Config servers are widely used in microservices architectures as placeholders for configurations. They also provide a centralized repository for users to manage configs for multiple applications.
Today, we are going to look at an example of how to use Nacos as a config server with Spring Cloud for Alibaba. The example is a Spring Boot application, running a Nacos server locally.
Malcolm Gladwell famously shed light on the role of ‘connectors’ in his best selling book The Tipping Point. He regarded connectors as, obviously, people who know a lot of people, but more importantly, people who can connect different worlds and spot things in one world that can be applied in another.
Or as Gladwell himself said, "connectors are people who link us up with the world. People with a special gift for bringing the world together."
It is no question that the future is going to be automated. We have automated self-driving vehicles, voice assistants, call center and text-based bots, and so much more. However, what does it take to bring automation to your business?
The short answer is that it doesn’t take much more than building standard applications if you’re using the right tools.
With the rapid development of cloud computing technology, an increasing number of developers are deploying applications to Alibaba Cloud Elastic Compute Service (ECS) instances. This tutorial describes how to deploy a Java application developed locally to an Alibaba Cloud ECS instance using Cloud Toolkit.
The coding method is similar — no matter whether you compile Java applications that run on the cloud or locally. Therefore, this article takes a Java servlet for printing "Hello World" on a web page as an example to explain the deployment method.
I had the opportunity to meet with Luc D’Urso, CEO, Ferhat Kaddour, V.P. Sales and Alliances, and Mike Oakes, Sr. Solution Architect at Atempo, the ninth company on IT Press Tour #31.
Their vision of the future is that data volumes are exploding and they will continue to grow at 61% per year through 2025. 80% of data will be unstructured, 50% will reside in the cloud, and 50% on-prem. Meeting the challenge of the data tsunami over-washing every industry as digital transformation is driving all sectors.
Hello everyone, in this article, I’m going to share my experience of when I tried to do a conversion in Mule 4. I will briefly explain the purpose of this article while showing the code that I can implement in Mule 3 and how I have to write it in Mule 4 in order to get a similar response.
As we all know, Mule 4 is trending in the market, which makes Mule 3 people migrate their code from Mule 3 to Mule 4.
In a previous article, we talked about how Apache RocketMQ fine-tuned the bottlenecks related to latency.
Remember Little’s law?
Welcome to our latest episode of Tom’s Tech Notes! In this episode, Tom asks what our collection of industry experts’ favorite use cases and benefits of microservices are.
As a primer and reminder from our initial post, these podcasts are compiled from conversations our analyst Tom Smith has had with industry experts from around the world as part of his work on our research guides.
The opening scene from the 1993 Michael Douglas film Falling Down (above) could very well have been shot yesterday. No, I’m not talking about the 90s buzz cut or the short sleeve collared shirt, but I am talking about its spot on depiction of the hell that is gridlock.
Traffic is at a standstill, the weather is sweltering, and Michael Douglas just can’t even — to the point where he actually abandons his vehicle under an overpass to alleviate the stress of it all. And let’s be honest, we’ve all dreamt about doing the exact same thing at one time or another.
It’s easy for modern, distributed, high-scale applications to hide database performance and efficiency problems. Optimizing performance of such complex systems at scale requires some skill, but more importantly it requires a sound strategy and good observability, because you can’t optimize what you can’t measure. This session explains a performance measurement and optimization process anyone can use to deliver results predictably, optimizing customer experience while freeing up compute resources and saving money.
The session begins with what to measure and how; how to analyze it; how to categorize problems into one of three types; and three matching strategies to use in optimization as a result. It is a recursive method that can be used at any scale, from a data center with many types of databases cooperating as one, to a single server and drilling down to a single query. Along the way, we’ll discuss related concepts such as internally- and externally-focused golden signals of performance and resource sufficiency, workload quality of service, and more.
