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In this talk I would like to share the workflow and tools we use to build, deploy and operate GraphQL APIs on our on-premise Kubernetes cluster.
I will share code and command examples explaining how we are operating our applications since our recent transition from REST APIs on Web servers to GraphQL APIs containers on Kubernetes.
This talk will not be about the difference between REST and GraphQL but focus on the workflow, tools and experience we gained in switching our run time environments and API models.
At Numberly, we have built and are operating our own on-premise Kubernetes cluster so we will also be talking about its capabilities and share some of the experience we gained in doing so.
- Our previous workflow and its limitations
- How we designed our Kubernetes cluster, its capabilities and the choices we made
- Developer workflow, environments management and deployment
- Our GraphQL stack, featuring a sample application
- What we're still working on to improve
Type: Talk (45 mins); Python level: Beginner; Domain level: Intermediate
CTO at Numberly, Open-Source contributor, Gentoo Linux developer, PSF contributing member.
I’ve been giving talks for a few years now, mostly to share my experience on architecture design, distributed systems, fault tolerance and scaling Python.
Numberly is a Marketing Technologist that helps its customers leverage the value of their data using all the digital communication channels available. We own and operate our infrastructure and are working on building large scale and highly available global architectures and applications. Our main development language to achieve this in all this variety of use cases is Python!
As a Gentoo Linux developer I focus mainly on clustering and NoSQL related packages. I'm a packager of various Open Source projects such as uwsgi, mongodb, consul, rabbitmq, keepalived, scylla...
You can catch me around with my handle: @ultrabug