GraphQL has many advantages over RESTful APIs. A lot of companies start thinking about migration paths for adopting GraphQL, which not only come with technological but also with organizational challenges!
This document is a presentation on GraphQL fundamentals. It was created by Virbhadra S. Ankalkote from BORN Group. The presentation covers what GraphQL is, who created it, why it was created, and how it works. It defines GraphQL as a query language for APIs that fulfills queries with existing data. It notes that Facebook developed GraphQL in 2012 for their native mobile app. In comparison to REST APIs, GraphQL allows clients to get precisely the data they need in one request. The presentation explains the GraphQL specification and includes sections on reading and writing data, using variables and fragments, and limitations such as indefinite querying depth.
GraphQL is a declarative data fetching method that provides a single endpoint for queries. It was developed by Facebook in 2012 and addresses challenges with REST like over- and under-fetching of data. GraphQL uses a schema to define types and their relations, and allows fetching nested data in a single query to the server. It supports queries to read data, and mutations to write data by creating, updating, or deleting data records.
This document discusses various GraphQL tooling options. It describes GraphQL Config as a common configuration format, the GraphQL CLI for tying together multiple tools, and GraphQL Playground for exploring schemas. It also outlines GraphQL Binding for reusing APIs, GrAMPS for building microservices, GraphQL Import for splitting schemas, Apollo Tracing for performance insights, and GraphQL Yoga as an all-in-one server implementation.
GraphQL is a data query and manipulation language that provides a single endpoint for fetching data from multiple sources. It allows clients to define their own data requirements and exposes data through a single schema. Some key benefits include fewer roundtrips to the server and allowing UI components to describe their own data dependencies. Apollo Client is commonly used with GraphQL and works well with Redux. It provides features like caching, refetching, and loading states. Development tools include Apollo devtools, GraphiQL, and ESLint plugins. Best practices include creating interfaces for pagination, handling authorization, error handling, and partial responses.
Learn how to build advanced GraphQL queries, how to work with filters and patches and how to embed GraphQL in languages like Python and Java. These slides are the second set in our webinar series on GraphQL.
apidays LIVE Paris - The Rise of GraphQL for database APIs by Karthic Raoapidays
apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020
The Rise of GraphQL for database APIs
Karthic Rao, Founder of Pixelbytestudio
This document is a presentation on GraphQL fundamentals. It was created by Virbhadra S. Ankalkote from BORN Group. The presentation covers what GraphQL is, who created it, why it was created, and how it works. It defines GraphQL as a query language for APIs that fulfills queries with existing data. It notes that Facebook developed GraphQL in 2012 for their native mobile app. In comparison to REST APIs, GraphQL allows clients to get precisely the data they need in one request. The presentation explains the GraphQL specification and includes sections on reading and writing data, using variables and fragments, and limitations such as indefinite querying depth.
GraphQL is a declarative data fetching method that provides a single endpoint for queries. It was developed by Facebook in 2012 and addresses challenges with REST like over- and under-fetching of data. GraphQL uses a schema to define types and their relations, and allows fetching nested data in a single query to the server. It supports queries to read data, and mutations to write data by creating, updating, or deleting data records.
This document discusses various GraphQL tooling options. It describes GraphQL Config as a common configuration format, the GraphQL CLI for tying together multiple tools, and GraphQL Playground for exploring schemas. It also outlines GraphQL Binding for reusing APIs, GrAMPS for building microservices, GraphQL Import for splitting schemas, Apollo Tracing for performance insights, and GraphQL Yoga as an all-in-one server implementation.
GraphQL is a data query and manipulation language that provides a single endpoint for fetching data from multiple sources. It allows clients to define their own data requirements and exposes data through a single schema. Some key benefits include fewer roundtrips to the server and allowing UI components to describe their own data dependencies. Apollo Client is commonly used with GraphQL and works well with Redux. It provides features like caching, refetching, and loading states. Development tools include Apollo devtools, GraphiQL, and ESLint plugins. Best practices include creating interfaces for pagination, handling authorization, error handling, and partial responses.
Learn how to build advanced GraphQL queries, how to work with filters and patches and how to embed GraphQL in languages like Python and Java. These slides are the second set in our webinar series on GraphQL.
apidays LIVE Paris - The Rise of GraphQL for database APIs by Karthic Raoapidays
apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020
The Rise of GraphQL for database APIs
Karthic Rao, Founder of Pixelbytestudio
What if you could create a GraphQL API by combining many smaller APIs? That's what we're aiming for with schema stitching, the new feature in the Apollo graphql-tools package.
GraphQL is an application layer query language developed by Facebook that allows clients to define queries for retrieving multiple resources from an API in a single request. It uses a type system and schema to define the data and operations available. GraphQL aims to solve issues with REST APIs like over-fetching and under-fetching data by allowing clients to specify exactly what data they need.
In this presentation, Suraj Kumar Paul of Valuebound has walked us through GraphQL. Founded by Facebook in 2012, GraphQL is a data query language that provides an alternative to REST and web service architectures.
Here he has discussed core ideas of GraphQL, limitations of RESTful APIs, operations, arguments, fragmentation, variables, mutations etc.
----------------------------------------------------------
Get Socialistic
Our website: http://valuebound.com/
LinkedIn: http://bit.ly/2eKgdux
Facebook: https://www.facebook.com/valuebound/
This document provides an introduction and overview of GraphQL, including:
- A brief history of GraphQL and how it was created by Facebook and adopted by other companies.
- How GraphQL provides a more efficient alternative to REST APIs by allowing clients to specify exactly the data they need in a request.
- Some key benefits of GraphQL like its type system, declarative data fetching, schema stitching, introspection, and versioning capabilities.
- Some disadvantages like potential complexity in queries and challenges with rate limiting.
GraphQL is a query language for APIs that allows flexible querying of data from a server. It was originally created by Facebook in 2012 and open sourced in 2015. Some key benefits of GraphQL include allowing apps to control the specific data received from servers instead of receiving all possible data like with REST APIs, and GraphQL queries mirroring the response structure. GraphQL schemas define query and mutation parameters as well as return data types.
05Nov13 Webinar: Introducing Revolution R Enterprise 7 - The Big Data Big Ana...Revolution Analytics
The document announces the release of Revolution R Enterprise 7 on November 5th. Key new features in RRE 7 include support for decision forests and tree visualization, stepwise logistic and generalized linear models, integration with additional data sources like HP Vertica and Teradata Aster, a new business user interface, inside-Hadoop deployment, and in-database deployment. RRE 7 also includes performance enhancements to R and new capabilities for scalable statistical modeling, machine learning, BI integration, and multi-node package management.
In this talk, I go over some of the concerns people initially have when adding GraphQL to their existing frontends and backends, and cover some of the tools that can be used to address them.
GraphQL: Enabling a new generation of API developer toolsSashko Stubailo
This document discusses the history and benefits of GraphQL as an API layer between frontends and backends. It provides examples of how GraphQL allows flexible queries to get only necessary data, and describes tools like GraphiQL, static query analysis, code generation and dev tools that improve the developer experience. GraphQL provides a shared language for frontend and backend teams to communicate about data requirements and optimize performance.
This document discusses GraphQL, a query language for APIs. It describes what GraphQL is, how it works, and its benefits. Specifically:
- GraphQL allows clients to specify the exact data they need in a single request, fetching multiple related resources from existing data sources like databases or REST APIs.
- It uses a type system with a schema definition language to provide a complete and understandable description of the available data in an API.
- Adopting GraphQL can improve development workflows by encouraging schema-first development, decoupling teams, enabling flexibility, and making it easier to experiment and adapt to users' needs.
GraphQL is a wonderful abstraction for describing and querying data. Apollo is an ambitious project to help you build apps with GraphQL. In this talk, we'll go over how all the parts—Client, Server, Dev Tools, Codegen, and more—create an end-to-end experience for building apps on top of any data.
## Detailed description
In today's development ecosystem, there are tons of options for almost every part of your application development process: UI rendering, styling, server side rendering, build systems, type checking, databases, frontend data management, and more. However, there's one part of the stack that hasn't gotten as much love in the last decade, because it usually falls in the cracks between frontend and backend developers: Data fetching.
The most common way to load data in apps today is to use a REST API on the server and manage the data manually on the client. Whether you're using Redux, MobX, or something else, you're usually doing everything yourself—deciding when to load data, how to keep it fresh, updating the store after sending updates to the server, and more. But if you're trying to develop the best user experience for your app, all of that gets in the way; you shouldn't have to become a systems engineer to create a great frontend. The Apollo project is based on the belief that data loading doesn't have to be complicated; instead, you should be able to easily get the data you want, when you want it, and it should be managed for you just like React manages updating your UI.
Because data loading touches both the frontend and backend of your app, GraphQL and Apollo have to include many parts to fulfill that promise of being able to seamlessly connect your data together. First, we need client libraries not only for React and JavaScript, but also for native iOS and Android. Then, we must bring server-side support for GraphQL queries, mutations, and most recently subscriptions to every server technology and make those servers easier to write. And finally, we want not only all of the tools that people are used to with REST APIs, but many more thanks to all of the capabilities enabled by GraphQL.
In this talk, we'll go over all of the parts of a GraphQL-oriented app architecture, and how different GraphQL and Apollo technologies come together to solve all of the parts of data loading and management for React developers.
GraphQL across the stack: How everything fits togetherSashko Stubailo
My talk from GraphQL Summit 2017!
In this talk, I talk about a future for GraphQL which builds on the idea that GraphQL enables lots of tools to work together seamlessly across the stack. I present this through the lens of 3 examples: Caching, performance tracing, and schema stitching.
Stay tuned for the video recording from GraphQL Summit!
Graph ql vs rest api - Seven Peaks Software (Node.JS Meetup 18 nov 2021)Seven Peaks Speaks
Georgii, our Senior full-stack developer, has over 12 years of experience working on both sides of web applications on the front-end and back-end.
Georgii was walk you through on GraphQL VS Rest API on our last Node.JS Meetup. There are several ways to create backend APIs. REST is the most common choice but it has some limitations. It’s where GraphQL comes as an alternative to REST.
For more info about Seven Peaks Software:
https://lnkd.in/g2jMsDy
This document discusses using streaming APIs like Kafka in production environments. It begins with an introduction to Kafka including topics, partitions, brokers, producers and consumers. It then discusses how Kafka can be used with microservices for improved decoupling and scalability with an event-driven approach. Kafka Streams and streaming APIs are presented as a way to include streaming data. Several use cases from industries like travel, transportation, finance and news are described that demonstrate how companies leverage Kafka for applications such as predictive maintenance, real-time data processing, and serving as a single source of truth. The presentation concludes with a demo of a simple microservices application using Kafka.
GraphQL: The Missing Link Between Frontend and Backend DevsSashko Stubailo
Engineers working on backend data services are often focused on operational concerns like data consistency, reliability, uptime, and storage efficiency. Because each situation calls for a specific set of tradeoffs, one organization can end up with a diverse set of backend databases and services. For the people building the UI and frontend API layers, this diversity can quickly become an issue, especially if the same client needs to call into multiple backends or fetch related objects across different data sources.
GraphQL is a language-agnostic API gateway technology designed precisely to solve this mismatch between backend and frontend requirements. It provides a highly structured, yet flexible API layer that lets the client specify all of its data requirements in one GraphQL query, without needing to know about the backend services being accessed. Better yet, because of the structured, strongly typed nature of both GraphQL queries and APIs, it's possible to quickly get critical information, such as which objects and fields are accessed by which frontends, which clients will be affected by specific changes to the backend, and more.
In this talk, I'll explain what GraphQL is, what data management problems it can solve in an organization, and how you can try it today.
apidays LIVE Paris - GraphQL meshes by Jens Neuseapidays
apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020
GraphQL meshes
Jens Neuse, Founder of Wundergraph
Your Roadmap for An Enterprise Graph Strategy Neo4j
This document provides a roadmap for developing an enterprise graph strategy. It outlines key steps including building a proof of concept graph using a small dataset, designing the graph schema, and creating demo applications. The roadmap involves discussions with stakeholders to understand use cases and business needs. Example graph schemas are provided for customer 360, supply chain, and master data management. The goal is to solve a "graphy problem" and showcase the value of connected data through new insights and analytics.
What if you could create a GraphQL API by combining many smaller APIs? That's what we're aiming for with schema stitching, the new feature in the Apollo graphql-tools package.
GraphQL is an application layer query language developed by Facebook that allows clients to define queries for retrieving multiple resources from an API in a single request. It uses a type system and schema to define the data and operations available. GraphQL aims to solve issues with REST APIs like over-fetching and under-fetching data by allowing clients to specify exactly what data they need.
In this presentation, Suraj Kumar Paul of Valuebound has walked us through GraphQL. Founded by Facebook in 2012, GraphQL is a data query language that provides an alternative to REST and web service architectures.
Here he has discussed core ideas of GraphQL, limitations of RESTful APIs, operations, arguments, fragmentation, variables, mutations etc.
----------------------------------------------------------
Get Socialistic
Our website: http://valuebound.com/
LinkedIn: http://bit.ly/2eKgdux
Facebook: https://www.facebook.com/valuebound/
This document provides an introduction and overview of GraphQL, including:
- A brief history of GraphQL and how it was created by Facebook and adopted by other companies.
- How GraphQL provides a more efficient alternative to REST APIs by allowing clients to specify exactly the data they need in a request.
- Some key benefits of GraphQL like its type system, declarative data fetching, schema stitching, introspection, and versioning capabilities.
- Some disadvantages like potential complexity in queries and challenges with rate limiting.
GraphQL is a query language for APIs that allows flexible querying of data from a server. It was originally created by Facebook in 2012 and open sourced in 2015. Some key benefits of GraphQL include allowing apps to control the specific data received from servers instead of receiving all possible data like with REST APIs, and GraphQL queries mirroring the response structure. GraphQL schemas define query and mutation parameters as well as return data types.
05Nov13 Webinar: Introducing Revolution R Enterprise 7 - The Big Data Big Ana...Revolution Analytics
The document announces the release of Revolution R Enterprise 7 on November 5th. Key new features in RRE 7 include support for decision forests and tree visualization, stepwise logistic and generalized linear models, integration with additional data sources like HP Vertica and Teradata Aster, a new business user interface, inside-Hadoop deployment, and in-database deployment. RRE 7 also includes performance enhancements to R and new capabilities for scalable statistical modeling, machine learning, BI integration, and multi-node package management.
In this talk, I go over some of the concerns people initially have when adding GraphQL to their existing frontends and backends, and cover some of the tools that can be used to address them.
GraphQL: Enabling a new generation of API developer toolsSashko Stubailo
This document discusses the history and benefits of GraphQL as an API layer between frontends and backends. It provides examples of how GraphQL allows flexible queries to get only necessary data, and describes tools like GraphiQL, static query analysis, code generation and dev tools that improve the developer experience. GraphQL provides a shared language for frontend and backend teams to communicate about data requirements and optimize performance.
This document discusses GraphQL, a query language for APIs. It describes what GraphQL is, how it works, and its benefits. Specifically:
- GraphQL allows clients to specify the exact data they need in a single request, fetching multiple related resources from existing data sources like databases or REST APIs.
- It uses a type system with a schema definition language to provide a complete and understandable description of the available data in an API.
- Adopting GraphQL can improve development workflows by encouraging schema-first development, decoupling teams, enabling flexibility, and making it easier to experiment and adapt to users' needs.
GraphQL is a wonderful abstraction for describing and querying data. Apollo is an ambitious project to help you build apps with GraphQL. In this talk, we'll go over how all the parts—Client, Server, Dev Tools, Codegen, and more—create an end-to-end experience for building apps on top of any data.
## Detailed description
In today's development ecosystem, there are tons of options for almost every part of your application development process: UI rendering, styling, server side rendering, build systems, type checking, databases, frontend data management, and more. However, there's one part of the stack that hasn't gotten as much love in the last decade, because it usually falls in the cracks between frontend and backend developers: Data fetching.
The most common way to load data in apps today is to use a REST API on the server and manage the data manually on the client. Whether you're using Redux, MobX, or something else, you're usually doing everything yourself—deciding when to load data, how to keep it fresh, updating the store after sending updates to the server, and more. But if you're trying to develop the best user experience for your app, all of that gets in the way; you shouldn't have to become a systems engineer to create a great frontend. The Apollo project is based on the belief that data loading doesn't have to be complicated; instead, you should be able to easily get the data you want, when you want it, and it should be managed for you just like React manages updating your UI.
Because data loading touches both the frontend and backend of your app, GraphQL and Apollo have to include many parts to fulfill that promise of being able to seamlessly connect your data together. First, we need client libraries not only for React and JavaScript, but also for native iOS and Android. Then, we must bring server-side support for GraphQL queries, mutations, and most recently subscriptions to every server technology and make those servers easier to write. And finally, we want not only all of the tools that people are used to with REST APIs, but many more thanks to all of the capabilities enabled by GraphQL.
In this talk, we'll go over all of the parts of a GraphQL-oriented app architecture, and how different GraphQL and Apollo technologies come together to solve all of the parts of data loading and management for React developers.
GraphQL across the stack: How everything fits togetherSashko Stubailo
My talk from GraphQL Summit 2017!
In this talk, I talk about a future for GraphQL which builds on the idea that GraphQL enables lots of tools to work together seamlessly across the stack. I present this through the lens of 3 examples: Caching, performance tracing, and schema stitching.
Stay tuned for the video recording from GraphQL Summit!
Graph ql vs rest api - Seven Peaks Software (Node.JS Meetup 18 nov 2021)Seven Peaks Speaks
Georgii, our Senior full-stack developer, has over 12 years of experience working on both sides of web applications on the front-end and back-end.
Georgii was walk you through on GraphQL VS Rest API on our last Node.JS Meetup. There are several ways to create backend APIs. REST is the most common choice but it has some limitations. It’s where GraphQL comes as an alternative to REST.
For more info about Seven Peaks Software:
https://lnkd.in/g2jMsDy
This document discusses using streaming APIs like Kafka in production environments. It begins with an introduction to Kafka including topics, partitions, brokers, producers and consumers. It then discusses how Kafka can be used with microservices for improved decoupling and scalability with an event-driven approach. Kafka Streams and streaming APIs are presented as a way to include streaming data. Several use cases from industries like travel, transportation, finance and news are described that demonstrate how companies leverage Kafka for applications such as predictive maintenance, real-time data processing, and serving as a single source of truth. The presentation concludes with a demo of a simple microservices application using Kafka.
GraphQL: The Missing Link Between Frontend and Backend DevsSashko Stubailo
Engineers working on backend data services are often focused on operational concerns like data consistency, reliability, uptime, and storage efficiency. Because each situation calls for a specific set of tradeoffs, one organization can end up with a diverse set of backend databases and services. For the people building the UI and frontend API layers, this diversity can quickly become an issue, especially if the same client needs to call into multiple backends or fetch related objects across different data sources.
GraphQL is a language-agnostic API gateway technology designed precisely to solve this mismatch between backend and frontend requirements. It provides a highly structured, yet flexible API layer that lets the client specify all of its data requirements in one GraphQL query, without needing to know about the backend services being accessed. Better yet, because of the structured, strongly typed nature of both GraphQL queries and APIs, it's possible to quickly get critical information, such as which objects and fields are accessed by which frontends, which clients will be affected by specific changes to the backend, and more.
In this talk, I'll explain what GraphQL is, what data management problems it can solve in an organization, and how you can try it today.
apidays LIVE Paris - GraphQL meshes by Jens Neuseapidays
apidays LIVE Paris - Responding to the New Normal with APIs for Business, People and Society
December 8, 9 & 10, 2020
GraphQL meshes
Jens Neuse, Founder of Wundergraph
Your Roadmap for An Enterprise Graph Strategy Neo4j
This document provides a roadmap for developing an enterprise graph strategy. It outlines key steps including building a proof of concept graph using a small dataset, designing the graph schema, and creating demo applications. The roadmap involves discussions with stakeholders to understand use cases and business needs. Example graph schemas are provided for customer 360, supply chain, and master data management. The goal is to solve a "graphy problem" and showcase the value of connected data through new insights and analytics.
Best practices: embedding interactive reports & visualizations in your appTIBCO Jaspersoft
Topics covered in this session:
- Levels of embedding (options for embedding)
- Embedding with Visualize.js
- How embedding works in the demo app
- Best practices & key takeaways
Anand Gupta has over 13 years of experience as a SAP ABAP consultant. He has extensive experience implementing SAP ERP, S/4HANA, and CRM projects for various clients. Some of his responsibilities include requirements gathering, solution design, development, testing, go-live preparation, and post go-live support. He has strong skills in ABAP, HANA, Fiori, WebIDE, and SAP Cloud Platform.
Deploying Machine Learning in production without servers - #serverlessCPHDamien Cavaillès
Try it now ! : https://welovedevs.com/app/companies
Learn more :
Serverless CPH : https://serverlesscph.dk/
WeLoveDevs.com : https://welovedevs.com/
Spread the love <span class="emoji-outer emoji-sizer"><span class="emoji-inner" style="background: url(chrome-extension://immhpnclomdloikkpcefncmfgjbkojmh/emoji-data/sheet_apple_32.png);background-position:50% 28.025851938895418%;background-size:5418.75% 5418.75%" data-codepoints="1f499"></span></span>
Your Roadmap for An Enterprise Graph StrategyNeo4j
This document provides a roadmap for developing an enterprise graph strategy with the following key steps:
1. Design and build a proof-of-concept graph using a small local dataset to demonstrate graph capabilities.
2. Present use cases and example queries to business stakeholders to validate the graph model and gather feedback.
3. Design the production graph schema and build APIs/services to integrate data from multiple sources.
4. Deploy the graph in the cloud and develop applications and reports to mobilize enterprise data using the graph.
This resume is for Alpana Chaphalkar. She is currently studying Applied Computer Science at SRH Hochschule Heidelberg in Germany and has work experience in web application development, automation testing, and SAP technologies. Her technical skills include programming languages like Java, C++, PHP, and databases like MySQL, Oracle, and SAP HANA. She has completed several projects related to lending, invoice management, real estate, and healthcare.
Your Roadmap for An Enterprise Graph StrategyNeo4j
This document provides a roadmap for developing an enterprise graph strategy with the following key steps:
1) Identify a "graphy problem" that a graph database could help solve based on input from business stakeholders.
2) Design and build a proof-of-concept graph using a local Neo4j instance to model sample data and write example queries.
3) Pick and build a demo application to showcase the value of the graph to stakeholders based on the sample data and queries.
GraphQL Munich Meetup #1 - How We Use GraphQL At CommercetoolsNicola Molinari
The document describes commercetools' experience with adopting GraphQL for their merchant center application. They were initially fetching category data with multiple REST requests, but were able to fetch it in one GraphQL query along with additional fields like number of subcategories and products. This solved a performance issue and allowed them to easily extend their API. They also migrated other parts of their client to use GraphQL, reducing network requests and complexity. Overall, GraphQL allowed them to optimize queries and extend their API with minimal effort.
This introduction to graph databases is specifically designed for Enterprise Architects who need to map business requirements to architectural components like graph databases. It explains how and why graphs matter for Enterprise Architecture and reviews the architectural differences between relational and graph models.
Qlik and Confluent Success Stories with Kafka - How Generali and Skechers Kee...HostedbyConfluent
Converting production databases into live data streams for Apache Kafka can be labor intensive and costly. As Kafka architectures grow, complexity also rises as data teams begin to configure clusters for redundancy, partitions for performance, as well as for consumer groups for correlated analytics processing. In this breakout session, you’ll hear data streaming success stories from Generali and Skechers that leverage Qlik Data Integration and Confluent. You’ll discover how Qlik’s data integration platform lets organizations automatically produce real-time transaction streams into Kafka, Confluent Platform, or Confluent Cloud, deliver faster business insights from data, enable streaming analytics, as well as streaming ingestion for modern analytics. Learn how these customer use Qlik and Confluent to: - Turn databases into live data feeds - Simplify and automate the real-time data streaming process - Accelerate data delivery to enable real-time analytics Learn how Skechers and Generali breathe new life into data in the cloud, stay ahead of changing demands, while lowering over-reliance on resources, production time and costs.
SPFx- A modern development model for SharePointKirti Prajapati
The document discusses the SharePoint Framework (SPFx) which is a new development model for building client-side SharePoint solutions using modern web technologies like HTML, CSS and JavaScript. It provides an overview of SPFx including its key features such as being framework agnostic and enabling responsive designs. The document compares SPFx to traditional SharePoint development and the add-in model, highlighting benefits like running solutions in no-script sites. It demonstrates the development tools, build process and deployment options for SPFx client-side web parts.
GraphQL Insights Deck ( Sabre_GDG - Sept 2023).pdfJames Anderson
GraphQL - Industry insights on the rise of the supergraph
Exploring what we’ve learned from hundreds of organizations transforming their business and customer experiences with GraphQL & the supergraph.
In his talk and Q&A session, Dan Boerner will share insights and best practices from his experience working with hundreds of companies working to unblock their teams and backlogs with the supergraph—a new layer of the stack. He’ll share real-world examples to explore why GraphQL and its architectural advantages must be coupled with leadership, vision, team empowerment, and mindset shifts to truly transform the way enterprises build, deliver and organize themselves to create digital products. As Apollo’s Graph Champion, Dan leads Apollo’s community of 800+ GraphQL leaders from 350 companies. Before joining Apollo, Dan led Expedia Group’s effort to radically accelerate the delivery of improved customer experiences with a company-wide supergraph.
Dan is passionate about helping graph champions harness the transformative power of the supergraph to improve product development and digital customer experiences. At Apollo, he leads a community of hundreds of GraphQL champions working to drive transformation within their organizations. He joined Apollo after a long tenure at Expedia Group where he led the effort to create a company-wide supergraph transforming product development and delivery, and enabling the organization to roll out their new trips platform in 1 year instead of 3.
https://youtu.be/0Vucl1qVecM
SVA discusses the opportunities and challenges they have encountered during their journey with customers, using mainframe offloading projects as an example.
This project report describes the development of an e-commerce website. It discusses the client-side and server-side programming used to build the website. The website uses an MVC framework with models to store data, views to display the user interface, and controllers to handle user requests. It also describes the hardware and software requirements including a web server, database, programming languages, and browser capabilities needed to implement the website. Screenshots of the website and coding examples are provided. The report concludes with future enhancements and a references section.
- Nilesh Umaretiya is a skilled software developer with over 4 years of experience developing applications using technologies like C#.NET, VB.NET, SQL Server, and SAP PowerBuilder.
- He has extensive experience developing 3-tier web and desktop applications for clients, including an ERP system and restaurant management system.
- His skills also include website design, mobile app design, and graphic design skills with tools like Photoshop and CorelDraw.
The document discusses microservices as an alternative to monolithic applications. It notes that monoliths can be difficult to scale, diagnose issues within, introduce changes to, and fail globally. Microservices are proposed as a solution by separating applications into smaller, independent services with distinct purposes. This allows for workload partitioning, parallel development, isolated failures, and more autonomy. However, microservices also present challenges around distributed systems and increased complexity. The document recommends starting with a modular monolith and gradually splitting services, using practices like event-driven architecture and contract testing.
The document outlines the microservices architecture of Enpal which includes 5 front end apps, 25+ microservices, 4 external partners, and 9+ SaaS tools. It discusses the benefits of using a microservices approach to parallelize development and manage risk. It also explains why an event-driven approach was chosen from the beginning given Enpal's distributed data across 30+ existing systems and long-term customer contracts. Finally, it acknowledges that every application has inherent complexity and the goal is to design it so that complexity is properly managed.
The document discusses the Berlin JavaScript community and its goals to facilitate knowledge sharing and support engineers in representing Klarna Engineering outside the company. It outlines a roadmap to define regular online JavaScript focused events in Q1 2020, host some meetups with Node.js Berlin, CodePen Berlin, and ReactJS in Q2 2020, and kick off a collective Berlin Culture group and regular online events while starting to invite external events and publish a list of Berlin events in Q3 2020.
El documento describe el proceso de segmentación de clientes realizado por BMDG Partners para una empresa de venta minorista llamada "Tu Carrito Musical". El objetivo era conocer mejor la base de clientes mediante técnicas de clustering y machine learning. Se recopilaron y limpiaron datos de 147.000 clientes, 459.000 productos y 800.000 transacciones. Luego se crearon características y se aplicaron técnicas como PCA y GMM para segmentar a los clientes en grupos. El resultado final fue una segmentación detallada de la base de clientes que permitirá
Web technologies are evolving blazingly fast and so it is AWS. Part of this evolution is GraphQL and the AWS team already took notice. In March 2019 AWS joined the GraphQL Foundation, double betting on the technology as an ingredient for great applications.
Designing GraphQL API's for scale on AWS is a challenging and exciting process, in this talk, we will talk about some key learnings from my past two years and how to overcome several challenges of this process.
The document discusses using blockchain identity and self-sovereign identity protocols to securely verify credentials in real-world scenarios. It proposes demonstrating this on a Raspberry Pi by creating a single sign-on application that can validate a user's credentials through the Pi and trigger real-world actions. A potential demo case is described for carsharing, accessing locations, or using age-restricted vending machines through verified digital identity.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
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.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
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
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.
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
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
9. Motivation - Legacy Application Stack
16.10.17 9
- Mostly MVC(Spring/Rails) with REST Endpoints
- Server-Side rendered HTML with Ajax calls
- One React JS Front End Client
10. Motivation - Requirements
16.10.17 10
- Complex UI
- Public API
- Faster Development
- Reduce integration effort
- Reduce project onboarding
- Performance
11. Motivation - Solutions?
16.10.17 11
Complex UI
- Experience with React.JS for over a year
- Future Implementation in most of the clients
- Developer team React knowledge
12. Motivation - Solutions?
16.10.17 12
Public API
- Pure REST standard is hard to implement
- Unique URI´s, request methods has to have a meaning(PUT or POST?)
- Need a Gateway for security and performance
/product or /products
PUT or POST
which Content-Type ?
26. Transition: GraphQL Schema
Prefer building a Graph-QL schema that describes
how clients use the data,
rather than mirroring the legacy database schema.
37. Challenges: Thinking in Graphs
06.07.17 lokalleads 37
In the REST implementation data is modeled in terms of
network services.
/campaigns
/campaigns_and_metrics
/campaigns_and_statistics
38. Challenges: Thinking in Graphs
06.07.17 lokalleads 38
With GraphQL, you model your business domain as a graph.
/campaigns
/campaigns_and_metrics
/campaigns_and_statistics