The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
Provides a simple and unambiguous taxonomy of three service models
- Software as a service (SaaS)
- Platform as a service (PaaS)
- Infrastructure as a service (IaaS)
(Private cloud, Community cloud, Public cloud, and Hybrid cloud)
- Problems with traditional data centers.
- Cloud computing definition, deployment, and services models.
- Essential characteristics of cloud services.
- IaaS examples.
- PaaS examples.
- SaaS examples.
- Cloud enabling technologies such as grid computing, utility computing, service oriented architecture (SOA), The Internet, Multi-tenancy, Web 2.0, Automation and Virtualization.
Cloud Computing offers an on-demand and scalable access to a shared pool of resources hosted in a data center at providers’ site. It reduces the overheads of up-front investments and financial risks for the end-user. Regardless of the fact that cloud computing offers great advantages to the end users, there are several challenging issues that are mandatory to be addressed.
Presentation for Introduction to Google Cloud Platform. This PPT provides basic understanding for services provided by Google Cloud Platform like Compute, Storage, VPC, IAM.
The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer.
Infrastructure as a Service ( IaaS) is one of the three fundamental services in cloud computing. IaaS provides access to basic computing resources such as hardware- processor, storage , network cards and more
Presentation of google app engine what it is and how it work
What is google app engine
Why app engine
Components
Architecture
Computing Environment
References
Provides a simple and unambiguous taxonomy of three service models
- Software as a service (SaaS)
- Platform as a service (PaaS)
- Infrastructure as a service (IaaS)
(Private cloud, Community cloud, Public cloud, and Hybrid cloud)
- Problems with traditional data centers.
- Cloud computing definition, deployment, and services models.
- Essential characteristics of cloud services.
- IaaS examples.
- PaaS examples.
- SaaS examples.
- Cloud enabling technologies such as grid computing, utility computing, service oriented architecture (SOA), The Internet, Multi-tenancy, Web 2.0, Automation and Virtualization.
Cloud Computing offers an on-demand and scalable access to a shared pool of resources hosted in a data center at providers’ site. It reduces the overheads of up-front investments and financial risks for the end-user. Regardless of the fact that cloud computing offers great advantages to the end users, there are several challenging issues that are mandatory to be addressed.
Presentation for Introduction to Google Cloud Platform. This PPT provides basic understanding for services provided by Google Cloud Platform like Compute, Storage, VPC, IAM.
The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer.
Infrastructure as a Service ( IaaS) is one of the three fundamental services in cloud computing. IaaS provides access to basic computing resources such as hardware- processor, storage , network cards and more
Presentation of google app engine what it is and how it work
What is google app engine
Why app engine
Components
Architecture
Computing Environment
References
The presentation includes a brief introduction of cloud and its services followed by details of google app engine (GAE). Features and components of GAE are included along with the comparison of other existing cloud service providers. Advantages and disadvantages are also shown and life cycle of GAE is described.
What's new in App Engine and intro to App Engine for BusinessChris Schalk
This is a presentation given by Devfest Madrid 2010 by Google Developer Advocate Chris Schalk on "What's new in Google App Engine and Intro to App Engine for Business"
Part I: Introduction to Cloud Computing
- What is Cloud Computing?
- Classification of Cloud Computing
Part II: Introduction to Google App Engine
- What is Google App Engine?
- Why Google App Engine?
- Core APIs & Language Support
- Google App Engine for Business
- Google App Engine Customers
- Q&A
This slide deck provides the basics of Azure App Service. This presentation was presented by Harikharan Krishnaraju, Developer Support Escalation Engineer, Microsoft during the TechMeet360 event organized by BizTalk360, held on December 17, 2016 at Coimbatore.
Entrepreneurship Tips With HTML5 & App Engine Startup Weekend (June 2012)Ido Green
My talk in Startup Weekend 2012 during Google I/O. It cover, startup life tips, modern web apps and how to leverage Google cloud (specific App Engine).
Google App Engine or GAE was first released as a beta version in April 2008. It is a platform for developing and hosting web applications in Google managed data centers. Google App Engine is software that facilitates the user to run his/her web applications on Google infrastructure and provides a wide range of APIs integrated with google accounts for security and scalability.
1. Cloud Computing
2. Why PaaS?
3. Google App Engine
4. GAE Timeline
5. Why Google App Engine?
6. Architecture - Application Server and Web Application
7. Working - Deployment Cycle, Physical Deployment Diagram, Runtime Environments, Components of GAE, Framework Structure, Sandbox in GAE
8. Services
9. Usage Limits
10. Discussion - Benefits and limitations
11. References
*The content, images, and references used in this presentation belong to their respective owners with due credit.
Academic Presentation by Sameer Satyam.
In computing ,a futex is a linux kernel system call that programmers can use to implement basic locking, or as a building block for higher-level locking abstractions such as posix mutexes or condition variables.
A Distributed computing architeture consists of very lightweight software agents installed on a number of client systems , and one or more dedicated distributed computing managment servers.
An ocular prosthesis or artificial eye is a type of craniofacial prosthesis that replaces an absent eye following an enuleatin, evisceration, or orbital exenteration.
Wibree is the first open technology offering connectivity between mobile devices or personal computers and small button cell battery power devices such as watches, wireless keyboards, toys and sports & health care sensors
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
2. Google App Engine
Content
•What Is App Engine?
•Google App Engine
•Why App Engine?
•Components
•Architectures
•Computing Environment
•Comparative Study with Other Service
•Advantages of Google App Engine
•Disadvantages of Google App Engine
•What Next?
•Conclusion
•References
3. What IS App Engine?
Google App Engine
•Google’s Platform to Bulid Web Application on Cloud
•Dynamic Web server with full support for common web techonologies
•Automatic Scaling & Load balancing
•Transctional Datastore model
4. Google App Engine
Google App Engine
Google App Engine (often referred to as GAE or simply App Engine) is a platform as a service
(PaaS) cloud computing platform for developing and hosting web applications in Google-managed
data centers. Applications are sandboxed and run across multiple servers. App Engine offers
automatic scaling for web applications—as the number of requests increases for an application, App
Engine automatically allocates more resources for the web application to handle the additional
demand.
Google App Engine is free up to a certain level of consumed resources. Fees are charged for
additional storage, bandwidth, or instance hours required by the application. It was first released as
a preview version in April 2008, and came out of preview in September 2011.
5. Why App Engine?
Google App Engine
•Lower total cost of ownership
•Rich set of APIs
•Fully featured SDK for Local development
•Ease of Deployment
13. Google App Engine
Google App Engine Amazon Web
Services
Cloud Services PaaS PaaS, IaaS
Platforms Supported Linux,Windows Server 2008 Linux,Open Solaris,
Windows Server 2003
Virtualization Platform Application Container OS level running on a Xen Hypervisor
Storage BigTable and MegaStore Amazon Simple Storage and
SimpleDB
Control Interface API API Command Line
Languages Supported Java Python Java,PHP,PythonRuby
Load Balancing Auto Round Robin
Data after termination Google will not take any action for 90
days after the effective date of
termination
Amazon will not take any action for a
period of 30 days after the
effective date of termination
14. Advantages of Google App Engine
Infrastructure for Security
Scalability
Performance and Reliability
Cost Savings
Platform Independence
Google App Engine
15. Disadvantages of Google App Engine
You Are At Google’s Mercy
Violation of Policies
Forget Porting
It isn’t Free
Google App Engine
16. What’s Next?
Google App Engine
•More Languages on App Engine
•Scheduted jobs
•Large download/upload support
•Purchasing additional capacity
17. Conclusion
Google App Engine
•Flexibility: Java or Python APIs, no 'lock-in‘
•Security: sandbox environment, rich APIs
•Easy to Start: generous free quota
•Easy to Scale: uses Google infrastructure
•FUTURE: better performance, new features
