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 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!
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 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: 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.
Meteor MIT Tech Talk 9/18/14: Designing a New Platform For Modern AppsSashko Stubailo
These are the slides for the talk Emily Stark and I presented at MIT on September 9, 2014.
We talked about the components that make up Meteor and how they fit together, finishing off with a more in-depth discussion of DDP, Meteor's Distributed Data Protocol.
GraphQL is quickly becoming mainstream as one of the best ways to get data into your React application. When we see people modernize their app architecture and move to React, they often want to migrate their API to GraphQL as part of the same effort. But while React is super easy to adopt in a small part of your app at a time, GraphQL can seem like a much larger investment. In this talk, we’ll go over the fastest and most effective ways for React developers to incrementally migrate their existing APIs and backends to GraphQL, then talk about opportunities for improvement in the space. If you’re using React and are interested in GraphQL, but are looking for an extra push to get it up and running at your company, this is the talk for you!
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.
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!
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 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: 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.
Meteor MIT Tech Talk 9/18/14: Designing a New Platform For Modern AppsSashko Stubailo
These are the slides for the talk Emily Stark and I presented at MIT on September 9, 2014.
We talked about the components that make up Meteor and how they fit together, finishing off with a more in-depth discussion of DDP, Meteor's Distributed Data Protocol.
GraphQL is quickly becoming mainstream as one of the best ways to get data into your React application. When we see people modernize their app architecture and move to React, they often want to migrate their API to GraphQL as part of the same effort. But while React is super easy to adopt in a small part of your app at a time, GraphQL can seem like a much larger investment. In this talk, we’ll go over the fastest and most effective ways for React developers to incrementally migrate their existing APIs and backends to GraphQL, then talk about opportunities for improvement in the space. If you’re using React and are interested in GraphQL, but are looking for an extra push to get it up and running at your company, this is the talk for you!
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.
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.
GraphQL is a query language for APIs that uses a type system to define queries and mutations. It originated at Facebook in 2011 to address issues with REST APIs like multiple round trips and misaligned data shapes. GraphQL allows clients to specify exactly what data they need in a single request, making it more efficient than REST. It has gained popularity with over 300 billion requests per day on Facebook and adoption by companies like GitHub for their APIs.
Taking Control of your Data with GraphQLVinci Rufus
The document discusses how GraphQL provides a solution for problems with traditional REST APIs by allowing flexible data fetching with one query. It summarizes pain points like over-fetching or under-fetching data and inconsistent features between platforms. The document then explains what GraphQL is, how it evolved from internal use at Facebook, popular brands using it, its specifications and implementations in different languages. It demonstrates how GraphQL enables flexible querying of data without versioning or multiple endpoints. The document also covers related tools like GraphiQL, schemas and types, and how GraphQL can be used with React. It concludes by discussing upcoming areas of focus like prioritizing data and supporting real-time updates.
It is a basic presentation which can help you understand the basic concepts about Graphql and how it can be used to resolve the frontend integration of projects and help in reducing the data fetching time
This presentation also explains the core features of Graphql and why It is a great alternative for REST APIs along with the procedure with which we can integrate it into our projects
This document introduces GraphQL, describing what it is and isn't. It explains that GraphQL is not a query language like SQL, but rather specifies fields that can be resolved through code. The document provides examples of GraphQL schemas, queries, and mutations. It also discusses GraphQL integration with various technologies like Relay and Java libraries. Finally, it demonstrates GraphQL tooling like GraphiQL and an example DX integration.
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/
The document discusses GraphQL, Relay, and some of their benefits and challenges. Some key points covered include:
- GraphQL allows for declarative and UI-driven data fetching which can optimize network requests.
- Relay uses GraphQL and allows defining data requirements and composing queries to fetch nested data in one roundtrip.
- Benefits include simpler API versioning since fields can be changed without breaking clients.
- Challenges include verbose code, lack of documentation, and not supporting subscriptions or local state management out of the box.
- Overall GraphQL aims to solve many data fetching problems but has a complex setup process and learning curve.
GraphQL is a specification created by Facebook that defines a query language for fetching data from backend services. It allows clients to request specific data fields from a server in a hierarchical manner and receive only the requested data. GraphQL queries are strongly typed and introspective, allowing clients to understand the structure of the returned data. While still in draft form, GraphQL is used in production by Facebook's mobile apps and provides advantages over traditional REST APIs by being more product-centric and client-driven.
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 and runtime for APIs that provides better performance, flexibility, and developer experience compared to REST. It allows clients to define exactly the structure and relations between data needed from the server.
- A GraphQL server is defined by a schema that specifies the types of objects and the fields they contain. Resolvers retrieve data and are independent of data sources. This allows GraphQL to work with various databases and services.
- Client-side frameworks like Relay and Apollo utilize GraphQL's capabilities by batching queries to minimize requests. The ecosystem is growing rapidly with server and client implementations in many languages.
GraphQL can be one of the best ways to make your product development more fun and productive. In this presentation I talk about how GraphQL makes your life simpler, and how to write and deploy a GraphQL API with Apollo Server 2.0 and serverless deployment via Netlify Functions.
Overview of GraphQL
How it is different from REST
When you should consider using it and when you should not
Incremental demos until calling GraphQL from an React application: https://github.com/bary822/graphQL-techtalk
CONDG April 23 2020 - Baskar Rao - GraphQLMatthew Groves
This document provides an overview of GraphQL, including:
- A brief history of API architectures like REST and how GraphQL compares
- Common problems with REST APIs that GraphQL aims to address
- Key aspects of GraphQL like queries, mutations, subscriptions and its schema-first approach
- Popular GraphQL platforms and clients like Apollo, Hasura and Relay
- A demo of building a GraphQL API
Introduction to Testing GraphQL PresentationKnoldus Inc.
Explore strategies and best practices for testing systems built on event-driven architecture. Learn how to ensure the reliability and responsiveness of event-driven applications through comprehensive testing methodologies.
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.
GraphQL is a query language for APIs that uses a type system to define queries and mutations. It originated at Facebook in 2011 to address issues with REST APIs like multiple round trips and misaligned data shapes. GraphQL allows clients to specify exactly what data they need in a single request, making it more efficient than REST. It has gained popularity with over 300 billion requests per day on Facebook and adoption by companies like GitHub for their APIs.
Taking Control of your Data with GraphQLVinci Rufus
The document discusses how GraphQL provides a solution for problems with traditional REST APIs by allowing flexible data fetching with one query. It summarizes pain points like over-fetching or under-fetching data and inconsistent features between platforms. The document then explains what GraphQL is, how it evolved from internal use at Facebook, popular brands using it, its specifications and implementations in different languages. It demonstrates how GraphQL enables flexible querying of data without versioning or multiple endpoints. The document also covers related tools like GraphiQL, schemas and types, and how GraphQL can be used with React. It concludes by discussing upcoming areas of focus like prioritizing data and supporting real-time updates.
It is a basic presentation which can help you understand the basic concepts about Graphql and how it can be used to resolve the frontend integration of projects and help in reducing the data fetching time
This presentation also explains the core features of Graphql and why It is a great alternative for REST APIs along with the procedure with which we can integrate it into our projects
This document introduces GraphQL, describing what it is and isn't. It explains that GraphQL is not a query language like SQL, but rather specifies fields that can be resolved through code. The document provides examples of GraphQL schemas, queries, and mutations. It also discusses GraphQL integration with various technologies like Relay and Java libraries. Finally, it demonstrates GraphQL tooling like GraphiQL and an example DX integration.
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/
The document discusses GraphQL, Relay, and some of their benefits and challenges. Some key points covered include:
- GraphQL allows for declarative and UI-driven data fetching which can optimize network requests.
- Relay uses GraphQL and allows defining data requirements and composing queries to fetch nested data in one roundtrip.
- Benefits include simpler API versioning since fields can be changed without breaking clients.
- Challenges include verbose code, lack of documentation, and not supporting subscriptions or local state management out of the box.
- Overall GraphQL aims to solve many data fetching problems but has a complex setup process and learning curve.
GraphQL is a specification created by Facebook that defines a query language for fetching data from backend services. It allows clients to request specific data fields from a server in a hierarchical manner and receive only the requested data. GraphQL queries are strongly typed and introspective, allowing clients to understand the structure of the returned data. While still in draft form, GraphQL is used in production by Facebook's mobile apps and provides advantages over traditional REST APIs by being more product-centric and client-driven.
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 and runtime for APIs that provides better performance, flexibility, and developer experience compared to REST. It allows clients to define exactly the structure and relations between data needed from the server.
- A GraphQL server is defined by a schema that specifies the types of objects and the fields they contain. Resolvers retrieve data and are independent of data sources. This allows GraphQL to work with various databases and services.
- Client-side frameworks like Relay and Apollo utilize GraphQL's capabilities by batching queries to minimize requests. The ecosystem is growing rapidly with server and client implementations in many languages.
GraphQL can be one of the best ways to make your product development more fun and productive. In this presentation I talk about how GraphQL makes your life simpler, and how to write and deploy a GraphQL API with Apollo Server 2.0 and serverless deployment via Netlify Functions.
Overview of GraphQL
How it is different from REST
When you should consider using it and when you should not
Incremental demos until calling GraphQL from an React application: https://github.com/bary822/graphQL-techtalk
CONDG April 23 2020 - Baskar Rao - GraphQLMatthew Groves
This document provides an overview of GraphQL, including:
- A brief history of API architectures like REST and how GraphQL compares
- Common problems with REST APIs that GraphQL aims to address
- Key aspects of GraphQL like queries, mutations, subscriptions and its schema-first approach
- Popular GraphQL platforms and clients like Apollo, Hasura and Relay
- A demo of building a GraphQL API
Introduction to Testing GraphQL PresentationKnoldus Inc.
Explore strategies and best practices for testing systems built on event-driven architecture. Learn how to ensure the reliability and responsiveness of event-driven applications through comprehensive testing methodologies.
Testing Graph QL Presentation (Test Automation)Knoldus Inc.
Discover how to test GraphQL effectively! This session dives into checking if your data queries and changes work correctly. You'll learn to ensure your data stays safe and accurate. We'll cover practical examples to help you understand these methods better by the end of our session.
apidays LIVE Australia 2020 - Have your cake and eat it too: GraphQL? REST? W...apidays
apidays LIVE Australia 2020 - Building Business Ecosystems
Have your cake and eat it too: GraphQL? REST? Why not have both!
Roy Mor, Technical Lead at Sisense
This document summarizes and compares several GraphQL libraries for Java: graphql-java, graphql-java-kickstart, and dgs-framework. It discusses their features for defining schemas and types, handling data fetching and caching, performing mutations, handling errors, testing functionality, and code generation capabilities. Overall, dgs-framework requires the least amount of boilerplate code, supports testing and code generation more fully, and is designed specifically for use within Spring Boot applications.
Sashko Stubailo - The GraphQL and Apollo Stack: connecting everything togetherReact Conf Brasil
Apresentado na React Conf Brasil, em São Paulo, 7 de Outubro de 2017 #reactconfbr
I’ve been exploring the space of declarative developer tools and frameworks for over five years. Most recently, I was the founding member of the Apollo project at Meteor Development Group. My greatest passion is to make software development simpler, and enable more people to create software to bring good to the world.
https://medium.com/@stubailo
@stubailo
- Patrocínio: Pipefy, Globo.com, Meteor, Apollo, Taller, Fullcircle, Quanto, Udacity, Cubos, Segware, Entria
- Apoio: Concrete, Rung, LuizaLabs, Movile, Rivendel, GreenMile, STQ, Hi Platform
- Promoção: InfoQ, DevNaEstrada, CodamosClub, JS Ladies, NodeBR, Training Center, BrazilJS, Tableless, GeekHunter
- Afterparty: An English Thing
Introduction to GraphQL (or How I Learned to Stop Worrying about REST APIs)Hafiz Ismail
Talk for FOSSASIA 2016 (http://2016.fossasia.org)
----
This talk will give a brief and enlightening look into how GraphQL can help you address common weaknesses that you, as a web / mobile developer, would normally face with using / building typical REST API systems.
Let's stop fighting about whether we should implement the strictest interpretation of REST or how pragmatic REST-ful design is the only way to go, or debate about what REST is or what it should be.
A couple of demos (In Golang! Yay!) will be shown that are guaranteed to open up your eyes and see that the dawn of liberation for product developers is finally here.
Background: GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012.
Hafiz Ismail (@sogko) is a contributor to Go / Golang implementation of GraphQL server library (https://github.com/graphql-go/graphql) and is looking to encourage fellow developers to join in the collaborative effort.
Active Cloud DB is a RESTful interface that allows easy evaluation and comparison of distributed databases. It runs on Google App Engine and exposes key-value access to databases like BigTable through a simple REST API. Tests can be run quickly to generate performance graphs comparing databases. The system includes sample bookstore applications and supports caching for improved performance.
Gutenberg, aka WordPress blocks, gives content producers powerful new ways to lay out content in a traditional WordPress site. Butow can headless WordPress developers empower Marketing teams with those same capabilities? In this session, the founder of GraphQL for WordPress (WPGraphQL) shares new capabilities and best practices for using Gutenberg on a headless site.
This document discusses the advantages of using Ruby on Rails for web development. It highlights that Rails allows for fast, agile development with features like scaffolding, DRY principles, and AJAX. Rails also emphasizes readable, well-tested code and follows the MVC framework. MVC separates the interface to the database (model), business logic, and the user interface (view). Rails makes it easy to link models and views through controllers and features like polymorphism, caching, and RESTful routes are discussed. Test-driven development is also highlighted as an important practice in Rails.
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.
Running Airflow Workflows as ETL Processes on Hadoopclairvoyantllc
While working with Hadoop, you'll eventually encounter the need to schedule and run workflows to perform various operations like ingesting data or performing ETL. There are a number of tools available to assist you with this type of requirement and one such tool that we at Clairvoyant have been looking to use is Apache Airflow. Apache Airflow is an Apache Incubator project that allows you to programmatically create workflows through a python script. This provides a flexible and effective way to design your workflows with little code and setup. In this talk, we will discuss Apache Airflow and how we at Clairvoyant have utilized it for ETL pipelines on Hadoop.
The document describes Key Alias, a smart identity platform that converts physical identity data like photos into digital identity data and reminds users of expiration dates. It discusses development tools like Quip, Slack, Gantt Pro and Meister Task used for requirements definition, problem solving, task management and timelines. The development flow involves Gitlab for code, NodeJS, React and related technologies for the backend and frontend, with code review and deployment. Future goals include using Docker, Chef, Jenkins and migrating to GitHub.
Lessons learned on the Azure API Stewardship Journey.pptxapidays
apidays LIVE Singapore 2022: Digitising at scale with APIs
April 20 & 21, 2022
Lessons learned on the Azure API Stewardship Journey
Adrian Hall, Principal Product Manager at Microsoft
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This document discusses implementing a service-oriented architecture (SOA) with the Zend Framework. It defines SOA and services, and describes how to build a service layer with domain models, data mappers, and data stores. It also covers decorating services with caching, logging, and formatting behaviors. The document shows how to expose services through JSON, XML, SOAP, and REST servers using Zend components. It discusses versioning services and notes on consumer performance and authentication/authorization when building web services.
This document summarizes different approaches for retrofitting GraphQL APIs: writing a GraphQL layer by hand ("The Developer Way"), using a lightweight API gateway ("The Cloud-native Way"), and using cloud provider native serverless services ("The Serverless Way"). It assesses the key criteria of convenience, rate limiting, query depth limiting, and caching for each approach. It includes code samples and a demo of setting up a GraphQL API with an API gateway.
This document provides an agenda and information for a class on databases, debugging, forms, and APIs. It includes exercises to set up debugging in VS Code and create a page that allows querying a database table. Key topics covered are debugging, generators, bundling, HTTP requests, parsing request bodies, asynchronous JavaScript, JSON, and RESTful APIs. Students are also instructed on requirements for their upcoming Project 3 presentations and Homework 11 assignment.
Grails has great performance characteristics but as with all full stack frameworks, attention must be paid to optimize performance. In this talk Lari will discuss common missteps that can easily be avoided and share tips and tricks which help profile and tune Grails applications.
This document discusses API management for GraphQL APIs. It begins with an introduction to GraphQL and then covers how API management platforms can support GraphQL APIs, including developer portals, enforcing security and policies at the gateway, and analytics. Key capabilities for GraphQL API management include importing GraphQL schemas, analyzing query complexity, enforcing rate limits on operations, and providing insights into usage patterns and latency from analytics. The document emphasizes that GraphQL is a good fit for some problems but API management is still needed to maximize benefits for both GraphQL API providers and consumers.
Similar to Adding GraphQL to your existing architecture (20)
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
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.
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
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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.
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GraphRAG for Life Science to increase LLM accuracy
Adding GraphQL to your existing architecture
1. Adding GraphQL to
your Existing Architecture
Sashko Stubailo
Open Source Lead, Apollo
@stubailo
2. • Client-side developer ergonomics
• Flexibility means fewer API changes
• Better efficiency, fetch just what you need
GraphQL makes everyone’s life better
So what might block people from using it?
3. • Where do I start?
• Can I use this at work without rewriting my
existing stuff?
• How do I get running in production?
First questions people ask
4. • Sometimes presented as totally new way of thinking,
which makes it seem like a big investment
• In practice, it’s a standardization of things people were
already doing
Is GraphQL really that different?
SIDE NOTE
5. • It’s what made React so easy to adopt
• Can you use it for just one feature or component?
• GraphQL can be done the same way
The golden ticket: Incremental adoption
7. Web App
Elastic Search MongoDB Dynamo DB
C L I E N T
S E R V E R
API Server
Existing app + GraphQL
?
?
8. • Fetch GraphQL anywhere you can do an HTTP request
• For fancier features—caching, network state
management, mutation handling—we’ve worked hard to
make Apollo Client compatible everywhere
• For some projects, great opportunity to improve your UI
and data management together
On the client, incremental is easy
9. • Model virtually any kind of application data
• Start with client-side needs, fill in API bit by bit
• Uniquely suited to being an API gateway, calling
your existing backends
• Suggestion: Experiment with clients that you can
push code to easily, like web or React Native
Incrementally adoptable API?
10. Two ways to present GraphQL
• Brownfield, existing app with existing
backend, every situation is different
• GraphQL addresses critical problems
• Greenfield, new app with new
backend, easy to write tutorials
• GraphQL sets you up to grow
11. • Most content builds “hello world” style APIs from
scratch, or starts with existing GraphQL API
• After you get a taste of the GraphQL experience, you
need a way to get it running in your existing app
• Everyone’s situation is unique
• Can we cut the problem into small bits?
Problem: Not enough guidance
16. 1. Understand what is going on inside your server
with instrumentation
2. Know the tools available to make improvements
3. Ensure that backend services are not adversely
affected by the new API layer
Production learning checklist
17. • You need your instrumentation to understand GraphQL
• Need to have some way to identify common queries,
expensive fields, critical paths, and schema usage
• Write your client code and queries in a way that lets you
identify what you see on the server
First: Instrumentation
18. Two classes of problems
• High latency or bandwidth usage causes bad experience
for the end-user client app
• Inefficient execution or expensive requests result in too
much load on the API or backend
19. Client-side improvements
• Load data judiciously to avoid
performance issues
• Load less data at a time, split into
multiple queries, avoid expensive fields
• Improve client-side caching with an
offline cache, cache redirects, and
optimistic UI
• Otherwise, need to improve server
query Human {
human {
name
weather
friends {
name
}
}
}
query Human
20. Biggest question: Server performance
• Executing each query with low latency needs to be
balanced with load on the API server and backends
• Two dimensions that can be optimized: GraphQL server
overhead, and work done by backend APIs and databases
21. GraphQL server overhead?
• GraphQL execution engine itself is quite efficient for the value it
provides, usually not the main thing to optimize
• Caching parsing and validation helps a lot, those are some of the
most expensive steps
• Make it stateless to scale horizontally
• Break out of GraphQL data model if necessary with custom scalars
• In general, overhead is easy to limit
22. Backend API usage
• GraphQL API is much closer to the backend, so
same number of roundtrips is less time
• We should try to make sure we do the same
number of fetches or less than we were doing
without GraphQL
• How can we reduce fetches to the backend or
make them more efficient?
REST
23. Reducing backend load
• Leverage backend features when you can
• Use something like DataLoader to collect requirements,
then make one batched request and avoid extra roundtrips
• Make sure GraphQL server manages backend load by
listening to backpressure or rate limiting calls
• In theory GraphQL can be very efficient since all data needs
are known ahead of time
24. Persisted queries?
• Save queries to a database and only send the ID instead
of the whole query string
• Supported by Apollo Client and Relay Modern
• Important to distinguish several possible concepts:
• Static queries - no runtime modification of queries
• Whitelisted queries - only accept known queries
• Persisted queries - send query ID, look it up on server
• Compiled queries - do some optimization in build step
• Different potential benefits from each one
{
id: ‘23235’,
variables: …
}
25. Preventing malicious queries
• Simple: Basic rate limiting
• Medium: Statically calculate cost from the query
document before execution, reject if too high
• Advanced: Track cost of each client over time, to block
people loading too much data quickly
• For extreme cases: Explicit whitelisting
26. Advanced performance ideas
• Get the same performance as a hand-crafted REST endpoint
but with no loss of generality
• For certain applications that have extremely common
queries, hand-optimize queries or fragments
• In the resolver, check if we are looking for that selection set
and run a more efficient batched fetch for the subtree
• HTTP caching of whole query results
27. • You can incrementally adopt GraphQL, start with a quick
prototype to get a feel for it
• Instrument everything to avoid unnecessary optimizations
• Work with backend devs to make sure the databases and
services are happy
• The normal thing is usually fine, but if you discover issues
there are many paths to optimize your GraphQL API
Conclusions
28. Help grow the community!
• Write more content about intermediate GraphQL topics,
to help people get this amazing API with their data
• Write about your production experiences, performance
optimizations you’ve made, and new patterns you come
up with
Tweet or DM me, let’s work together: @stubailo