I’d like to share with you the architecture and programming pattern we've been using to build Cloud Native applications. The use case I'm going to present is a RESTful application deployed on AWS, using AWS API Gateway and AWS Lambda. I want to show how by adopting specific AWS components and programming paradigms, we can increase the reliability of the applications we write, while also improving their maintainability.

You may be wondering, what is the relationship between high-performance organisations and Cloud Native? It’s quite simple, really. Cloud Native is a sociotechnology, meaning it encompasses technical elements, like containers and Kubernetes, social elements, like strategic leadership, and sociotechnology elements, such as microservices.

One of the main drivers behind Kubernetes’ success is the ability to manage containerised workloads and services by specifying a declarative configuration and letting the system make it happen. This effectively automates and abstracts away all those tedious and error-prone step-by-step deployment tasks usually known as ‘operations’.

First, some good news: the DevOps field’s expertise and performance is growing rapidly. Its best practices, like a clear change-approval process, not only improve speed and stability, but also help decrease engineer burnout.

Debugging Docker containers can be a very challenging process. Here, I’ll share a few basic techniques for debugging containers—mostly Docker ones, but the techniques are also valid for many other types of Linux container engines. (The methods I’ll detail here are intended for Linux-based systems.)