If you haven't shouted "Bingo" yet, you have only yourself to blame. How can it be possible to use almost all of the bleeding-edge technologies, frameworks and platforms listed above successfully together in a real-world project away from the greenfield and Hello World demos? A field report.
In the future, many companies will try to grow their IT infrastructure with the help of the cloud or even move it completely to the cloud. Larger enterprises often call for multicloud. In terms of serverless, there are a few ways to achieve multicloud operation. Using AWS Lambda, a function can be made available and the whole thing can be made cloud-independent with Knative.
In times when ever larger amounts of data are processed and the speed of development in IT is - in order to keep up with the competition - becoming increasingly sought after, it is more and more important to be able to react scalably to a growing business volume and to establish a fast development and innovation cycle. This is exactly where serverless can help, as it eliminates much of the complexity of operation and allows you to bring speed to development.
AWS Lambda provides serverless computing in the form of functions as a service (FaaS). This means you can leverage on-demand infrastructure without the need for provisioning and hardware maintenance. Overall, Lambda is a great service for real-time data processing and backends. However, to achieve optimal performance you need to do some troubleshooting. In this article, you will learn how to improve cold start performance, implement efficient monitoring and logging, debug functions, and avoid timeouts.