Serverless architectures are the next step in the evolution of cloud services. The first attempts at walking with them are easy. However, you should know the stumbling blocks in order to be able to avoid them. This article presents the typical challenges with corresponding possible solutions.
Java is still the first choice when it comes to software development for business use . However, the development of Java software alone is not enough: machines, operating systems, JREs, application servers, etc. are required for productive use - and large frameworks and libraries are also required as the basis for code functionality. This overhead hurts more the simpler the required functionality is, because it makes development, testing, and operation more difficult. The alternative concept: Serverless.
Why does it have to be "Serverless or Microservices"? It should be "Microservices with Serverless"! Based on some of the generally accepted principles of microservices, we can use serverless architectures and technologies to build highly focused microservices. Let's take a pragmatic and concise approach to building microservices with Azure Functions, Azure Service Bus, Azure Storage, and other services and tools. And it works for almost all software developers: Java, .NET, Node.js, and even Python.
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.