Name: GraphQL Galaxy 2021
Start: 2021-12-09T15:00:00.000Z
End: 2021-12-10T20:00:00.000Z

Vlad Dumitrica

Daria Shabala

Ricardo Machado

Robert

Oscar Pagani

Phiroze 

Myron Davis

Norm Crandall

Creatopy Tech

yuya-soneda

Simon Flack

Hannah Vivian Shaw

Aman Beg

Ian Sutherland

Rahul Rana

Christian Guy

Serge Bedzhyk

Max Medina

Rishi Narang

mickael

Martyna Skup

Andres Pineda

Filip Michalowski

Carlo Straccialini

Adrian Marte

Anthony Miller

Michael Edelman 

Shingo Ichikawa

Brett Leibowitz

Murtaza Bagwala

Janko Vrbnjak

Mohammed

Mary Etokwudo

Todos amamos GraphQL, pero puede ser desalentador poner en marcha un servidor y mantener tu código organizado, mantenible y testeable a largo plazo. ¡No más! Ven a ver cómo paso de un directorio vacío a una API GraphQL completamente desarrollada en cuestión de minutos. Además, verás lo fácil que es usar y crear directivas para limpiar aún más tu código. ¡Vas a amar aún más GraphQL una vez que hagas las cosas Redwood Easy! <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

De GraphQL Zero a GraphQL Hero con RedwoodJS

Tom Pressenwurter introduces Redwood.js, a full stack app framework for building GraphQL APIs easily and maintainably. He demonstrates a Redwood.js application with a React-based front end and a Node.js API. Redwood.js offers a simplified folder structure and schema for organizing the application. It provides easy data manipulation and CRUD operations through GraphQL functions. Redwood.js allows for easy implementation of new queries and directives, including authentication and limiting access to data. It is a stable and production-ready framework that integrates well with other front-end technologies.

We all love GraphQL, but it can be daunting to get a server up and running and keep your code organized, maintainable, and testable over the long term. No more! Come watch as I go from an empty directory to a fully fledged GraphQL API in minutes flat. Plus, see how easy it is to use and create directives to clean up your code even more. You're gonna love GraphQL even more once you make things Redwood Easy! <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

From GraphQL Zero to GraphQL Hero with RedwoodJS

Tom Preston-Werner

El Guild ha lanzado recientemente Envelop - un nuevo y moderno Framework de Servidor GraphQL y sistema de plugins. En esta charla compartiré una breve descripción de Envelop y por qué probablemente deberías actualizar tu servidor GraphQL existente a él. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Baterías Incluidas Reimaginadas - El Resurgimiento de GraphQL Yoga

Envelope is a powerful GraphQL plugin system that simplifies server development and allows for powerful plugin integration. It provides conformity for large corporations with multiple GraphQL servers and can be used with various frameworks. Envelope acts as the Babel of GraphQL, allowing the use of non-spec features. The Guild offers GraphQL Hive, a service similar to Apollo Studio, and encourages collaboration with other frameworks and languages.

The Guild has recently released Envelop - a new, modern GraphQL Server Framework and plugin system. In this talk I’ll share a brief overview of Envelop and why you should probably upgrade your existing GraphQL server to it. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Batteries Included Reimagined - The Revival of GraphQL Yoga

Uri Goldshtein

Adoptando GraphQL en una Empresa

Today's Talk is about adopting GraphQL in an enterprise. It discusses the challenges of using REST APIs and the benefits of GraphQL. The Talk explores different approaches to adopting GraphQL, including coexistence with REST APIs. It emphasizes the power of GraphQL and provides tips for successful adoption. Overall, the Talk highlights the advantages of GraphQL in terms of efficiency, collaboration, and control over APIs.

Adopting GraphQL in an Enterprise

Shruti Kapoor

Excited for panel discussion. Introducing panelists with significant GraphQL experience. Evolution of GraphQL working group from internal to open-source collaboration. Formalization of collaboration processes. Monthly meetings of the GraphQL Working Group. Establishment of committee for company sanity. Community engagement guidelines and significant contributions. Involvement process in the GraphQL Working Group. Transparency and engagement practices. Exciting developments in client-controlled nullability and Defer and Stream in GraphQL. Innovations within the working group and ecosystem. Formation of GraphQL Foundation and legal structuring. Role of program manager in GraphGo Foundation. Crucial role of technical steering committee in decision-making and community representation.

Moderator - Uri Goldshtein  Panelists:Lee ByronSasha SolomonBenjieBrielle Harrison <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Panel Discussion: GraphQL Working Group

Lee Byron

Sasha Solomon

Benjie

Brielle Harrison

¿Alguna vez has pensado en construir algo que no requiera mucho código de plantilla con un tamaño de paquete pequeño? En esta masterclass, Scott Spence irá desde el hola mundo hasta cubrir el enrutamiento y el uso de endpoints en SvelteKit. Configurarás una API de GraphQL en el backend y luego usarás consultas de GraphQL con SvelteKit para mostrar los datos de la API de GraphQL. Construirás un proyecto rápido y seguro que utiliza las características de SvelteKit, y luego lo desplegarás como un sitio completamente estático. Este curso es para los curiosos de Svelte que no han tenido una experiencia extensa con SvelteKit y quieren una comprensión más profunda de cómo usarlo en aplicaciones prácticas. Tabla de contenidos: - Inicio e introducción a Svelte - Inicializar el proyecto frontend - Recorrido por el proyecto esqueleto de SvelteKit - Configurar el proyecto backend - Consultar datos con GraphQL - Recuperación de datos en el frontend con GraphQL - Estilización - Directivas de Svelte - Enrutamiento en SvelteKit - Endpoints en SvelteKit - Despliegue en Netlify - Navegación - Mutaciones en GraphCMS - Envío de mutaciones GraphQL a través de SvelteKit - Preguntas y respuestas <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Construir con SvelteKit y GraphQL

This workshop focuses on using Svelte and SvelteKit to build a GraphQL-based CMS. It covers project setup, configuration, and working with GraphCMS. The workshop also explores fetching data from endpoints, styling with SvelteAdd, and working with blog post data and routing. Troubleshooting Tailwind CSS configuration and deployment with Versel are also discussed.

Have you ever thought about building something that doesn't require a lot of boilerplate with a tiny bundle size? In this workshop, Scott Spence will go from hello world to covering routing and using endpoints in SvelteKit. You'll set up a backend GraphQL API then use GraphQL queries with SvelteKit to display the GraphQL API data. You'll build a fast secure project that uses SvelteKit's features, then deploy it as a fully static site. This course is for the Svelte curious who haven't had extensive experience with SvelteKit and want a deeper understanding of how to use it in practical applications. Table of contents: - Kick-off and Svelte introduction - Initialise frontend project - Tour of the SvelteKit skeleton project - Configure backend project - Query Data with GraphQL - Fetching data to the frontend with GraphQL - Styling - Svelte directives - Routing in SvelteKit - Endpoints in SvelteKit - Deploying to Netlify - Navigation - Mutations in GraphCMS - Sending GraphQL Mutations via SvelteKit - Q&amp;A <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Build with SvelteKit and GraphQL

Scott Spence

The Graph es un protocolo de indexación para consultar redes como Ethereum, IPFS y otras blockchains. Cualquiera puede construir y publicar APIs abiertas, llamadas subgraphs, haciendo que los datos sean fácilmente accesibles. En esta masterclass aprenderás cómo construir un subgraph que indexa datos de blockchain de NFT desde el contrato inteligente de Foundation. Desplegaremos la API y aprenderemos cómo realizar consultas para recuperar datos utilizando varios tipos de patrones de acceso a datos, implementando filtros y ordenamiento. Al final de la masterclass, deberías entender cómo construir y desplegar APIs eficientes en The Graph para indexar datos de cualquier contrato inteligente desplegado en Ethereum. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Construyendo APIs de GraphQL sobre Ethereum con The Graph

This workshop focuses on building a GraphQL API on top of the Ethereum blockchain, using the Graph Protocol. The Graph provides a decentralized approach to data querying and storage, allowing developers to build decentralized APIs that read and index blockchain data. The workshop covers topics such as creating subgraphs, defining data models, handling events, and deploying and querying the subgraph. Participants learn how to interact with smart contracts and the Graph Node, and how to customize queries to retrieve specific information.

The Graph is an indexing protocol for querying networks like Ethereum, IPFS, and other blockchains. Anyone can build and publish open APIs, called subgraphs, making data easily accessible. In this workshop you’ll learn how to build a subgraph that indexes NFT blockchain data from the Foundation smart contract. We’ll deploy the API, and learn how to perform queries to retrieve data using various types of data access patterns, implementing filters and sorting. By the end of the workshop, you should understand how to build and deploy performant APIs to The Graph to index data from any smart contract deployed to Ethereum. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Building GraphQL APIs on top of Ethereum with The Graph

Nader Dabit

GraphQL abstrae las llamadas a la API de aguas abajo desde el frontend y todo lo que el frontend tiene que hacer es solicitar campos en una consulta que son necesarios para la representación del componente. El frontend no sabe que un campo correspondiente puede resultar en una llamada a la API o en cálculos pesados en el lado del backend. Esta abstracción afecta el rendimiento cuando el esquema de GraphQL no está estructurado correctamente. Veamos un ejemplo para entender más:Aquí está la consulta para obtener las habitaciones disponibles para un hotel:hotel (id: $hotelId) id rooms id type name El frontend no sabe que el campo rooms dentro de la consulta hotel disparará otra llamada a la API incluso si el campo type se obtendrá de otro punto final de la API. Estas llamadas anidadas a la API empeoran el rendimiento si hay más habitaciones. Podemos resolver esto de manera efectiva estructurando bien el esquema y usando cargadores de datos.

Rendimiento y Monitoreo de GraphQL

This Talk explores the performance implications of using GraphQL in a hotel property management system. It discusses optimizing GraphQL API calls, schema design, and caching using Data Loader. The use of automatic persisted queries and caching can improve performance. The impact of response size and pagination in GraphQL queries is also addressed. Additionally, the Talk emphasizes the importance of monitoring and testing queries, as well as improving perceived performance through visual feedback.

GraphQL abstracts the downstream API calls from the frontend and all that frontend has to do is request fields in a query that are required for the rendering of the component. The frontend is not aware that a corresponding field might result in an API call or heavy computations on the backend side. This abstraction hits the performance when the GraphQL schema is not structured properly. Let's take an example to understand more:Here's the query to get available rooms for a hotel:hotel (id: $hotelId) { id rooms { id type name } }The frontend doesn't know that the rooms field inside the query hotel will fire another API call even type field would be fetched from another API endpoint. These nested API calls worsen the performance if there are more rooms. We can effectively solve this structuring the schema well and using data loaders.

GraphQL Performance and Monitoring

Ankita Masand

En Shopify a gran escala, resolvemos algunos problemas bastante difíciles. En este masterclass, cinco oradores diferentes describirán algunos de los desafíos que hemos enfrentado y cómo los hemos superado. Tabla de contenidos: 1 - El infame problema "N+1": Jonathan Baker - Vamos a hablar sobre qué es, por qué es un problema y cómo Shopify lo maneja a gran escala en varios APIs de GraphQL. 2 - Contextualizando APIs de GraphQL: Alex Ackerman - Cómo y por qué decidimos usar directivas. Compartiré qué son las directivas, qué directivas están disponibles de forma predeterminada y cómo crear directivas personalizadas. 3 - Consultas de GraphQL más rápidas para clientes móviles: Theo Ben Hassen - A medida que tu aplicación móvil crece, también lo harán tus consultas de GraphQL. En esta charla, repasaré diversas estrategias para hacer que tus consultas sean más rápidas y efectivas. 4 - Construyendo el producto del futuro hoy: Greg MacWilliam - Cómo Shopify adopta las características futuras en el código actual. 5 - Gestión efectiva de APIs grandes: Rebecca Friedman - Tenemos miles de desarrolladores en Shopify. Veamos cómo estamos asegurando la calidad y consistencia de nuestras APIs de GraphQL con tantos colaboradores.<a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Problemas difíciles de GraphQL en Shopify

The Workshop covered various topics related to GraphQL at Shopify, including the Nplusone problem, batch loading with lazy resolvers, contextualizing GraphQL APIs with directives, optimizing GraphQL for mobile, managing large GraphQL APIs, and handling deprecated fields and nullability. The speakers shared insights and solutions to these challenges, such as using Active Record Preloading, GraphQL Batch library, and custom directives. They also discussed the importance of measuring performance, pagination design, and parallel querying for mobile optimization. Overall, the Workshop provided valuable information on improving GraphQL performance, API design, and versioning strategies.

At Shopify scale, we solve some pretty hard problems. In this workshop, five different speakers will outline some of the challenges we’ve faced, and how we’ve overcome them. Table of contents: 1 - The infamous "N+1" problem: Jonathan Baker - Let's talk about what it is, why it is a problem, and how Shopify handles it at scale across several GraphQL APIs. 2 - Contextualizing GraphQL APIs: Alex Ackerman - How and why we decided to use directives. I’ll share what directives are, which directives are available out of the box, and how to create custom directives. 3 - Faster GraphQL queries for mobile clients: Theo Ben Hassen - As your mobile app grows, so will your GraphQL queries. In this talk, I will go over diverse strategies to make your queries faster and more effective. 4 - Building tomorrow’s product today: Greg MacWilliam - How Shopify adopts future features in today’s code. 5 - Managing large APIs effectively: Rebecca Friedman - We have thousands of developers at Shopify. Let’s take a look at how we’re ensuring the quality and consistency of our GraphQL APIs with so many contributors. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Hard GraphQL Problems at Shopify

Rebecca Friedman

Jonathan Baker

Alex Ackerman

Théo Ben Hassen

 Greg MacWilliam

¿Cómo implementarías una caché GraphQL de alto rendimiento? ¿Cómo podemos diseñar un buen algoritmo para ello? ¿Existe una solución de código abierto eficiente, escalable y fácil de implementar? ¿Cómo se calcula la clave de caché? ¿Qué hay de las invalidaciones de caché? ¿Sería posible deduplicar la ejecución del resolvedor? Esto puede parecer desalentador, pero en realidad todo se reduce a código y algoritmos.En esta charla vamos a explorar un sistema de caché GraphQL que hemos desarrollado para Mercurius, uno de los servidores GraphQL más rápidos para Node.js.<a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

GraphQL Caching Desmitificado

Today's Talk focuses on GraphQL caching and improving performance using Fastify and Mercurius. The experiment involves federated services, resolver caching, and load testing with AutoCANON. Enabling caching with a 0 second TTL can increase throughput by 4 times. The AsyncCacheDedupe module allows for efficient caching and avoiding unnecessary computations. Redis pipelining has improved requests per second by 100 times. Cache invalidation is an ongoing topic of development.

How would you implement a performant GraphQL cache? How can we design a good algorithm for it? Is there a good Open Source solution that is efficient, scalable and easy to deploy? How is the caching key computed? What about cache invalidations? Would it be possible to deduplicate resolver execution? This might be seen as daunting but in reality is all code and algorithms.In this talk we are going to walk through a GraphQL caching system that we have developed for Mercurius - one of the fastest GraphQL servers for Node.js. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

GraphQL Caching Demystified

Matteo Collina

En este masterclass construiremos y desplegaremos una aplicación de GraphQL de pila completa utilizando Next.js, Neo4j y Vercel. Utilizando un grafo de conocimiento de artículos de noticias, primero construiremos una API de GraphQL utilizando las rutas de API de Next.js y la Biblioteca de GraphQL de Neo4j. A continuación, nos enfocaremos en el front-end, explorando cómo utilizar GraphQL para la obtención de datos con una aplicación de Next.js. Por último, exploraremos cómo agregar personalización y recomendación de contenido en nuestra API de GraphQL para servir artículos relevantes a nuestros usuarios, luego desplegaremos nuestra aplicación en la nube utilizando Vercel y Neo4j Aura. Tabla de contenidos: - Visión general de Next.js y cómo empezar con Next.js - Rutas de API con Next.js y construcción de una API de GraphQL - Utilizando la Biblioteca de GraphQL de Neo4j - Trabajando con Apollo Client y obtención de datos de GraphQL en Next.js - Despliegue con Vercel y Neo4j Aura <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Masterclass de GraphQL en la Nube con Neo4j Aura, Next.js y Vercel

The Workshop covered various topics related to building a full stack news article application using Neo4j AuraDB, GraphQL, and Next.js. It discussed graph data models, traversing graphs, and building GraphQL APIs backed by Neo4j. The Neo4j GraphQL library was highlighted for its ability to generate resolver functions and optimize database queries. The Workshop also covered Next.js and deploying the application to Vercel. Custom logic was added to the GraphQL API using the Cypher-GraphQL-Schema directive.

In this workshop we will build and deploy a full stack GraphQL application using Next.js, Neo4j, and Vercel. Using a knowledge graph of news articles we will first build a GraphQL API using Next.js API routes and the Neo4j GraphQL Library. Next, we focus on the front-end, exploring how to use GraphQL for data fetching with a Next.js application. Lastly, we explore how to add personalization and content recommendation in our GraphQL API to serve relevant articles to our users, then deploy our application to the cloud using Vercel and Neo4j Aura. Table of contents: - Next.js overview and getting started with Next.js - API Routes with Next.js &amp; building a GraphQL API - Using the Neo4j GraphQL Library - Working with Apollo Client and GraphQL data fetching in Next.js - Deploying with Vercel and Neo4j Aura <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Full Stack GraphQL In The Cloud With Neo4j Aura, Next.js, & Vercel

William Lyon

En Unity, utilizamos la federación de GraphQL para exponer una amplia gama de funcionalidades empresariales en toda la organización en un solo esquema de GraphQL. Con un número cada vez mayor de servicios, esto presenta desafíos para la autenticación y autorización en general. Exploro cómo implementamos la autenticación de GraphQL a nivel de gateway, las decisiones clave de diseño detrás de ella y los amplios beneficios que esto puede tener. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Autenticación y Autorización de GraphQL a Escala

This talk discusses the implementation of GraphQL Authentication and Authorization at scale at Unity. The speaker explains how they use GraphQL Federation to expose business functionality through a centralized schema and the challenges they faced in handling auth at scale. They describe how they simplified configuration and scaling using Mercurius and implemented hooks and an Orth plugin. The implementation at Unity involves a Unity Orth endpoint and a central Unity Orth directive definition. The talk also covers the implementation of AuthPolicyHandler and AuthDirective for downstream services and showcases different access levels. The Mercurius Auth plugin provides a scalable approach to authentication and ongoing improvements include adding support for a filter schema.

At Unity, we use GraphQL federation to expose a wide range of business functionality across the organization in a single GraphQL schema. With an ever-growing number of services, this presents challenges for authentication and authorization across the board. I explore how we implemented GraphQL auth at the gateway level, the key design decisions behind it, and the wide-reaching benefits this can have. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

GraphQL Authentication and Authorization at Scale

Jonny Green

Durante años, no poder cachear GraphQL se consideraba una de sus principales desventajas en comparación con las APIs RESTful. Ya no más. GraphCDN hace posible cachear casi cualquier API de GraphQL en el edge, y no solo eso, sino que nuestra caché es aún más inteligente que cualquier caché RESTful podría ser. Sumergámonos en los detalles internos de GraphCDN para descubrir cómo exactamente logramos esto. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Cómo Cachear APIs de GraphQL en el Edge

Max Stoiber, co-founder of GraphCDN, discusses the challenges faced with RethinkDB and the need for caching in a read-heavy API. He explores how GraphQL clients handle caching and the potential of running a GraphQL client at the edge for faster response times. Authorization and cache key management at the edge are also discussed, along with the benefits of edge-caching and the importance of caching in GraphQL APIs. The audience response reveals that a significant percentage are already caching their APIs, while different use cases for caching and the concept of edge computing are explained.

For years, not being able to cache GraphQL was considered one of its main downsides compared to RESTful APIs. Not anymore. GraphCDN makes it possible to cache almost any GraphQL API at the edge, and not only that but our cache is even smarter than any RESTful cache could ever be. Let's dive deep into the inner workings of GraphCDN to figure out how exactly we make this happen. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

How to Edge Cache GraphQL APIs

Max Stoiber

Las aplicaciones frontend modernas desean consultar eficientemente datos al cargar la página y navegar, formatear los datos con TypeScript y almacenar en caché los datos entre solicitudes repetidas. Configurar todo esto por tu cuenta es una tarea... pero con Apollo y Next.js, puedes configurar tu cliente para generar automáticamente tipos de TypeScript, almacenar en caché los resultados de las consultas de manera inteligente y, en general, ser muy fácil de trabajar. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

GraphQL + Apollo + Next.js: Un Trío Encantador

This talk provides an overview of using GraphQL, Apollo, and Next.js together. It covers Next.js' data loading and routing capabilities, code generation with GraphQL, and generating TypeScript types. The talk also explores Apollo Client and its integration with GraphQL code generation. The speaker recommends checking out companion repositories and resources for more information.

Modern frontend applications want to efficiently query data on page load and navigate, format the data with TypeScript, and cache data between repeat requests. Setting that all up on your own is a chore... but with Apollo and Next.js, you can set up your client to auto-generate TypeScript types, cache query results intelligently, and generally be a breeze to work with. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

GraphQL + Apollo + Next.js: A Lovely Trio

Josh Goldberg

Weaviate utiliza GraphQL para proporcionar una interacción de datos fácil de usar. Weaviate es un motor de búsqueda de vectores de código abierto, y todas las búsquedas (por ejemplo, semánticas, contextuales) se realizan a través de su API de GraphQL. Hemos pensado mucho en el diseño de la API de GraphQL, lo que resulta en una buena experiencia para el usuario y el desarrollador. En esta charla, te llevaré en el viaje de cómo se formó nuestra implementación de GraphQL según las necesidades de los usuarios y los requisitos de software, y mostraré una demostración del diseño actual de Weaviate. La demostración mostrará cómo el diseño de GraphQL de Weaviate permite la búsqueda semántica (vectorial) en combinación con la búsqueda escalar a través de datos no estructurados. Se utilizan modelos de aprendizaje automático en segundo plano, pero con el diseño actual de GraphQL, los usuarios sin conocimientos técnicos pueden consultar fácilmente la base de datos de vectores. Weaviate tiene una arquitectura modular, por lo que los usuarios pueden conectar varios modelos de aprendizaje automático en la parte superior de la base de datos de vectores. Ejemplos son el módulo de Preguntas y Respuestas recién lanzado y el módulo de Reconocimiento de Entidades Nombradas. Los módulos pueden ampliar el esquema de GraphQL de forma dinámica, para consultar las nuevas características de manera intuitiva.Esta presentación contiene una demostración donde consultaremos la Wikipedia completa, realizaremos consultas de búsqueda semántica y más. Todo a través de la API de GraphQL de Weaviate. No se requieren conocimientos previos. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Búsqueda Semántica a través de la Wikipedia Completa con la API de GraphQL de Weaviate

Weaviate is a database and search engine that uses a GraphQL API. It supports various machine learning models for data vectorization and search. The core functions of Weaviate are get, explore, and aggregate, which allow users to query and search through the data set. Weaviate provides fast and accurate results, allowing users to find anything in the dataset. The GraphQL API in Weaviate can be used for querying specific data and establishing graph relations.

Weaviate uses GraphQL to provide user-friendly data interaction. Weaviate is an open-source vector search engine, and all searches (e.g. semantic, contextual) are done via its GraphQL API. We’ve put a lot of thought into the design of the GraphQL API, which results in good user and developer experience. In this talk, I will take you along in the journey of how our GraphQL implementation was shaped according to user needs and software requirements, and show a demo of the current design for Weaviate. The demo will show how Weaviate’s GraphQL design enables semantic (vector) search in combination with scalar search through unstructured data. Machine learning models are used in the background, but with the current GraphQL design, users without a technical background can query the vector database easily. Weaviate has a modular architecture, so users can connect various machine learning models on top of the vector database. Examples are the newly released Question Answering module and the Named Entity Recognition module. Modules can extend the GraphQL schema dynamically, to query the new features intuitively.This presentation contains a demo where we will query the complete Wikipedia, conduct semantic search queries and more. All through Weaviate’s GraphQL API. No prior knowledge is required. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Semantic Search through the Complete Wikipedia with Weaviate’s GraphQL API

Bob van Luijt

Has oído hablar del desarrollo de GraphQL basado en esquemas y en código. Has visto herramientas que generan automáticamente esquemas de GraphQL a partir de Swagger y SQL. Pero hay otra forma de construir APIs de GraphQL que es flexible, mantenible y evolutiva: ¡simplemente escribir SDL de GraphQL con directivas! <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Desarrollo de GraphQL impulsado por directivas

Lenny Burdett discusses Directive-Driven GraphQL, a prototype for building GraphQL APIs. The approach involves adding and removing parts of the schema, and offers advantages over imperative systems. The prototype integrates GraphQL with gRPC, allowing for easy editing and reshaping of the schema. The gRPC DSL and directives determine the behavior of the API. The directive-driven approach also supports Apollo Federation and future work includes support for GraphQL unions and real-time data subscriptions.

You've heard of schema-first and code-first GraphQL development. You've seen tools that autogenerate GraphQL schemas from Swagger and SQL. But there's another way to build GraphQL APIs that's flexible, maintainable, and evolvable — just writing GraphQL SDL with directives! <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Directive-driven GraphQL Development

Lenny Burdette

Tabla de contenidos: - Desplegando una API GraphQL predefinida - Creando un worker en el borde + caché en Cloudflare - Configurando la caché basada en los nombres de tipo - Agregando invalidación basada en los tipos de retorno de mutación <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Recreando la caché GraphQL de urql en el borde

The Workshop covered various topics related to software development and engineering. It included discussions on coding, communication, and troubleshooting Wrangler configuration. The participants learned about proxying requests in Cloudflare Workers, identifying mutations in GraphQL queries, and caching responses in a KV store. They also explored the AST with astexplorer.net and manipulated the AST to add type names to queries. The Workshop concluded with a discussion on caching subscriptions in GraphQL and handling mutations and query invalidation.

Table of contents: - Deploying a premade GraphQL API - Creating an edge worker + cache on Cloudflare - Configuring caching based on typenames - Adding invalidation based on mutation return types <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Recreating urql's GraphQL cache on the edge

Andy Richardson

WordPress sin cabeza utilizando su API REST incorporada es una solución poderosa para escalar WordPress en la web, pero las relaciones complejas pueden convertirse fácilmente en cadenas de solicitudes, lo que dificulta el mantenimiento junto con el posible costo de rendimiento. Con WPGraphQL, podemos aprovechar los beneficios de GraphQL, lo que conduce a una mejor experiencia de desarrollo y lógica de solicitud optimizada, asegurándonos de entregar solo lo que necesitamos a nuestros usuarios.Exploraremos estas ventajas y cómo encajan estas piezas junto con herramientas modernas como Next.js para construir grandes experiencias para la web. <a href="https://www.colfayock.com/event-notes/graphql-galaxy-2021" target="_blank">Diapositivas y más</a> <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Explorando el Gráfico de WordPress con Next.js y WPGraphQL

WordPress is widely used, and it now supports a REST API for headless usage. Serving static HTML files allows for infinite scaling and surviving viral traffic. GraphQL can be used to interface with WordPress data, reducing complexity. WordPress can be coupled with plugins like Yoast and ACF, and WPGraphQL works seamlessly with these plugins. GraphQL allows for selecting only necessary data and has performance advantages over REST APIs.

Headless Wordpress using its built-in REST API is a powerful solution to scale WordPress to the web, but complex relationships can easily turn into chains of requests, making maintainability difficult along with the potential cost of performance. With WPGraphQL, we can harness the benefits of GraphQL, leading to a better developer experience and optimized request logic, making sure we’re only delivering what we need to our users.We’ll explore these advantages and how these pieces fit together with modern tools like Next.js to build great experiences for the web. <a href="https://www.colfayock.com/event-notes/graphql-galaxy-2021" target="_blank">Slides &amp; more</a> <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Exploring the WordPress Graph with Next.js & WPGraphQL

Colby Fayock

Presentaré el concepto de una malla de datos y por qué cada vez más personas se están inclinando hacia ella como solución a sus problemas de modernización de datos (tanto en línea como analíticos) y aplicaciones. Hablaré sobre los requisitos clave en torno a 1) propiedad y arquitectura de datos descentralizadas orientadas al dominio, 2) datos como producto, 3) infraestructura de datos de autoservicio como plataforma y 4) gobernanza computacional federada (ref). Y luego hablaré sobre cómo GraphQL abre una oportunidad para sentar las bases de una malla de datos y las mejores prácticas en la construcción, operación y mantenimiento de una malla de datos de grado empresarial. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Evaluando GraphQL para Configurar una Malla de Datos de Grado Empresarial

This Talk explores the benefits of using GraphQL APIs for data, including representing domain models, addressing API tooling and infrastructure, and supporting interconnected data. It discusses model mapping, read APIs, filtering, sorting, and aggregating data, as well as mutations for invoking logic. The Talk also highlights the importance of standardizing infrastructure and leveraging GraphQL's automatic model mapping and authorization. Additionally, it touches on the use of specialized databases, the comparison between GraphQL and gRPC for data APIs, and the speaker's experience working on various parts of the stack.

I'll introduce the concept of a data mesh and why people increasingly are gravitating towards that as a solution to their data (both online and analytical) and application modernization problems. I'll talk about the key requirements around 1) domain-oriented decentralized data ownership and architecture, 2) data as a product, 3) self-serve data infrastructure as a platform, and 4) federated computational governance (ref). And then I'll talk about how GraphQL opens up an opportunity for laying the foundation for a data mesh and best-practices in building, operating and maintaining an enterprise grade data mesh. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Evaluating GraphQL for Setting Up an Enterprise-Grade Data Mesh

Tanmai Gopal

GraphQL es un lenguaje de consulta para APIs que proporciona una descripción completa y comprensible de los datos en su API, al tiempo que brinda a los clientes el poder de solicitar exactamente lo que necesitan y nada más. Si bien hay varios beneficios de GraphQL, también existen diversos desafíos para adoptar APIs de GraphQL dentro de las organizaciones. Entonces, ¿GraphQL es adecuado para ti? Si es así, ¿por dónde debes empezar? En este masterclass, te guiaremos a través de los diversos conceptos de GraphQL de manera práctica con el objetivo de ayudar a la audiencia a comprender GraphQL como una tecnología y evaluar si es la elección correcta para su proyecto/organización. Tabla de contenidos: - ¿Qué es GraphQL? - Una visión general de la tecnología y por qué existe - El debate REST v/s GraphQL - El ecosistema de GraphQL - herramientas y recursos - Configuración del proyecto (React + Express + Tyk) - Conceptos básicos de GraphQL: práctica - Gestión de la API de GraphQL con Tyk - Unión de esquemas con Tyk Universal Data Graph - Conclusión <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Aprendiendo GraphQL: de curioso a confiado

Welcome to the workshop on building and managing GraphQL APIs. Today, we'll be learning about GraphQL, building APIs with Express GraphQL, securing GraphQL endpoints with Tyke, and creating a GraphQL endpoint using Tyke's universal data graph. GraphQL provides flexibility and eliminates overfetching and underfetching of data. We'll explore querying information and mutations, as well as the concept of resolvers. We'll also learn about GraphQL API management with Tyke and the benefits of using Tycloud. Additionally, we'll see how to migrate from existing infrastructure to GraphQL using Tyke's universal data graph.

GraphQL is a query language for APIs that provides a complete and understandable description of the data in your API while giving clients the power to ask for exactly what they need and nothing more. While there are a number of benefits of GraphQL, there are also various challenges to adopting GraphQL APIs within organisations. So, is GraphQL right for you? If so, where do you get started? In this workshop, we will take you through the various concepts of GraphQL in a hands-on manner with the objective of helping the audience understand GraphQL as a technology and evaluate if it is the right choice for their project/organisation. Table of contents: - What is GraphQL - An overview of the technology and why it exists - The REST v/s GraphQL debate - The GraphQL ecosystem - tools and resources - Project setup (React + Express + Tyk) - GraphQL concepts: basic hands-on - GraphQL API management with Tyk - Schema stitching with Tyk Universal Data Graph - Conclusion <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Learning GraphQL: from curious to confident

Buddha Bhattacharya

¿Quieres empezar a construir un servidor GraphQL pero no tienes idea de por dónde empezar? Cada desarrollador (frontend) pide una API GraphQL pero a menudo carece del conocimiento backend para crear una que sea eficiente. Existen muchas formas diferentes de crear el servidor GraphQL perfecto, desde el enfoque de esquema primero hasta el enfoque de código primero o incluso soluciones generadas automáticamente. En este masterclass interactivo, aprenderás a construir una API GraphQL sin servidor utilizando StepZen. Con StepZen, puedes crear un GraphQL para cualquier fuente de datos (SQL, NoSQL y REST) e incluso otras APIs GraphQL en cuestión de minutos. Incluso puedes manejar casos de uso más complicados como la autenticación y el despliegue. Con un poco de código, podrás combinar diferentes fuentes de datos en una API totalmente eficiente que podrás utilizar en tus aplicaciones desde el primer día. Tabla de contenidos: - ¿Qué es StepZen? - Conexión a una fuente de datos (SQL, NoSQL y REST) - Uso de directivas personalizadas - Manejo de flujos de secuencia - Despliegue <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Construyendo una API GraphQL sin servidor para cualquier fuente de datos con StepZen

Today's workshop is about building a serverless GraphQL API using StepZen. It covers the code-first and schema-first approaches, connecting multiple data sources, merging data from different endpoints, and using StepZen's sequences to combine data. The workshop also highlights the importance of understanding StepZen and GraphQL for building scalable GraphQL servers.

Want to get started with building a GraphQL server but have no idea where to begin? Every (frontend) developer asks for a GraphQL API but often lacks the backend knowledge to create a performant one. There are many different flavours in creating the perfect GraphQL server, ranging from schema-first to code-first or even auto-generated solutions. In this interactive workshop, you will learn about building a serverless GraphQL API using StepZen. With StepZen, you can create a GraphQL for any data source (SQL, NoSQL &amp; REST) and even other GraphQL APIs within minutes. And even handle more complicated use cases such as authentication and deployment. Using little code, you'll get to combine different data sources in one fully performant API that you can use in your applications from day one. Table of contents: - What is StepZen? - Connecting to a data source (SQL, NoSQL &amp; REST) - Using custom directives - Handle sequence flows - Deployment <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Building a Serverless GraphQL API For Any Datasource With StepZen

Roy Derks

Discussion on GraphQL in different languages with panelists introducing themselves and their expertise. Introduction of panelists using different languages with GraphQL expertise in Python, Rust, Ruby on Rails, and mobile development with Swift and Kotlin. Discussion about the unique aspects and advantages of using different programming languages with GraphQL, starting with a question on what makes a language special for GraphQL. Insights from panelists like Jeremy on the benefits and challenges of using Rust for GraphQL.

Moderator -  Uri Goldshtein Panelists:Ellen Shapiro - Swift, KotlinGabriel Nordborn - RescriptRelayMarcin Gebala - PythonAlexander Varwijk - PHPRobert Mosolgo - Ru <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Panel Discussion: GraphQL for non-JS Languages

Alexander Varwijk

Ellen Shapiro

Marcin Gebala

Robert Mosolgo

Gabriel Nordborn

¡Bienvenido a Fauna! Este masterclass ayuda a los desarrolladores de GraphQL a construir aplicaciones de alto rendimiento con Fauna que se escalan a cualquier tamaño de base de usuarios. Comienzas con lo básico, utilizando solo el playground de GraphQL en el panel de Fauna, luego construyes una aplicación completa de pila completa con Next.js, agregando funcionalidad a medida que avanzas. En la primera sección, Comenzando con Fauna, aprendes cómo Fauna crea automáticamente consultas, mutaciones y otros recursos basados en tu esquema de GraphQL. Aprendes cómo realizar tareas comunes con GraphQL, cómo usar el lenguaje de consulta de Fauna (FQL) para realizar tareas más avanzadas. En la segunda sección, Construyendo con Fauna, aprendes cómo Fauna crea automáticamente consultas, mutaciones y otros recursos basados en tu esquema de GraphQL. Aprendes cómo realizar tareas comunes con GraphQL, cómo usar el lenguaje de consulta de Fauna (FQL) para realizar tareas más avanzadas. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Construyendo un backend serverless nativo de GraphQL con Fauna

Today's workshop focused on serverless development with Fauna. The workshop covered topics such as building a client-serverless model, exploring data access patterns, and creating a serverless application. It also delved into user authentication, session management, and querying data in the front end. The workshop highlighted the power of Fauna for data manipulation and the flexibility it offers for building applications with fine-grained access control.

Welcome to Fauna! This workshop helps GraphQL developers build performant applications with Fauna that scale to any size userbase. You start with the basics, using only the GraphQL playground in the Fauna dashboard, then build a complete full-stack application with Next.js, adding functionality as you go along. In the first section, Getting started with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks. In the second section, Building with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Building a GraphQL-native serverless backend with Fauna

Rob Sutter

Shadid Haque

"¿Para qué se utiliza GraphQL?" "¿Cómo encuentro los campos que necesito?" "¿Cómo pruebo las consultas en un gráfico local?" Todas estas son preguntas comunes y válidas que tienen los desarrolladores que están aprendiendo GraphQL cuando comienzan a trabajar con un gráfico unificado. ¿El secreto para superar estos desafíos? ¡Lo adivinaste, Apollo Studio! En esta sesión, profundizaremos en las mejores herramientas de Apollo Studio para ayudar a los desarrolladores nuevos (y experimentados) a sentirse seguros al realizar consultas y colaborar en un gráfico unificado.<a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

El Secreto para la Incorporación de Gráficos

Today's Talk focused on making GraphQL graphs more usable and approachable. It covered topics such as onboarding developers, enforcing graph usage, handling errors and authentication, creating a custom developer portal, enhancing the log-in button and query IDE experience, enforcing rules, and building and customizing public graphs.

"What is GraphQL used for?” “How do I find the fields I need?” “How do I test queries against a local graph?” All of these are common and valid questions that developers who are learning GraphQL have when they are first getting started with a unified graph. The secret to overcoming these challenges? You guessed it, Apollo Studio! In this session, we’ll dive into the best tools in Apollo Studio to help new (and experienced) developers feel confident when querying and collaborating on a unified graph <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

The Secret to Graph Onboarding

Danielle Man

The DiscussionRoom covered a range of topics related to GraphQL, including its impact on scalability, data management, and application development. There were discussions on GraphQL's versatility, integration in mobile app development, and benefits of schema utilization in web and mobile development. Challenges such as trade-offs in schema utilization, type safety, and library complexities were also highlighted, emphasizing the importance of schema design, type safety, and user-focused GraphQL usage progression.

Vishwa Mehta - ModeratorPanelists:Ellen Shapiro, ApolloJoe Savona, RelayDominik Dorfmeister, React QueryPhil Plucktun, URQL <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Panel Discussion: GraphQL Client-Side Libraries

Joe Savona

Vishwa Mehta

Dominik Dorfmeister

Phil Pluckthun

<div>Al comienzo de la pandemia de COVID-19, la Universidad Johns Hopkins trabajó en recopilar y refinar datos de múltiples fuentes y proporcionó al mundo un repositorio de Github y un montón de archivos CSV. ¿El problema? Es casi imposible construir algo a partir de datos en bruto como estos.En esta sesión de codificación en vivo, Maxime Beunier, un defensor del desarrollador de MongoDB, te mostrará cómo construir una API GraphQL sin servidor basada en este conjunto de datos utilizando Python y la plataforma de datos de MongoDB. ¡Finalmente vamos a aprovechar el servidor sin servidor y el generoso nivel gratuito de MongoDB!</div> <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Construyendo una API GraphQL sin servidor en 7 minutos

Maxime Beunier, a developer advocate at MongoDB, demonstrates how to build a serverless GraphQL API using MongoDB Atlas and Realm. He creates a new app called Galaxy, links it to the production cluster, and deploys it in Ireland. He then shows how to authenticate users and obtain a token to access the GraphQL API. The demo showcases the ease and speed of building a serverless GraphQL API and provides all the necessary links for further exploration.

<div>At the beginning of the COVID-19 pandemic, Johns Hopkins University worked on gathering and refining data from multiple sources and provided the world with a Github repository and a bunch of CSV files. The Problem? It’s nearly impossible to build anything from raw data like this.In this live coding session, MongoDB Developer Advocate Maxime Beugnet will show you how to build a serverless GraphQL API based on this dataset using Python and the MongoDB Data Platform. We are finally going to put serverless and the MongoDB generous free tier to good use!</div> <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Building a Serverless GraphQL API in 7 Minutes

Maxime Beugnet

En esta charla, cubriremos las bibliotecas, herramientas y procesos que utilizamos para implementar GraphQL a cientos de desarrolladores en Yelp. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Herramientas y Procesos para Gestionar GraphQL a Escala

This talk discusses the life of a GraphQL developer at Yelp, covering tooling, processes, and the scale of GraphQL usage. It emphasizes the importance of making good schema choices and using GraphQL Faker for quick iteration. The talk also highlights the challenges of using data loaders at Yelp and the solutions implemented, such as code generation and precommits. It mentions the significance of schema review, documentation, and GraphQL adoption. Lastly, it mentions the value of obsessive documentation and the use of vPress for generating markdown and an in-house UI for query reference.

In this talk, we'll cover the libraries, tooling and processes we use to roll out GraphQL to hundreds of developers at Yelp. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Tooling and Processes for Managing GraphQL at Scale

Mark Larah

La mayoría de las personas en la Galaxia GraphQL están familiarizadas con las herramientas de JavaScript al crear servidores GraphQL. Pero, ¿qué haces si la especialidad de tu equipo es PHP y tienes todos tus datos existentes disponibles en una plataforma basada en Drupal?En esta sesión te llevaré a un recorrido por las herramientas que utilizamos para construir un servicio basado en PHP que maneja suscripciones GraphQL para impulsar el chat en tiempo real de Open Social, y cómo puedes aplicar nuestros conocimientos a tu propio proyecto. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Servicio de Suscripciones GraphQL utilizando PHP y Drupal

This Lightning Talk discusses the setup of GraphQL subscriptions in a Drupal-based product, using Rescript and React on the client-side and the Urql GraphQL client. The choice of ReactPHP over AMP for the subscription service is explained, highlighting the use of Fibers in PHP 8.1 for asynchronous task handling.

Most people in the GraphQL Galaxy are familiar with JavaScript tools when creating GraphQL servers. But what do you do if your team’s speciality is PHP and you have all your existing data available in a Drupal based platform?In this session I’ll take you on a tour of the tools we used to build a PHP based service that handles GraphQL subscriptions powering Open Social’s Real-Time chat, and how you can use our learnings for your own project. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

GraphQL Galaxy 2021

The biggest GraphQL conference in the cloud