technologies.
Semantic Technologies for Enterprise Cloud ManagementPeter Haase
This document discusses managing enterprise clouds through semantic technologies. It presents a vision of fully automated data center management from a single intuitive console. Key challenges include integrating heterogeneous IT resource data and enabling collaborative documentation. The proposed solution applies a semantic data model, wiki for documentation, and a flexible living user interface. Widgets, search, and visual analytics tools provide tailored access and insights. Experience shows semantic technologies scale well and the approach is highly reusable across domains.
The GAO report assessed the progress of 7 federal agencies in implementing the federal "Cloud First" policy. The agencies have made progress by incorporating cloud requirements into policies and processes and meeting deadlines to identify and implement cloud services. However, 2 agencies may not meet the June 2012 deadline and agency plans were missing key elements like estimated costs. The report also identified 7 common challenges agencies faced in implementing cloud computing, such as meeting security requirements and obtaining guidance. It concludes better upfront planning is needed for future cloud efforts to fully realize expected benefits of improved efficiencies and reduced costs.
The document discusses several initiatives related to cloud computing, open data, and semantic technologies in the federal government. It outlines the White House's cloud computing initiative through Apps.gov to help agencies quickly purchase cloud services. It also discusses the evolution of the federal enterprise architecture to incorporate semantic interoperability patterns and open linked data. Finally, it notes that Data.gov plans to provide guidance to help agencies semantically mark up their datasets so they can be better leveraged.
The document discusses the challenges of scale and complexity in modern systems and how semantic technologies can help provide governance. It proposes using a semantic governance repository with services, policies, taxonomies, and machine learning to classify and search services. Event processing and business rules would monitor for situations while semantic search allows discovery. The goal is an open source platform leveraging existing components to enable semantic intelligence for cloud enterprises.
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS Web image re ranking using query-sp...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
The document discusses automated planning and its applications. It provides examples of planning systems used for space exploration missions, games, manufacturing, and cloud computing. Hierarchical planning is described as an approach that provides a hierarchy of actions and goals to guide the planning process. The case study focuses on using Elastra Enterprise Cloud Server to automatically configure, deploy, and scale applications across hybrid cloud environments through hierarchical planning and orchestration.
Presented by Roberto Masiero, Vice President ADP Innovation Lab, ADP
In this presentation we will cover ADP's Semantic Search strategy and implementation. From the use cases to the design to support semantic searches on a vast set of data, to crawling data from hundreds of data sources. We will also cover our architecture to scale the search service on a multi-tenant SaaS environment.
IoT Day 2016: Cloud Services for IoT Semantic InteroperabilityMark Underwood
Presentation made on IoT Day 2016 about the importance of API-first, cloud services role in implementing ontologies for IoT. The use case is homely: providing proper humidity to my electric violin and guitar instruments while in their cases.
Cloud IT Economics: What you don't know about TCO can hurt youAl Brodie
An e-book that explores factors beyond basic price that impact the true cost of ownership for cloud implementations by comparing and contrasting prevalent approaches, using common enterprise workloads, from three prominent cloud service providers.
Introduction to Enterprise Cloud EconomicsEverest Group
Everest Group experts will disucss the transformational impact emerging cloud models can have on IT cost and performance in the enterprise. This webinar will focus on the specific enterprise benefits of cloud infrastructure services, including compute, storage and networking.
Stuart Robertson
Manager, Global Alliances at CTP, takes us through cloud economics and the thought process and analysis for building a business case for cloud adoption. He shows a high level methodology for building an economic model and developing a business case, and concludes with lessons learned and best practices that CTP uses in its approach with FSI customers.
This document introduces COSBench, a benchmark tool developed by Intel to measure the performance of cloud object storage services. It describes key components of COSBench including the workload configuration, performance metrics collected, and a web console for managing tests. The document also provides a case study using COSBench to evaluate the performance of OpenStack Swift, an open source cloud storage system, by describing the entities and architecture of OpenStack Swift and the test configuration used.
Scaling a database eventually brings you to the limits of your database engine’s capabilities. Many database users solve this with sharding, but that adds a new layer of management complexity. In this session, we’ll see how a single, scalable Amazon Aurora database can consolidate multiple shards in a scalable, cost-effective way. We’ll see a demo of a sharded system migration to Aurora using AWS Database Migration Service.
The Zeus Volt tablet can function as a taser or electric car charger for self-defense or charging electric vehicles. It targets teenagers, college students, and some professionals. It has several advanced features like a holographic recorder and projector. Plan options range from $10.99-30.99 per month for the Zeus Volt and $14.99-85 per month for the iPad and Galaxy Tab, with data allowances and repair coverage varying with the plan.
Tape storage remains a highly cost effective solution for backup and archival storage despite perceptions that it is outdated. Recent developments show continued improvements in tape technology with areal density demonstrations of 29.5 Gbit/in2 and LTO roadmaps extending to 12.8 TB capacities. The Long Term File System also allows tapes to be accessed like removable drives, opening new use cases. Together these advances ensure tape storage will continue to be relevant for the next decade.
The document discusses automated planning and its applications. It provides examples of planning systems used for space exploration missions, games, manufacturing, and cloud computing. Hierarchical planning is described as an approach that provides a hierarchy of actions and goals to guide the planning process. The case study focuses on using Elastra Enterprise Cloud Server to automatically configure, deploy, and scale applications across hybrid cloud environments through hierarchical planning and orchestration.
Presented by Roberto Masiero, Vice President ADP Innovation Lab, ADP
In this presentation we will cover ADP's Semantic Search strategy and implementation. From the use cases to the design to support semantic searches on a vast set of data, to crawling data from hundreds of data sources. We will also cover our architecture to scale the search service on a multi-tenant SaaS environment.
IoT Day 2016: Cloud Services for IoT Semantic InteroperabilityMark Underwood
Presentation made on IoT Day 2016 about the importance of API-first, cloud services role in implementing ontologies for IoT. The use case is homely: providing proper humidity to my electric violin and guitar instruments while in their cases.
Cloud IT Economics: What you don't know about TCO can hurt youAl Brodie
An e-book that explores factors beyond basic price that impact the true cost of ownership for cloud implementations by comparing and contrasting prevalent approaches, using common enterprise workloads, from three prominent cloud service providers.
Introduction to Enterprise Cloud EconomicsEverest Group
Everest Group experts will disucss the transformational impact emerging cloud models can have on IT cost and performance in the enterprise. This webinar will focus on the specific enterprise benefits of cloud infrastructure services, including compute, storage and networking.
Stuart Robertson
Manager, Global Alliances at CTP, takes us through cloud economics and the thought process and analysis for building a business case for cloud adoption. He shows a high level methodology for building an economic model and developing a business case, and concludes with lessons learned and best practices that CTP uses in its approach with FSI customers.
This document introduces COSBench, a benchmark tool developed by Intel to measure the performance of cloud object storage services. It describes key components of COSBench including the workload configuration, performance metrics collected, and a web console for managing tests. The document also provides a case study using COSBench to evaluate the performance of OpenStack Swift, an open source cloud storage system, by describing the entities and architecture of OpenStack Swift and the test configuration used.
Scaling a database eventually brings you to the limits of your database engine’s capabilities. Many database users solve this with sharding, but that adds a new layer of management complexity. In this session, we’ll see how a single, scalable Amazon Aurora database can consolidate multiple shards in a scalable, cost-effective way. We’ll see a demo of a sharded system migration to Aurora using AWS Database Migration Service.
The Zeus Volt tablet can function as a taser or electric car charger for self-defense or charging electric vehicles. It targets teenagers, college students, and some professionals. It has several advanced features like a holographic recorder and projector. Plan options range from $10.99-30.99 per month for the Zeus Volt and $14.99-85 per month for the iPad and Galaxy Tab, with data allowances and repair coverage varying with the plan.
Tape storage remains a highly cost effective solution for backup and archival storage despite perceptions that it is outdated. Recent developments show continued improvements in tape technology with areal density demonstrations of 29.5 Gbit/in2 and LTO roadmaps extending to 12.8 TB capacities. The Long Term File System also allows tapes to be accessed like removable drives, opening new use cases. Together these advances ensure tape storage will continue to be relevant for the next decade.
2. About Me
Cloud and Enterprise IT Entrepreneur
CEO, CloudVertical - “Reducing IT Waste”
Previously GM, Hosting365 (now SunGard)
@edbyrne
www.edbyrne.me
blog.cloudvertical.com
3. Agenda
What is Cloud Economics
The Myths of Cloud Computing
Variables and Cost Models
Resources
4. Principles of Cloud Economics
IT as a Utility - Available and Scalable
IT is Paid for using a Consumption based model
Theoretically 100% capital efficient
5. IT Cost Model
Capacity is CapEx and Cyclically Driven
Usage follows predictable patterns
Cost increases with time and complexity
6. Cloud Cost Model (Theory)
Capacity scales up and down in line with demand
Usage follows predictable patterns (no change)
Cost matches capacity - pay as you consume
7. IT Cloud Cost Model (Actual)
Capacity is provisioned based on expected load
Usage follows predictable patterns
Cost goes up and to the right, with an **** moment
8. Cloud Economics Reality
The Cloud is not analogous to the Electricity model.
The Cloud is not Pay as You Go. It’s Pay as You Provision.
Utilisation is the problem -> the traditional capacity planning
model has migrated to the Cloud.
• Physical Hardware - 20% Utilisation Average
• Virtualised Infrastructure - 30% Utilisation Average
• Cloud Deployments - 30% Utilisation Average
10. Traditional Culture
IT has never been responsible for Cost metering
Budgets are aspirational targets
Existing tools focus on Uptime, Usage and Performance Monitoring
11. Efficient Computing
You can’t manage what you don’t measure
Create Accountability, Visibility, Reporting
Meter Cost, Capacity and Usage
Show-back reports for each use type
1. Inform 2. Improve 3. Maintain
14. Truth
Like for Like - More Expensive
But it’s not Like-for-Like
• Scalability & Flexibility
• Resilience & Redundancy
• OpEx not CapEx
More Cost Effective for a lot of workloads
16. Truth
Versus Fully Loaded Server Cost - True 90% of time
Do you know the true costs of your IT infrastructure?
Cloud often ‘looks’ more expensive but is not.
Netflix vs Zynga models -> both right
24. Truth
Jevon's Paradox : The easier it becomes to consume a
resource, the more of it that will be consumed.
The Cloud has enormous efficiency capabilities.
Waste is not a technology problem, it’s a people one.
25. AWS Costs Cheat Sheet
Know the Units Instance Storage
EBS Standard
EBS PIOPS
EBS Requests
Storage
N/A
10c /gb-month (provisioned)
12.5c /gb-month (provisioned)
10c per million
Regional Cost Differences
Region
US East (Virginia)
US West (Oregon)
US West (California)
Variation
BASE
0%
12.5%
EBS Provisioned IOPS 10c /month (2.628m requests) EU (Ireland) 8%
Compute - CPU/hour EBS Snapshot
S3 Standard
S3 Reduced Redundancy
12.5c /gb-month (stored)
12.5c /gb-month (stored)
9.3c /gb-month (stored)
Asia (Singapore)
Asia (Toyko)
South America (Sao Paulo)
8%
15%
45%
Memory - GB/hour
Glacier 1c /gb-month (stored)
Instance Sizes Network
API name Compute Memory Hourly Cost Data IN FREE
Storage - GB/stored
t1.mirco <2 0.613 0.02 Data OUT 12c /gb
m1.small 1 1.7 0.08 Data within AZ FREE
m1.medium 2 3.75 0.16 Data within Region 1c /gb
m1.large 4 7.5 0.32 Managed Data (EIP/ELB) 1c /gb
Network - GB/managed
m1.xlarge 8 15 0.64 Load Balancer 2.5c /hour
m2.xlarge 6.5 17.1 0.45 Load Balanced Traffic .8c /gb
m2.2xlarge 13 34.2 0.9 IP Address Per Instance FREE
m2.4xlarge 26 68.4 1.8 Extra or Unused IP Address .5c /hour
c1.medium 5 1.7 0.165
c1.xlarge 20 7 0.66
Time Key
cc1.4xlarge 33.5 23 1.3 Day = 24 Hours
24 hours /day
cc2.8xlarge 88 60.5 2.4 Week = 168 Hours
cg1.4xlarge 33.5 22 2.1 Month = 730 Hours
hi1.4xlarge 35 60.5 3.1 Year = 8,760 Hours
Month = 2,628,000 Seconds
168 hours /week Micro
Instance
On-Demand Instance Costs
Hour
0.02
Day
0.48
Week
3.36
Month
15
Year
175
730 hours /month
Small 0.08 1.92 13.44 58 701
Medium 0.16 3.84 26.88 117 1402
Large 0.32 7.68 53.76 234 2803
Extra Large 0.64 15.36 107.52 467 5606
8,760 hours /year Extra Large High Memory
Double Extra Large High Memory
Quadruple Extra Large High Memory
Medium High CPU
0.45
0.9
1.8
0.165
10.8
21.6
43.2
3.96
75.6
151.2
302.4
27.72
329
657
1314
120
3942
7884
15768
1445
Extra Large High CPU 0.66 15.84 110.88 482 5782
Quadruple Extra Large Cluster Compute 1.3 31.2 218.4 949 11388
Eight Extra Large Cluster Compute 2.4 57.6 403.2 1752 21024
40 hours working week Quadruple Extra Large Cluster GPU
Quadruple Extra Large High I/O SSD
2.1
3.1
50.4
74.4
352.8
520.8
1533
2263
18396
27156
173 hours working month Light
Average Reserved Instance Savings
Type % Saving Yr 1
40
% Saving Yr 3
56 All Prices in Dollars, from US East Virginia as published
2,076 hours working year Medium
Heavy
48
53
65
70
11 October 2012. Tiered Discounts and Free Tier Amounts
Not Applied. For more info go to www.cloudvertical.com
26. Optimise - Rightsize
Development Environment : 40 hours per week (24% available time)
Load Test / System Patch / Software Upgrade: 8 hours / 1 day - once-off
Back-office Applications : 40 hours per week ‘heavy’; outside hours 25% capacity
Travel / E-Commerce Site : Busy Consumer Hours. Seasonal. Marketing Driven.
27. Resources www.cloudvertical.com
Deck: blog.cloudvertical.com
AWS Economics Centre : http://aws.amazon.com/economics/
Cloudonomics Book: http://www.amazon.com/Cloudonomics-Website-Business-Value-Computing/dp/1118229967
Microsoft Cloud Economics: http://www.microsoft.com/en-us/news/presskits/cloud/docs/the-economics-of-the-cloud.pdf
AWS Costs Cheat Sheet: https://blog.cloudvertical.com/2012/10/aws-cost-cheat-sheet-2/
On-Premise vs. Cloud Cost Model: http://andrewmcafee.org/2012/10/mcafee-cloud-costs-google-model
Data Gravity: http://datagravity.org/