There's a lot of focus on microservices these days--everyone is refactoring monolitic applications into platforms built on microservices architecture or creating microservices to attend to new business needs. But though virtually every business has decided to migrate toward microservices architecture, not everyone has decided how to do so.
If you've used MongoDB or been a part of users' conversations about MongoDB, you'll be aware that, while it's one of the most successful NoSQL databases available, it has faced a lot of criticism for not supporting multi-document transactions. Now, that's about to change.
(This article was first published on LinkedIn.)
When developing applications, you’ve probably faced a situation in which you need to integrate with third-party APIs, either to improve a service that provides users with data or to add a new functionality. Many software engineers solve this by mapping complex DTOs, but there's a much easier method available.
Some time ago I wrote about how to set up a .NET Core Web API to report metrics to New Relic. Now, I'm going to show you how to use New Relic--or any other monitoring platform, such as Azure Application Insights--to get a performance baseline for your API.
Visual Studio Code's Pipe transport debug configuration makes debugging many non-standard configurations easy. In this article, I will demonstrate how to leverage this tool to debug a .NET Core application running inside a Kubernetes cluster.
Over the years I have seen several approaches for validating inputs (@RequestParam, @RequestBody, etc.) for REST endpoints. Many of these approaches are pretty manual and require explicitly calling a validation mechanism. But is there a way to automate this process while writing as little code as possible, still validating all inputs, and responding with friendly messages to consumers?