The document discusses cloud computing concepts and technologies. It provides an introduction to cloud models like IaaS, PaaS and SaaS and demonstrates cloud capabilities through examples on Amazon AWS, Google App Engine and Windows Azure. It also discusses the Hadoop distributed file system and MapReduce programming model for large scale data processing in the cloud.
cloud computing - concepts and technologies and mechanisms of tackling problems in cloud
you plz ignore who created it , plz focus on problem oriented points
This document discusses cloud computing concepts, technologies, and business implications. It provides an introduction to cloud models like IaaS, PaaS, and SaaS and demonstrates cloud capabilities through examples of Amazon AWS, Google App Engine, and Windows Azure. The document also discusses enabling technologies for cloud computing like virtualization and programming models for big data like MapReduce and Hadoop.
Cloud computing is defined as the sharing of computing resources such as cycles, data storage, bandwidth and other resources over the internet. It allows for on-demand access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. Some key characteristics of cloud computing include pay-as-you-go pricing models, platform/software/infrastructure as a service, and the ability to scale resources up or down quickly based on needs.
This document discusses cloud computing concepts, technologies, and business implications. It provides an introduction to cloud models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It also demonstrates cloud capabilities through examples of cloud models, data and computing models using MapReduce, and graph processing using Amazon Elastic MapReduce. The document discusses enabling cloud technologies including virtualization, multi-core architectures, and web services interfaces.
This document discusses a presentation on cloud computing concepts, technologies, and business implications. It provides an outline of the talk including an introduction to cloud models like IaaS, PaaS, and SaaS. It also discusses demonstrating cloud capabilities through examples and a case study of applying cloud computing to a real business application. The speakers' backgrounds in cloud computing are introduced and the document concludes with an introduction stating that cloud computing represents a new golden era in computing.
This document provides an outline for a talk on cloud computing. It begins with an introduction to cloud concepts and technologies like virtualization and parallel computing models. It then discusses different cloud models including IaaS, PaaS and SaaS. The outline includes demonstrations of cloud capabilities with Amazon AWS and Microsoft Azure, as well as data and computing models using MapReduce. It concludes with a case study of a real business application of the cloud and a question and answer section.
Cloud computing 13 principal enabling technologiesVaibhav Khanna
Cloud computing is Internet-based computing, whereby shared resources, software and information are provided to computers and other devices on-demand, like the electricity grid.
The cloud computing is a culmination of numerous attempts at large scale computing with seamless access to virtually limitless resources
cloud computing - concepts and technologies and mechanisms of tackling problems in cloud
you plz ignore who created it , plz focus on problem oriented points
This document discusses cloud computing concepts, technologies, and business implications. It provides an introduction to cloud models like IaaS, PaaS, and SaaS and demonstrates cloud capabilities through examples of Amazon AWS, Google App Engine, and Windows Azure. The document also discusses enabling technologies for cloud computing like virtualization and programming models for big data like MapReduce and Hadoop.
Cloud computing is defined as the sharing of computing resources such as cycles, data storage, bandwidth and other resources over the internet. It allows for on-demand access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. Some key characteristics of cloud computing include pay-as-you-go pricing models, platform/software/infrastructure as a service, and the ability to scale resources up or down quickly based on needs.
This document discusses cloud computing concepts, technologies, and business implications. It provides an introduction to cloud models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It also demonstrates cloud capabilities through examples of cloud models, data and computing models using MapReduce, and graph processing using Amazon Elastic MapReduce. The document discusses enabling cloud technologies including virtualization, multi-core architectures, and web services interfaces.
This document discusses a presentation on cloud computing concepts, technologies, and business implications. It provides an outline of the talk including an introduction to cloud models like IaaS, PaaS, and SaaS. It also discusses demonstrating cloud capabilities through examples and a case study of applying cloud computing to a real business application. The speakers' backgrounds in cloud computing are introduced and the document concludes with an introduction stating that cloud computing represents a new golden era in computing.
This document provides an outline for a talk on cloud computing. It begins with an introduction to cloud concepts and technologies like virtualization and parallel computing models. It then discusses different cloud models including IaaS, PaaS and SaaS. The outline includes demonstrations of cloud capabilities with Amazon AWS and Microsoft Azure, as well as data and computing models using MapReduce. It concludes with a case study of a real business application of the cloud and a question and answer section.
Cloud computing 13 principal enabling technologiesVaibhav Khanna
Cloud computing is Internet-based computing, whereby shared resources, software and information are provided to computers and other devices on-demand, like the electricity grid.
The cloud computing is a culmination of numerous attempts at large scale computing with seamless access to virtually limitless resources
The document discusses cloud computing concepts, technologies, and business implications. It outlines that the talk will introduce cloud context, demonstrate cloud capabilities through examples, and present a case study. Key points include that cloud computing provides on-demand access to shared computing resources over the internet and is enabled by technologies like virtualization, multi-core processors, and large data storage. Common cloud models include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
This document provides an overview of cloud computing and various cloud services. It discusses the evolution of cloud computing from earlier technologies like grid computing and utility computing. It describes the key cloud frameworks of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Major cloud providers like Amazon Web Services, Microsoft Azure, Google Cloud, and Salesforce are discussed. The document also outlines some of the advantages and use cases of cloud computing for enterprises.
The document summarizes a 2005 presentation slide on grid technology, noting that it is an emerging enabling technology that naturally evolves distributed systems and the internet through middleware supporting a network of systems for sharing, standardization, and openness. The infrastructure and application model deals with sharing compute cycles, data, storage, and other resources, moving toward delivering computing to the masses similar to other utilities like electricity and voice communication.
Over the past five years, cloud computing has gone from a curiosity to
core scientific technology. The cloud's relative simplicity, instant
availability, and reasonable cost have made it attractive to
scientists, especially in domains relatively new to large scale data
analysis. This trend will continue into the foreseeable future,
challenging resource providers to adapt their services, to provide
easy federation with other providers, and to accommodate many
different scientific disciplines. For developers of cloud services,
there are also many challenges. Efficient access to, and the curation
of large data sets remain largely unsolved problems. Image
management also raises new issues, especially if these images are to
be shared and trusted. This presentation reviews the current status
of cloud computing and presents some ideas on how the upcoming
challenges might be met.
Presented at CNAF in Bologna, Italy by Charles Loomis in May 2013.
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Key characteristics of cloud computing include on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. Common uses of cloud computing involve hosting applications and services through major cloud platforms like Amazon Web Services, Microsoft Azure, and Google Cloud.
The document discusses cloud computing technology and applications. It provides an introduction to cloud computing concepts, distributed systems, MapReduce, and technologies like Google File System, BigTable and AppEngine. It then outlines the syllabus for a cloud computing course, including topics on virtualization, data centers, and guest lectures. Project presentations will account for 60% of the grading.
Ahmad Shah Sultani presented on cloud computing using the Apache CloudStack open source platform. He discussed the history and characteristics of cloud computing, different service models (SaaS, PaaS, IaaS), and types of cloud storage. He also explained concepts like virtualization and the benefits of using open source software to build clouds. Sultani demonstrated how to deploy CloudStack on virtualized servers to create a private cloud and manage virtual machines through its web-based user interface.
This document provides an overview of cloud computing presented by Ganesh Neelakanta Iyer. It begins with Ganesh introducing himself and his research interests in cloud computing, resource allocation, and pricing. He then provides a basic introduction to cloud computing, discussing how common technologies like YouTube, Google, and Facebook utilize cloud computing. The document outlines different cloud service models including Software as a Service, Platform as a Service, and Infrastructure as a Service. It also discusses some challenges of cloud computing and tips for getting started. Ganesh describes his research focusing on auction-based and incentive-based mechanisms for multiple cloud orchestration. He concludes with future projections about cloud computing growth and job opportunities in India.
This document provides an overview of cloud computing. It begins with learning objectives and defines cloud computing according to NIST as a model for enabling network access to a shared pool of configurable computing resources that can be rapidly provisioned with minimal management effort. It describes the five essential cloud characteristics, three service models (SaaS, PaaS, IaaS), and four deployment models (private, public, hybrid, community). Examples are given for each along with issues and benefits of cloud computing. The document provides a comprehensive introduction to cloud computing concepts.
This document discusses the use of cloud computing in academic libraries. It defines cloud computing and outlines the main types: Software as a Service, Platform as a Service, and Infrastructure as a Service. The document explores how libraries can use cloud computing to provide services like storage, access to collections and resources, and instruction. While cloud computing provides benefits like cost savings, increased storage, and flexibility, it also poses security, connectivity, and reliability risks that libraries must consider when adopting these services.
Clould Computing and its application in LibrariesAmit Shaw
Cloud computing offers several potential benefits for libraries, including lower costs, increased storage capacity, improved mobility and access, and more flexible workflows. Key aspects of cloud computing include deployment models like private, public and hybrid clouds. Issues include security, data ownership, and lack of control. Recent trends include the use of cloud-based library services and products, as well as research into cloud computing architectures and management. Overall, cloud computing can help libraries modernize services in a cost-effective manner.
Cloud computing allows consumers and businesses to use applications without installation and access files from any internet-connected device. It provides shared computing resources over a network on-demand as a utility. There are concerns around security and privacy as cloud providers have control over user data. However, new approaches around information-centric security aim to give more control to users. A shift to cloud computing could benefit large internet companies while traditional software producers may face challenges adapting. It remains to be seen if cloud computing will ultimately become the dominant IT model.
Current Trends and Future Directions in cloud computing were discussed. Key points included:
- Cloud computing provides on-demand access to computing resources and pay-per-use model.
- Major cloud platforms offer Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
- Big data and NoSQL databases are enabling organizations to analyze large and diverse datasets.
- Future directions may include newSQL databases, software defined datacenters, and harnessing big data for intelligence.
Best example of Cloud computing is my academic digital library.Aman Pandey
This document discusses using cloud computing in academic libraries. It defines cloud computing and outlines its types. The document explores how libraries can use cloud computing to provide services like storage, content access, and instruction. Benefits include cost savings, increased storage, flexibility and mobility. Challenges include security, network connectivity dependence on providers, and integration issues. The document concludes that while immature, cloud computing can make library software and data universally available if bandwidth issues are addressed.
Zpryme Report on Cloud and SAS SolutionsPaula Smith
The document provides an overview of the history and development of cloud computing and software-as-a-service (SaaS) technologies and their potential benefits for utilities. It discusses how utilities initially struggled with smart grid modernization due to fragmented systems and big data challenges. The emergence of cloud hosting, SaaS and managed services has enabled even small and mid-sized utilities to realize the benefits of a fully integrated smart grid infrastructure. The document then covers key concepts around cloud computing models, virtualization, and the opportunities that SaaS and cloud-based analytics present for improved utility operations and planning.
AI-Driven Science and Engineering with the Global AI and Modeling Supercomput...Geoffrey Fox
Most things are dominated by Artificial Intelligence (AI). Technology Companies like Amazon, Google, Facebook, and Microsoft are AI First organizations.
Engineering achievement today is highlighted by the AI buried in a vehicle or machine. Industry (Manufacturing) 4.0 focusses on the AI-Driven future of the Industrial Internet of Things.
Software is eating the world.
We can describe much computer systems work as designing, building and using the Global AI and Modelling supercomputer which itself is autonomously tuned by AI. We suggest that this is not just a bunch of buzzwords but has profound significance and examine consequences of this for education and research.
Naively high-performance computing should be relevant for the AI supercomputer but somehow the corporate juggernaut is not making so much use of it. We discuss how to change this.
This document provides an overview of cloud computing concepts including:
- The key characteristics of cloud computing including on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service.
- The roots of cloud computing in technologies like virtualization, distributed computing, web services, and utility computing.
- The different service models of cloud computing including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The document discusses cloud computing concepts, technologies, and business implications. It outlines that the talk will introduce cloud context, demonstrate cloud capabilities through examples, and present a case study. Key points include that cloud computing provides on-demand access to shared computing resources over the internet and is enabled by technologies like virtualization, multi-core processors, and large data storage. Common cloud models include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
This document provides an overview of cloud computing and various cloud services. It discusses the evolution of cloud computing from earlier technologies like grid computing and utility computing. It describes the key cloud frameworks of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Major cloud providers like Amazon Web Services, Microsoft Azure, Google Cloud, and Salesforce are discussed. The document also outlines some of the advantages and use cases of cloud computing for enterprises.
The document summarizes a 2005 presentation slide on grid technology, noting that it is an emerging enabling technology that naturally evolves distributed systems and the internet through middleware supporting a network of systems for sharing, standardization, and openness. The infrastructure and application model deals with sharing compute cycles, data, storage, and other resources, moving toward delivering computing to the masses similar to other utilities like electricity and voice communication.
Over the past five years, cloud computing has gone from a curiosity to
core scientific technology. The cloud's relative simplicity, instant
availability, and reasonable cost have made it attractive to
scientists, especially in domains relatively new to large scale data
analysis. This trend will continue into the foreseeable future,
challenging resource providers to adapt their services, to provide
easy federation with other providers, and to accommodate many
different scientific disciplines. For developers of cloud services,
there are also many challenges. Efficient access to, and the curation
of large data sets remain largely unsolved problems. Image
management also raises new issues, especially if these images are to
be shared and trusted. This presentation reviews the current status
of cloud computing and presents some ideas on how the upcoming
challenges might be met.
Presented at CNAF in Bologna, Italy by Charles Loomis in May 2013.
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Key characteristics of cloud computing include on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service. Common uses of cloud computing involve hosting applications and services through major cloud platforms like Amazon Web Services, Microsoft Azure, and Google Cloud.
The document discusses cloud computing technology and applications. It provides an introduction to cloud computing concepts, distributed systems, MapReduce, and technologies like Google File System, BigTable and AppEngine. It then outlines the syllabus for a cloud computing course, including topics on virtualization, data centers, and guest lectures. Project presentations will account for 60% of the grading.
Ahmad Shah Sultani presented on cloud computing using the Apache CloudStack open source platform. He discussed the history and characteristics of cloud computing, different service models (SaaS, PaaS, IaaS), and types of cloud storage. He also explained concepts like virtualization and the benefits of using open source software to build clouds. Sultani demonstrated how to deploy CloudStack on virtualized servers to create a private cloud and manage virtual machines through its web-based user interface.
This document provides an overview of cloud computing presented by Ganesh Neelakanta Iyer. It begins with Ganesh introducing himself and his research interests in cloud computing, resource allocation, and pricing. He then provides a basic introduction to cloud computing, discussing how common technologies like YouTube, Google, and Facebook utilize cloud computing. The document outlines different cloud service models including Software as a Service, Platform as a Service, and Infrastructure as a Service. It also discusses some challenges of cloud computing and tips for getting started. Ganesh describes his research focusing on auction-based and incentive-based mechanisms for multiple cloud orchestration. He concludes with future projections about cloud computing growth and job opportunities in India.
This document provides an overview of cloud computing. It begins with learning objectives and defines cloud computing according to NIST as a model for enabling network access to a shared pool of configurable computing resources that can be rapidly provisioned with minimal management effort. It describes the five essential cloud characteristics, three service models (SaaS, PaaS, IaaS), and four deployment models (private, public, hybrid, community). Examples are given for each along with issues and benefits of cloud computing. The document provides a comprehensive introduction to cloud computing concepts.
This document discusses the use of cloud computing in academic libraries. It defines cloud computing and outlines the main types: Software as a Service, Platform as a Service, and Infrastructure as a Service. The document explores how libraries can use cloud computing to provide services like storage, access to collections and resources, and instruction. While cloud computing provides benefits like cost savings, increased storage, and flexibility, it also poses security, connectivity, and reliability risks that libraries must consider when adopting these services.
Clould Computing and its application in LibrariesAmit Shaw
Cloud computing offers several potential benefits for libraries, including lower costs, increased storage capacity, improved mobility and access, and more flexible workflows. Key aspects of cloud computing include deployment models like private, public and hybrid clouds. Issues include security, data ownership, and lack of control. Recent trends include the use of cloud-based library services and products, as well as research into cloud computing architectures and management. Overall, cloud computing can help libraries modernize services in a cost-effective manner.
Cloud computing allows consumers and businesses to use applications without installation and access files from any internet-connected device. It provides shared computing resources over a network on-demand as a utility. There are concerns around security and privacy as cloud providers have control over user data. However, new approaches around information-centric security aim to give more control to users. A shift to cloud computing could benefit large internet companies while traditional software producers may face challenges adapting. It remains to be seen if cloud computing will ultimately become the dominant IT model.
Current Trends and Future Directions in cloud computing were discussed. Key points included:
- Cloud computing provides on-demand access to computing resources and pay-per-use model.
- Major cloud platforms offer Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
- Big data and NoSQL databases are enabling organizations to analyze large and diverse datasets.
- Future directions may include newSQL databases, software defined datacenters, and harnessing big data for intelligence.
Best example of Cloud computing is my academic digital library.Aman Pandey
This document discusses using cloud computing in academic libraries. It defines cloud computing and outlines its types. The document explores how libraries can use cloud computing to provide services like storage, content access, and instruction. Benefits include cost savings, increased storage, flexibility and mobility. Challenges include security, network connectivity dependence on providers, and integration issues. The document concludes that while immature, cloud computing can make library software and data universally available if bandwidth issues are addressed.
Zpryme Report on Cloud and SAS SolutionsPaula Smith
The document provides an overview of the history and development of cloud computing and software-as-a-service (SaaS) technologies and their potential benefits for utilities. It discusses how utilities initially struggled with smart grid modernization due to fragmented systems and big data challenges. The emergence of cloud hosting, SaaS and managed services has enabled even small and mid-sized utilities to realize the benefits of a fully integrated smart grid infrastructure. The document then covers key concepts around cloud computing models, virtualization, and the opportunities that SaaS and cloud-based analytics present for improved utility operations and planning.
AI-Driven Science and Engineering with the Global AI and Modeling Supercomput...Geoffrey Fox
Most things are dominated by Artificial Intelligence (AI). Technology Companies like Amazon, Google, Facebook, and Microsoft are AI First organizations.
Engineering achievement today is highlighted by the AI buried in a vehicle or machine. Industry (Manufacturing) 4.0 focusses on the AI-Driven future of the Industrial Internet of Things.
Software is eating the world.
We can describe much computer systems work as designing, building and using the Global AI and Modelling supercomputer which itself is autonomously tuned by AI. We suggest that this is not just a bunch of buzzwords but has profound significance and examine consequences of this for education and research.
Naively high-performance computing should be relevant for the AI supercomputer but somehow the corporate juggernaut is not making so much use of it. We discuss how to change this.
This document provides an overview of cloud computing concepts including:
- The key characteristics of cloud computing including on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service.
- The roots of cloud computing in technologies like virtualization, distributed computing, web services, and utility computing.
- The different service models of cloud computing including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
1. Cloud Computing: Concepts,
Technologies and Business
Implications
B. Ramamurthy & K. Madurai
bina@buffalo.edu & kumar.madurai@ctg.com
This talks is partially supported by National Science
Foundation grants DUE: #0920335, OCI: #1041280
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2. Outline of the talk
• Introduction to cloud context
o Technology context: multi-core, virtualization, 64-bit processors, parallel
computing models, big-data storages…
o Cloud models: IaaS (Amazon AWS), PaaS (Microsoft Azure), SaaS (Google
App Engine)
• Demonstration of cloud capabilities
o Cloud models
o Data and Computing models: MapReduce
o Graph processing using amazon elastic mapreduce
• A case-study of real business application of the
cloud
• Questions and Answers
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3. Speakers’ Background in cloud
computing
• Bina:
o Has two current NSF (National Science Foundation of USA)
awards related to cloud computing:
o 2009-2012: Data-Intensive computing education: CCLI Phase 2:
$250K
o 2010-2012: Cloud-enabled Evolutionary Genetics Testbed: OCI-
CI-TEAM: $250K
o Faculty at the CSE department at University at Buffalo.
• Kumar:
o Principal Consultant at CTG
o Currently heading a large semantic technology business
initiative that leverages cloud computing
o Adjunct Professor at School of Management, University at
Buffalo.
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4. Introduction: A Golden Era in
Computing
Powerful
multi-core
processors
General
purpose
graphic
processors
Superior
software
methodologies
Virtualization
leveraging the
powerful
hardware
Wider bandwidth
for communication
Proliferation
of devices
Explosion of
domain
applications
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6. Evolution of Internet Computing
Publish
Inform
Interact
Integrate
Transact
Discover
(intelligence)
Automate
(discovery)
time
scale
Social
media
and
networking
Semantic
discovery
Data-intensive
HPC, cloud
web
deep web
Data
marketplace
and
analytics
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7. Top Ten Largest Databases
0
1000
2000
3000
4000
5000
6000
7000
LOC CIA Amazon YOUTube ChoicePt Sprint Google AT&T NERSC Climate
Top ten largest databases (2007)
Terabytes
Ref: http://www.focus.com/fyi/operations/10-largest-databases-in-the-world/
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8. Challenges
• Alignment with the needs of the business / user / non-
computer specialists / community and society
• Need to address the scalability issue: large scale data, high
performance computing, automation, response time, rapid
prototyping, and rapid time to production
• Need to effectively address (i) ever shortening cycle of
obsolescence, (ii) heterogeneity and (iii) rapid changes in
requirements
• Transform data from diverse sources into intelligence and
deliver intelligence to right people/user/systems
• What about providing all this in a cost-effective manner?
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9. Enter the cloud
• Cloud computing is Internet-based computing, whereby
shared resources, software and information are provided
to computers and other devices on-demand, like the
electricity grid.
• The cloud computing is a culmination of numerous
attempts at large scale computing with seamless access
to virtually limitless resources.
o on-demand computing, utility computing, ubiquitous computing, autonomic
computing, platform computing, edge computing, elastic computing, grid
computing, …
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10. “Grid Technology: A slide from my presentation
to Industry (2005)
• Emerging enabling technology.
• Natural evolution of distributed systems and the Internet.
• Middleware supporting network of systems to facilitate
sharing, standardization and openness.
• Infrastructure and application model dealing with sharing of
compute cycles, data, storage and other resources.
• Publicized by prominent industries as on-demand computing,
utility computing, etc.
• Move towards delivering “computing” to masses similar to
other utilities (electricity and voice communication).”
• Now,
Hmmm…sounds like the definition for cloud computing!!!!!
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11. It is a changed world now…
• Explosive growth in applications: biomedical informatics, space exploration,
business analytics, web 2.0 social networking: YouTube, Facebook
• Extreme scale content generation: e-science and e-business data deluge
• Extraordinary rate of digital content consumption: digital gluttony: Apple
iPhone, iPad, Amazon Kindle
• Exponential growth in compute capabilities: multi-core, storage, bandwidth,
virtual machines (virtualization)
• Very short cycle of obsolescence in technologies: Windows Vista
Windows 7; Java versions; CC#; Phython
• Newer architectures: web services, persistence models, distributed file
systems/repositories (Google, Hadoop), multi-core, wireless and mobile
• Diverse knowledge and skill levels of the workforce
• You simply cannot manage this complex situation with your traditional IT
infrastructure:
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12. Answer: The Cloud Computing?
• Typical requirements and models:
o platform (PaaS),
o software (SaaS),
o infrastructure (IaaS),
o Services-based application programming interface (API)
• A cloud computing environment can provide one or more
of these requirements for a cost
• Pay as you go model of business
• When using a public cloud the model is similar to renting
a property than owning one.
• An organization could also maintain a private cloud
and/or use both.
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14. Common Features of Cloud Providers
Development
Environment:
IDE, SDK, Plugins
Production
Environment
Simple
storage
Table Store
<key, value>
Drives
Accessible through
Web services
Management Console and Monitoring tools
& multi-level security
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15. Windows Azure
• Enterprise-level on-demand capacity builder
• Fabric of cycles and storage available on-request for a
cost
• You have to use Azure API to work with the infrastructure
offered by Microsoft
• Significant features: web role, worker role , blob storage,
table and drive-storage
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16. Amazon EC2
• Amazon EC2 is one large complex web service.
• EC2 provided an API for instantiating computing
instances with any of the operating systems supported.
• It can facilitate computations through Amazon Machine
Images (AMIs) for various other models.
• Signature features: S3, Cloud Management Console,
MapReduce Cloud, Amazon Machine Image (AMI)
• Excellent distribution, load balancing, cloud monitoring
tools
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17. Google App Engine
• This is more a web interface for a development
environment that offers a one stop facility for design,
development and deployment Java and Python-based
applications in Java, Go and Python.
• Google offers the same reliability, availability and
scalability at par with Google’s own applications
• Interface is software programming based
• Comprehensive programming platform irrespective of the
size (small or large)
• Signature features: templates and appspot, excellent
monitoring and management console
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18. Demos
• Amazon AWS: EC2 & S3 (among the many infrastructure
services)
o Linux machine
o Windows machine
o A three-tier enterprise application
• Google app Engine
o Eclipse plug-in for GAE
o Development and deployment of an application
• Windows Azure
o Storage: blob store/container
o MS Visual Studio Azure development and production environment
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20. The Context: Big-data
• Data mining huge amounts of data collected in a wide range of domains
from astronomy to healthcare has become essential for planning and
performance.
• We are in a knowledge economy.
o Data is an important asset to any organization
o Discovery of knowledge; Enabling discovery; annotation of data
o Complex computational models
o No single environment is good enough: need elastic, on-demand
capacities
• We are looking at newer
o Programming models, and
o Supporting algorithms and data structures.
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21. Google File System
• Internet introduced a new challenge in the form web logs,
web crawler’s data: large scale “peta scale”
• But observe that this type of data has an uniquely different
characteristic than your transactional or the “customer
order” data : “write once read many (WORM)” ;
• Privacy protected healthcare and patient information;
• Historical financial data;
• Other historical data
• Google exploited this characteristics in its Google file
system (GFS)
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22. What is Hadoop?
At Google MapReduce operation are run on a special file
system called Google File System (GFS) that is highly
optimized for this purpose.
GFS is not open source.
Doug Cutting and others at Yahoo! reverse engineered the
GFS and called it Hadoop Distributed File System (HDFS).
The software framework that supports HDFS, MapReduce
and other related entities is called the project Hadoop or
simply Hadoop.
This is open source and distributed by Apache.
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23. Fault tolerance
• Failure is the norm rather than exception
• A HDFS instance may consist of thousands of server
machines, each storing part of the file system’s data.
• Since we have huge number of components and that each
component has non-trivial probability of failure means that
there is always some component that is non-functional.
• Detection of faults and quick, automatic recovery from them
is a core architectural goal of HDFS.
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25. Hadoop Distributed File System
Application
Local file
system
Master node
Name Nodes
HDFS Client
HDFS Server
Block size: 2K
Block size: 128M
Replicated
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26. What is MapReduce?
MapReduce is a programming model Google has used successfully is
processing its “big-data” sets (~ 20000 peta bytes per day)
A map function extracts some intelligence from raw data.
A reduce function aggregates according to some guides the data
output by the map.
Users specify the computation in terms of a map and a reduce
function,
Underlying runtime system automatically parallelizes the
computation across large-scale clusters of machines, and
Underlying system also handles machine failures, efficient
communications, and performance issues.
-- Reference: Dean, J. and Ghemawat, S. 2008. MapReduce: simplified data
processing on large clusters. Communication of ACM 51, 1 (Jan. 2008), 107-113.
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27. Classes of problems “mapreducable”
Benchmark for comparing: Jim Gray’s challenge on data-
intensive computing. Ex: “Sort”
Google uses it for wordcount, adwords, pagerank, indexing data.
Simple algorithms such as grep, text-indexing, reverse indexing
Bayesian classification: data mining domain
Facebook uses it for various operations: demographics
Financial services use it for analytics
Astronomy: Gaussian analysis for locating extra-terrestrial
objects.
Expected to play a critical role in semantic web and in web 3.0
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29. MapReduce Engine
• MapReduce requires a distributed file system and an
engine that can distribute, coordinate, monitor and gather
the results.
• Hadoop provides that engine through (the file system we
discussed earlier) and the JobTracker + TaskTracker
system.
• JobTracker is simply a scheduler.
• TaskTracker is assigned a Map or Reduce (or other
operations); Map or Reduce run on node and so is the
TaskTracker; each task is run on its own JVM on a node.
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30. Demos
• Word count application: a simple foundation for text-
mining; with a small text corpus of inaugural speeches
by US presidents
• Graph analytics is the core of analytics involving linked
structures (about 110 nodes): shortest path
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31. A Case-study in Business:
Cloud Strategies
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32. Predictive Quality Project Overview
• Identify special causes that relate to bad outcomes for the quality-related
parameters of the products and visually inspected defects
• Complex upstream process conditions and dependencies making the
problem difficult to solve using traditional statistical / analytical methods
• Determine the optimal process settings that can increase the yield and
reduce defects through predictive quality assurance
• Potential savings huge as the cost of rework and rejects are very high
Problem / Motivation:
Solution:
• Use ontology to model the complex manufacturing processes and utilize
semantic technologies to provide key insights into how outcomes and causes
are related
• Develop a rich internet application that allows the user to evaluate process
outcomes and conditions at a high level and drill down to specific areas of
interest to address performance issues
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33. Why Cloud Computing for this Project
• Well-suited for incubation of new technologies
o Semantic technologies still evolving
o Use of Prototyping and Extreme Programming
o Server and Storage requirements not completely known
• Technologies used (TopBraid, Tomcat) not part of
emerging or core technologies supported by corporate IT
• Scalability on demand
• Development and implementation on a private cloud
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34. Public Cloud vs. Private Cloud
Rationale for Private Cloud:
• Security and privacy of business data was a big concern
• Potential for vendor lock-in
• SLA’s required for real-time performance and reliability
• Cost savings of the shared model achieved because of
the multiple projects involving semantic technologies that
the company is actively developing
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35. Cloud Computing for the Enterprise
What should IT Do
• Revise cost model to utility-based computing: CPU/hour,
GB/day etc.
• Include hidden costs for management, training
• Different cloud models for different applications -
evaluate
• Use for prototyping applications and learn
• Link it to current strategic plans for Services-Oriented
Architecture, Disaster Recovery, etc.
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36. References & useful links
• Amazon AWS: http://aws.amazon.com/free/
• AWS Cost Calculator:
http://calculator.s3.amazonaws.com/calc5.html
• Windows Azure: http://www.azurepilot.com/
• Google App Engine (GAE):
http://code.google.com/appengine/docs/whatisgoogleapp
engine.html
• Graph Analytics:
http://www.umiacs.umd.edu/~jimmylin/Cloud9/docs/cont
ent/Lin_Schatz_MLG2010.pdf
• For miscellaneous information:
http://www.cse.buffalo.edu/~bina
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37. Summary
• We illustrated cloud concepts and demonstrated the cloud
capabilities through simple applications
• We discussed the features of the Hadoop File System, and
mapreduce to handle big-data sets.
• We also explored some real business issues in adoption of
cloud.
• Cloud is indeed an impactful technology that is sure to
transform computing in business.
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