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Real-time API's with GraphQL
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Sandeep Singh
October 14, 2018
Research
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Real-time API's with GraphQL
Sandeep Singh
October 14, 2018
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Transcript
Real-Time API’s with GraphQL Sandeep Singh initialspark.co.uk @initial_spark
◦ What is GraphQL ? ◦ Why it exists and
the problems it aims to solve ? ◦ GraphQL core concepts ◦ Real-Time API’s – the what, why and how Agenda @initial_spark
GraphQL is a declarative query language for your API @initial_spark
@initial_spark
◦Built on specification ◦Hierarchical ◦Client‐driven ◦Strongly typed What is GraphQL?
@initial_spark
Q: Why GraphQL? @initial_spark
◦Efficiency ◦Predictability ◦Versioning ◦Caching ◦Security, tooling, documentation and more Modern
API considerations @initial_spark
Let’s look at an example… @initial_spark
@initial_spark
Efficiency @initial_spark
Efficiency @initial_spark GraphQL API Mongo DB AWS Lamba REST API
SOAP Service HTTP TCP/IP HTTP SOAP Optimisted data for each channel
Versioning Evolution @initial_spark
Tooling & DX @initial_spark
Introspection { __schema{ types{ name } } } • Query
schema, types and fields • Build tools o Auto complete / Validate (graphiql) o Code generation o Documentation @initial_spark
GraphQL Core Concepts @initial_spark
Schema Type System Query Language GraphQL Core Concepts @initial_spark
GraphQL Core Concepts - Resolvers @initial_spark
Schema Type System Query Language o Operations • Queries –
read • Mutations – write • Subscriptions – real-time o Alias o Fragments GraphQL Core Concepts @initial_spark
Lets build a GraphQL API! @initial_spark
@initial_spark
◦ Unpredictable Execution ◦ Handling File Upload ◦ Cache at
Network Level ◦ Authentication/Authorisation GraphQL - Challenges @initial_spark
Q:What about Real-time data? @initial_spark
@initial_spark Chat Notifications Live feed Collaborative
◦ Pull ◦ Polling - Short/Long - HTTP ◦ Push
◦ Subscriptions - Event driven ◦ Live queries - Infinitely fast/cheap polling (State driven) Real-Time API’s @initial_spark
◦ Real time events ◦ Idea: Server pushes data to
client when something ‘interesting’ occurs ◦ The client defines the shape of the data pushed to it Subscriptions – Event Based @initial_spark
◦ The initial state is large, but the incremental change
sets are small ◦ You care about low-latency updates in the case of specific events, e.g. chat application where users expect to receive new messages in a matter of seconds Subscriptions – When to use @initial_spark
Subscriptions Implementation @initial_spark
Subscriptions (Redis, Kafka, MQ, own?) @initial_spark Request / Response Bi-Directional
Transport (SSE, websockets etc) HTTP Subscription(s) GraphQL Domain Events Events
@initial_spark
Let’s look at another example… @initial_spark
@initial_spark GraphQL API Run Mutation Trigger Subscription subscription {patientDischarged{…}} PAS
View (Admin) Ward View (Nurse)
Lets have some fun with subscriptions @initial_spark
Advanced features – Enrich payload @initial_spark
@initial_spark There isn’t such thing as a free lunch…
◦ Scaling state is hard ◦ Who’s subscribed/ how do
we send messages etc ◦ QOS ◦ Throttling ◦ Buffering Subscriptions - Challenges @initial_spark
◦ http://graphql.org/learn/ ◦ https://www.youtube.com/watch?v=bn8qsi8jVew - Lee Byron ◦ https://github.com/apollographql/apollo-client ◦
https://github.com/initialspark/real-time-apis-graphql ◦ https://www.graphqlhub.com/ ◦ https://www.youtube.com/watch?v=4_Bcw7BULC8 - Authentication Resources @initial_spark
Thank you ! You can find me at @initial_spark &
initialspark.co.uk