InfoQ Homepage API Content on InfoQ
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/articles/Standardized-Specification-Driven-API-Lifecycle/en/smallimage/logo-1647025459155.jpg)
A Standardized, Specification-Driven API Lifecycle
At QCon Plus last November, Kin Lane, Chief Evangelist with Postman, and the Open Technologies Team lead presented on API specifications. API specifications are essential to him and at Postman. So he wanted to share a bit of how they see API specifications impacting how they produce and consume APIs.
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Ballerina for Full-Stack Developers: a Guide to Creating Backend APIs
This article explores Ballerina’s intuitive syntax for writing REST APIs. We also discuss authentication, authorization, OpenAPI tool, observability, SQL/NoSQL client libraries, and key language features. At the end of this article, you will have a good understanding of why Ballerina is a prominent candidate for writing your next backend API.
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Creating and Using HTTP Client SDKs in .NET 6
In this article, the author explains the process behind developing HTTP Client SDKs in .NET 6. Different approaches for real-world scenarios are presented and explained while the author shows you how to develop your own SDK using .NET 6, step-by-step.
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Introducing the KivaKit Framework
In this article, we take a brief tour of the KivaKit open source Java microservices application framework. KivaKit is a collection of mini-frameworks designed to work together. Each mini-framework is described in more detail at https://www.kivakit.org as well as on Jonathan Locke’s blog State of the Art.
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Using API-First Development and API Mocking to Break Critical Path Dependencies
Teams are using API mocking to break critical path dependencies and enable what were serial execution sequences into parallel paths. This article looks at where mocks should be used for the greatest impact and provides a model to estimate the effect of implementing API mocking and an API-first approach.
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Reducing Cloud Infrastructure Complexity
Cloud computing adoption has taken the world by storm, and is accelerating unabated. According to Flexera’s annual State of the Cloud Report for 2020, 93% of respondents used multi or hybrid cloud strategies. This article examines different aspects of cloud infrastructure complexity, and approaches to mitigate it.
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Service Mesh Ultimate Guide 2021 - Second Edition: Next Generation Microservices Development
Get up to speed on the adoption of service mesh. Learn how to deploy service mesh solutions in heterogeneous infrastructures and application/service connectivity.
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Adoption of Cloud Native Architecture, Part 3: Service Orchestration and Service Mesh
This part 3 article in Cloud Native Architecture Adoption series, explores service interaction in a microservices based architecture, typical challenges we experience in distributed systems without proper governance, and how patterns like service orchestration and service mesh can help address those challenges.
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Bootstrapping the Authentication Layer and Server with Auth0.js and Hasura
When you're trying to prototype an MVP for your app and want to start iterating quickly, the upfront cost of setting up authentication can be a massive roadblock. The authentication layer requires significant work, and you must always be on the lookout for security vulnerabilities.
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Consistency, Coupling, and Complexity at the Edge
Successful use of a microservices architecture requires maintaining a clear separation of concerns in the various layers and by employing design principles best suited to each layer. While RESTful API design has become the standard for microservices, it can cause problems at the UI layer. Alternatives such as the Backend-for-Frontend pattern using GraphQL can provide better separation of concerns.
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Turning Microservices Inside-Out
Turning microservices inside-out means moving past a single, request/response API to designing microservices with an inbound API for queries and commands, an outbound APIs to emit events, and a meta API to describe them both. A database can be supplemented with Apache Kafka via a connecting tissue such as Debezium.
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Benefits of Loosely Coupled Deep Learning Serving
As deep networks are becoming more specialized and resource-hungry, serving such networks on acceleration hardware in tight-budget environments is also becoming difficult. Instead of using API frameworks, loosely coupled components can be preferred as an alternative. They bring high controllability, easy adaptability, transparent observability, and cost-effectiveness when serving deep networks.