In this tutorial, we are going to try out a Spring Boot Swagger-enabled REST project and explore how the validation constraints can be utilized automatically for enriching Swagger models.
We are going to refer to https://www.baeldung.com/swagger-2-documentation-for-spring-rest-api and https://spring.io/guides/gs/rest-service/ as starting points.
Hi, Spring fans! In this installment of Spring Tips, we’re going to look at Alibaba’s Apache RocketMQ. We’ve talked some about Alibaba in Spring Tips before. Check out the earlier Spring Tips installment in which we explore some of Spring Cloud Alibaba.
In order to use Apache RocketMQ, you’ll need to follow the steps in the RocketMQ quickstart. This Spring Tips installment introduces Apache RocketMQ, originally a technology developed and used internally at Alibaba and proven in the forge of 11/11, the famous Chinese sales holiday, sort of like “Cyber Monday,” or “Black Friday,” in the US. Sort of like that, but waaaaaay bigger. In 2019, Alibaba (alone, with no other e-commerce engines involved), made almost $40 billion USD in 24 hours. This required that trillions of messages be sent through something that could scale to meet the demand. RocketMQ is the only thing they could trust.
In this article, we focus our attention on the DevOps.
What is DevOps? How is it different from Agile? What are the popular DevOps Tools? What is the role of Docker, Kubernetes and Azure DevOps in DevOps. Let’s get started with a simple use case.
Unlike analysts at the large firms, who have to specialize in narrow market segments to avoid stepping on each other’s toes, we at Intellyx have the luxury of covering cross-cutting topics that align with business needs.
One of our tools in trade: looking closely at how two different markets interrelate and thus provide business value. In today’s Cortex, I’ll consider the relationship between low-code and cloud-native computing.
The usage of ML is increasingly rising these years. Businesses are impresses with a range of opportunities ML enables for them. However, they’re still struggling to deploy ML models because of the long duration and complexity of the process.
When a business has to come up with the prediction of a particular data set, the traditional approach includes the performance of the following actions:
As our business, Shopee, boomed, our team faced severe challenges in scaling our back-end system to meet the demand. Our previous article introduces how we use TiDB, an open-source, MySQL-compatible, hybrid transactional and analytical processing (HTAP) database, to scale-out our system so that we can deliver better service for our users without worrying about database capacity.
There are so many databases available in the market. How do you choose the right one? In this post, I’ll share our thoughts with you. I hope this post can help you when you’re comparing multiple databases and looking for the right fit for your application.
You can build a custom skill for Alexa by extending a servlet that accepts requests from and sends responses to the Alexa service in the cloud.
This project will walk through how to build an Alexa Skill with Spring Boot and Http Servlet mapping examples.
Apache Ignite as a distributed database and caching platform needs end-to-end monitoring to act on time. Historically, Apache Ignite provides a set of API and instrumentation to gather application-specific information and metrics by the external tools. In release 2.8.0, Apache Ignite improved the monitoring capabilities and introduced some nice features like "System views subsystem" and "Metrics subsystem."
In this short article, we are going to explore the Apache Ignite new monitoring opportunities and how to use different tools and technics to gather metrics for diagnosis. Anyway, the full release notes of version 2.8.0 can be found here.
Health checks are a fundamental part of our APIs. I guess they fall in that category of "non-functional-but-heavily-required" things. More or less like a good part of the infrastructure code.
They don’t add business value per se but have an enormous impact for those in IT, like DDD and design patterns. You can normally see them in conjunction with container orchestration or monitoring tools to ensure that the system is alive and kicking.
When you are creating a RESTful API, it’s easy to get overwhelmed by all the different things you need to take into consideration: throttling, REST verbs, security, authentication, input validation, etc., so it’s easy to forget about the more subtle issues that can make a lot of difference in the long run. Most of the topics described above were already discussed (extensively if not exhaustively) elsewhere, so I’ll try to give my take on how to create a readable API for developers to consume. It’s a more subtle and less-discussed topic that can have a significant impact on the success of your API. After all, an API that no one can read, no one will use.
Use a convention for endpoint URLs and method names: plural vs singular – pick one. There is nothing worse than trying to fetch information from /api/v1/orders/{id} and debugging this forever just to find out that this is the only place where you have chose to use /api/v1/order/{id} (singular instead of plural) as the endpoint URL.
