With the current trend of data-intensive products, accessing the data in a structured way for various clients is challenging. The existing solutions are monolithic and any small changes in the application, will require the entire application to be redeployed and scaling them is also a great challenge.
To overcome this problem the industry is inclining towards the GraphQL way to implementing APIs for their products/platforms. Having said that, to catch with the scalability and modularity of the product we need to divide the components into various DGS’s (Domain Graph Service). When we are diving the components into various DGS’s, deployment and scalability of them are becoming a bottleneck. We at BigThinkCode solved this issue by implementing the GraphQL API gateway, which acts as an interface for all the DGS’s. Now since the connectivity is based on the API gateway the DGS’s can be individually deployed as separate k8 pods and these pods can be scaled horizontally based on the incoming traffic for the specific DGS.
As a result of this implementation, we were able to scale up and scale down the resources as per the needs of the application and its traffic. This has also helped the team to develop and deploy the pods in need basis. It has also avoided in deploying the solutions as a whole and deploy them as separate DSG’s thus making it more robust and agile.
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