The Road to GraphQL At Enterprise Scale

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • mercurius

    Implement GraphQL servers and gateways with Fastify

    GraphQL Gateway is primarily responsible for serving GraphQL queries to consumers. It takes a query from a client, breaks it into smaller sub-queries, and executes that plan by proxying calls to the appropriate downstream subgraphs. When we started our journey, there was only Apollo Federation in the arena, and we used it. Still, now you can look at other options (e.g. Mercurius, Conductor, Hot Chocolate, Wundergraph, Hasura Remote Schemas), compare benchmarks and decide what's important and preferable for your needs. The Gateway provides a unified API for consumers while giving backend engineers flexibility and service isolation.

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  • graphql-schema-registry

    GraphQL schema registry

    Completely open-sourced solution written with similar tools

  • zipkin

    Zipkin is a distributed tracing system

    From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.

  • supergraph-demo-opentelemetry

    open-telemetry config for Apollo Server and Apollo Gateway

    For example, let’s take a look at GitHub repository with integrated Open Telemetry to Apollo Federation.

  • jaeger

    CNCF Jaeger, a Distributed Tracing Platform

    From the perspective of the realization of GraphQL infrastructure, the interesting direction is "Finding". How to find the problem? How to find the bottleneck of the system? Distributed Tracing System (DTS) will help answer this question. Distributed tracing is a method of observing requests as they propagate through distributed environments. In our scenario, we have dozens of subgraphs, gateway, and transport layer through which the request goes. We have several tools that can be used to detect the whole lifecycle of the request through the system, e.g. Jaeger, Zipkin or solutions that provided DTS as a part of the solution NewRelic.

  • wundergraph

    WunderGraph is a Backend for Frontend Framework to optimize frontend, fullstack and backend developer workflows through API Composition.

    GraphQL Gateway is primarily responsible for serving GraphQL queries to consumers. It takes a query from a client, breaks it into smaller sub-queries, and executes that plan by proxying calls to the appropriate downstream subgraphs. When we started our journey, there was only Apollo Federation in the arena, and we used it. Still, now you can look at other options (e.g. Mercurius, Conductor, Hot Chocolate, Wundergraph, Hasura Remote Schemas), compare benchmarks and decide what's important and preferable for your needs. The Gateway provides a unified API for consumers while giving backend engineers flexibility and service isolation.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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