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GraphQL is a query language for APIs. Today, GraphQL is one of the most popular protocols for building web APIs. It’s a suitable choice for driving integrations between microservices and building integrations with frontend applications. As an alternative to REST, GraphQL lets developers construct requests that pull data from multiple data sources in a single API call. Therefore reducing the network calls and bandwidth saves the battery life and CPU cycles consumed by the backend applications.
Why GraphQL ?
To avoid multiple versioning of our rest API.
Ask for what we need: Client has a provision to ask only those fields which they needs. There would be no handling on server side specific to the platform.
Avoid multiple API calls to get the related data. GraphQL allows us to get the related data in a single request.
Speed up the application performance.
These are some of the reasons that make GraphQL an excellent choice for building the service API for Marionette. As we explain the specification for the trading APIs, we will also review scalar types of GraphQL, design of custom object types, as well as queries and mutations. (If you are just starting out with GraphQL, Apollo Odyssey has some great interactive tutorials to help you.)
GraphQL for Managing Marionette’s APIs
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Further, just as we can use SQL to define schemas for our database tables, Marionette uses GraphQL to write specifications that describe the type of data queried from the servers. A GraphQL API specification is called a schema, and it’s written in a standard called Schema Definition Language (SDL).
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Containers
Brief introduction so what containers are?
How are they used in Marionette?
Do they satisfy the current Marionette needs?
What will we do if we need to scale current needs?
Containers have become a dominant concept in server-side software deployment and for many are the de facto choice for packaging and running microservice architectures. The container concept, popularized by Docker, often allied with a supporting container orchestration platform like Kubernetes, become a popular choice for running microservice architectures at scale.
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