As Serverless is on the rise, the art of debugging and tracing is changing, too, as well as the day to day work life of developers and admins. At the Serverless Architecture Conference 2019 in The Hague we talked to Billie Thompson, cloud-native consultant at Armakuni, about how Serverless is affecting the IT industry and how tracing is done in the times of Serverless.
The recent Serverless Architecture Conference in The Hague, Netherlands brought together developers and DevOps engineers from across Europe. And if any topic was guaranteed to ignite a heated debate among participants it was Knative vs. Serverless.
Serverless is a buzzword that everybody seems to be talking about nowadays. You may like the term or not, but the important thing here is what it describes. In a nutshell, Serverless means the application's scale is constantly adapted to ensure that you always have the exact amount of resources you currently need available. In case of doubt, this may even mean: none at all! For you as a user, this means that you always pay only for the capacity you need to provide a response to the queries to your application. If there are no users or requests, you pay nothing at all.
What are the benefits of serverless computing? What exactly is Knative and what features are still in development? In our interview with Evan Anderson, Senior Staff Software Engineer at Google, he gives an introduction to the new shiny serverless tooling based on Kubernetes. He also talks about the benefits and the downsides of serverless computing and why it is such a big topic at the moment.
With three years on the market, GraphQL is a sophisticated and established alternative to REST. It should be taken into consideration when creating or further developing an API. Various applications such as Facebook, Instagram, and XING already successfully use this REST alternative. This is enough reason to give an insight into how GraphQL can be integrated into modern serverless architectures with little effort.
In the interaction between GraphQL and AWS Lambda, a highly scalable implementation is presented that can be adapted to different architectures and frameworks.