Being a developer is awesome. Writing code, solving problems, and thinking of ingenious solutions for complicated algorithms is what we live for. But, the grass is not always so green on this side of the fence. Sooner or later, you need to get your hands dirty and deploy the app you worked so hard on. Deployments are not always easy. To be blunt, they can be challenging and time-consuming. That’s what we’ll solve in this tutorial.

Azure App Service is a platform-as-a-service (PaaS) offering for deploying applications to the cloud without worrying about infrastructure. App Service’s “serverless” approach removes the need to provision or manage the servers that run your applications, which provides flexibility, scalability, and ease of use. However, App Service also introduces infrastructure-like considerations that can impact performance and costs.

With over 200 products offered by AWS, when designing a solution, such as a micro-services based system using a number of these services at its core, it becomes rather challenging to not only monitor them but on the onset of a problem troubleshooting it and resolving it within the least amount of time becomes a daunting task. Building a monitorable system requires a deep understanding of the failure domain of the critical components, which is a tall order for a fairly complex system.

As the world is increasingly reliant on technology, software developers, cloud architects, and DevOps practitioners bear a responsibility similar to that of the health industry or to airplane pilots, for example. In this reality, cloud monitoring isn’t optional, it’s a matter of being professional. What is optional, however, is what monitoring solution to go for. Obviously, the one that best fits your specific needs but which one is it?

Non-Fungible Tokens, or short NFTs, are all the rage right now. Everyone and their pets are starting an NFT project. Some people got rich from using NFTs; others did not. Some say it’s the savior that will rip the power away from big corporations and give it back to the creators; others say it’s just a giant pyramid scheme.

In a serverless application, AWS Lambda functions are typically invoked by JSON-formatted events from other AWS services—like API Gateway, S3, and DynamoDB—and respond with JSON-formatted payloads. Having visibility into these function request and response payloads can provide context around your function invocations and help you uncover the root causes of Lambda function failures.