This document provides information on different cloud platforms and services available on Google Cloud Platform that can be used with Google App Engine. It discusses Google App Engine environments and how microservices can be implemented. It also covers App Engine scaling options, including manual, basic, and automatic scaling and provides examples. Finally, it shows a sample reference architecture integrating App Engine with other Google Cloud services like Datastore, Cloud Storage, Cloud Tasks, Pub/Sub, API Endpoints, and Memcache.
Google App Engine is a Platform as a Service (PaaS) cloud computing platform that allows developers to build and host web applications in Google's data centers. It provides a scalable and reliable environment for developing applications using popular languages like Java, Python, PHP, and Go. App Engine handles tasks like provisioning servers and managing traffic so developers can focus on their code. It also includes services for storage, mail delivery, caching, and accessing web resources. App Engine is well-suited for applications with unpredictable traffic spikes or those where developers don't want to manage their own servers.
Google App Engine is a Platform as a Service (PaaS) cloud computing platform that allows developers to build and host web applications in Google's data centers. It provides a scalable and reliable environment for developing applications using popular languages like Java, Python, PHP, and Go. Google App Engine handles tasks like provisioning servers and managing traffic so developers can focus on building their applications. It also includes services for storage, mail delivery, caching, and accessing web resources.
The document discusses how to build a scalable mobile app. It explains that as an app grows in users it needs to scale to continue performing well. There are two approaches to scaling - scaling out by adding more servers or scaling up by improving existing servers. The document recommends designing for scalability from the start by using a multi-server architecture with load balancing, developing in the cloud, and following a microservices approach. It also stresses the importance of database architecture and optimization to ensure scalability.
Google App Engine is a platform for developing and hosting scalable web applications on Google's infrastructure. It provides automatic scaling, high performance, reliability and free usage within quotas. Developers can focus on coding without server maintenance. While easy to use, it has limitations around data usage and dependency on Google services. Overall, App Engine is suitable for building scalable apps using Google's capabilities and free tier.
Serverless computing is an emerging cloud computing model where the cloud provider manages resources and scales applications automatically in response to demand. With serverless, developers focus on writing code for independent, stateless functions rather than worrying about servers. Serverless platforms support automatic scaling, pay-per-use pricing, and event-driven computing using functions as the basic unit. While serverless offers benefits like reduced costs and management overhead, it also presents drawbacks like vendor lock-in and lack of debugging access.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like memcache to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like memcache to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Use Google Guice as a dependency injection framework, 6) Leverage GWT for performance, 7) Employ the GWT MVP pattern for large apps, and 8) Consider frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Use Google Guice as a dependency injection framework, 6) Leverage GWT for performance, 7) Adopt the GWT MVP pattern for large apps, and 8) Consider frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like memcache to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
Mobile App Development Company in Saudi ArabiaSteve Jonas
EmizenTech is a globally recognized software development company, proudly serving businesses since 2013. With over 11+ years of industry experience and a team of 200+ skilled professionals, we have successfully delivered 1200+ projects across various sectors. As a leading Mobile App Development Company In Saudi Arabia we offer end-to-end solutions for iOS, Android, and cross-platform applications. Our apps are known for their user-friendly interfaces, scalability, high performance, and strong security features. We tailor each mobile application to meet the unique needs of different industries, ensuring a seamless user experience. EmizenTech is committed to turning your vision into a powerful digital product that drives growth, innovation, and long-term success in the competitive mobile landscape of Saudi Arabia.
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
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The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like memcache to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like memcache to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Use Google Guice as a dependency injection framework, 6) Leverage GWT for performance, 7) Employ the GWT MVP pattern for large apps, and 8) Consider frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup times by minimizing dependencies, 5) Use Google Guice as a dependency injection framework, 6) Leverage GWT for performance, 7) Adopt the GWT MVP pattern for large apps, and 8) Consider frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like memcache to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern, and 8) Consider frameworks like Apache Wicket.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket that are optimized for App Engine.
The document provides 8 rules for building a web application effectively on Google App Engine: 1) Design a simple data model, 2) Handle data model updates via a non-default version, 3) Use techniques like Appstats and caching to reduce costs, 4) Improve cold startup time by minimizing dependencies, 5) Prefer Google Guice as a dependency injection framework, 6) Use GWT for a desktop-like interface, 7) Employ the GWT MVP pattern for large applications, and 8) Consider web frameworks like Apache Wicket.
Mobile App Development Company in Saudi ArabiaSteve Jonas
EmizenTech is a globally recognized software development company, proudly serving businesses since 2013. With over 11+ years of industry experience and a team of 200+ skilled professionals, we have successfully delivered 1200+ projects across various sectors. As a leading Mobile App Development Company In Saudi Arabia we offer end-to-end solutions for iOS, Android, and cross-platform applications. Our apps are known for their user-friendly interfaces, scalability, high performance, and strong security features. We tailor each mobile application to meet the unique needs of different industries, ensuring a seamless user experience. EmizenTech is committed to turning your vision into a powerful digital product that drives growth, innovation, and long-term success in the competitive mobile landscape of Saudi Arabia.
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
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https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
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What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
Spark is a powerhouse for large datasets, but when it comes to smaller data workloads, its overhead can sometimes slow things down. What if you could achieve high performance and efficiency without the need for Spark?
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Explore delta-rs + CDC and how these open-source innovations power lightweight, high-performance data applications beyond Spark! 🚀
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
2. Mod-2
• Working with Google App Engine Google App
Engine (GAE), Development of scalable web
application on Google cloud, Build and deploy
simple web applications to Google cloud,
Develop simple application using Google App
Engine (GAE) and its services, Exploring PaaS
with App Engine, Event Driven Programs with
Cloud Functions, Containerizing and
Orchestrating Apps with GKE.
3. Google App Engine(GAE)
• Google App Engine is mostly used to run Web
applications.
• App Engine makes it easier to develop scalable
and high-performance Web apps.
• The App Engine SDK facilitates the testing and
professionalization of applications by
emulating the production runtime
environment and allowing developers to
design and test applications on their own PCs.
4. Environments available in Google App
Engine
• GAE provides two types of app development
environments.
• In the standard environment, applications run
in a sandbox using the runtime environment
of one of the languages supported by GAE.
The environment is suitable for applications
that need to scale rapidly (up or down) in
response to sudden or extreme traffic spikes
5. Cont.,
• The GAE flexible environment automatically
scales apps up or down while also balancing
the load. It allows developers to customize the
runtimes provided for the supported
languages or provide their own runtime by
supplying a custom Docker image or
Dockerfile.
6. Cont.,
• The environment is suitable for many kinds of apps,
including apps that do the following:
• Receive consistent traffic.
• Experience regular traffic fluctuations.
• Run in a Docker container with a custom runtime or
source code written in other programming languages.
• Use frameworks with native code.
• Access Google Cloud project resources residing in the
Google Compute Engine network.
7. GAE's key features
• Blobstore for serving large data objects.
• GAE Cloud Storage to read and write files
during app runtime.
• Page Speed Service for automatically speeding
up webpage load times.
• URL Fetch Service to issue HTTP requests and
receive responses for efficiency and scaling.
• Mem cache to cache data in-memory and
speed up database operations.
8. Development of scalable web application on
Google cloud
• The easiest definition of scalability would
sound like the ability of a web app to deal with
increasing load without breaking down. It
means that no matter how many users on how
many platforms are present in one moment,
the app will perform equally well for all of
them.
9. examples of scalable web applications
• Bitly
• Bitly is the app that provides link optimization
services to individuals and businesses. Bitly helps
improve interactions with customers and build
brand awareness. Also, the app has data collection
and real-time analytics functionality, so it becomes
easy to monitor business performance.
• Slack
• Slack is a business app that helps to connect
employees. It has rich functionality that simplifies
teamwork:
10. Cont.,
• Dropbox
• Dropbox is one of the most famous file-
sharing services. The solution makes it
possible to keep business data securely and
enhances teams’ collaboration by bringing it
to one place. Dropbox is used by Spotify,
National Geographic, and other businesses,
both big and small.
11. Why should you build a scalable web application?
• Imagine that your marketing campaign for a
trip planner app attracted lots of users and, at
some point, the app has to simultaneously
serve hundreds of thousands of them. That
means millions of requests and operations
processed at the same time and a high load on
your server. If designed improperly, the system
just won’t be able to handle it.
12. scalable app architecture
• Scalable software platform: separation of concerns and
horizontal scaling.
• Separation of concerns:
• Sometimes apps are engineered in a way that one server
does the whole job: handles user requests, stores user
files, etc. In other words, it does the job that should
normally be done by several separate servers.
• Consequently, when the server gets overloaded, the
entire app is affected: pages won’t open, images won’t
load, etc. To avoid this, ensure the separation of concerns.
13. Cont.,
• For example, an API server handles priority
client-server requests that require an instant
reply. a user wants to change their profile
image. After the image is uploaded, it usually
undergoes certain processing: for example, it
can get resized, analyzed for explicit content,
or saved in storage.
14. Horizontal scaling
• How many requests is your server able to handle?
Basically, it depends on its specifications: RAM and
CPU capacity. What happens when there is only one
server that handles all of the tasks? After the load
goes beyond the server capacity, the server crashes
and the app doesn’t respond until the server recovers.
• The idea behind horizontal scaling lies in the
distribution of the load between several servers. Each
server runs a snapshot (or a copy) of the application
and is enabled or disabled depending on the current
load. Distribution of the load is carried out by a
special component — Load Balancer.
16. Cont.,
• The Load Balancer controls the number of servers
required for the smooth operation of the app. It
knows how many servers are working at the
moment as well as how many are in idle mode.
• When it sees that a server works at the top
capacity and the number of requests is growing, it
activates other servers to redistribute the load
between them. And vice versa: it disables
unneeded servers when the number of requests is
reducing.
23. Exploring PaaS with App Engine
• App engine allows you to build highly scalable
applications fully managed server less platform.
App engine is ideal if time to market is highly
valuable to you and you want to be able to
focus on writing code without ever having to
touch a server infrastructure.
• It is also ideal if you do not want to worry
about a pager going off for receiving 5XX errors.
App engine allows you to have high availability
apps without a complex architecture.
24. Cont.,
• As a fully managed environment app engine is a perfect example
of a computing platform provided as a service.
• App Engine can save organizations time and cost in software
application development by eliminating the need to buy build and
operate computer hardware and other infrastructure.
• This includes no server management and no need to configure
deployments. This allows engineering teams to focus on creating
high value applications instead of no value operations work.
• You can quickly building and deploy applications using the range
of popular programming languages, like Java, PHP, node.js
Python, C sharp, ., Ruby and Go or you can bring your own
language runtime and frameworks.
25. Cont.,
• App Engine allows you to manager resources from
the command line, debug source code in production
and run API back ends easily using industry-leading
tools such as cloud SDK cloud source repositories,
Intellij Idea, Visual Studio and Portia.
• App engine also automatically scales depending on
the application traffic and consumes resources
when code is running. This allows cost to be kept to
a minimum.
26. Event Driven Programs with Cloud Functions
• In Cloud Functions, you use event-driven
functions when you want a function to be
invoked automatically in response to an event
that occurs in your cloud environment.
• CloudEvent functions are based on CloudEvents
, an industry-standard specification for
describing event data in a common way.
• CloudEvents GitHub repository.
• a set of CloudEvents SDKs to help work with
CloudEvents objects in your code.