When planning the creation of a website or web app, underestimating the time needed to deliver can sink a project. The longer the project is in development the more money, time, and other resources are required to see it to delivery. Also, the longer it is developed, the more that excitement for the project wanes and it might just be cast to the rubbish heap of other discarded projects.

Fortunately, over the years with advancements in tech stacks and the development of best practices, development times can be significantly reduced. This article looks at 10 easy-to-adopt practices that will reduce development time.

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As the author of GCeasy – Garbage collection logs analysis tool, I get to see a few interesting Garbage Collection Patterns again and again. Based on the Garbage collection pattern, you can detect the health and performance characteristics of the application instantly. In this post, let me share a few interesting Garbage collection patterns that have intrigued me.

1. Healthy Saw-tooth Pattern
Fig 1: Healthy saw-tooth GC pattern

You will see a beautiful saw-tooth GC pattern when an application is healthy, as shown in the above graph. Heap usage will keep rising; once a ‘Full GC’ event is triggered, heap usage will drop all the way to the bottom. 

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Fundamentally Hyperlambda is really just a Turing complete markup language, with some added capabilities resembling features from XSLT and XPath. You could argue Hyperlambda is the programming equivalent of YAML. On the index of « programming level abstractions » if we argue that CISC x86 assembly code is at level 1 (the bottom level) and C# and Java is at level 5, while Python and PHP are at level 10 – Hyperlambda is at level 100+ somewhere.

Of course, the point being, that 95% of the times you need a low level programming construct, Hyperlambda implicitly creates your C# objects and ties these together 100% correctly out of the box. This reduces the cognitive complexity of your resulting app’s code by orders of magnitudes. To illustrate this difference, please have a look at the following code snippet taken from Microsoft’s official documentation for how to correctly create an HTTP request from C#.

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Introduction

A URL shortener is a service that is used to create short links from very long URLs. Usually, short links have the size of one-third or even one-fourth of the original URL, which makes them easier to type, present, or tweet. Clicking on a short link user will be automatically redirected to the original URL. 

There are many URL shortening services available online, such as tiny.cc, bitly.com, and cutt.ly. Implementing a URL shortening service is not a complex task, and it is often part of system design interviews. In this post, I will try to explain the process of implementing the service. 

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Is observability mission critical at this point? The folks at New Relic think so. And they’re not alone, according to their recent whitepaper on observability 90% of respondents believe observability is strategically important to their business. It’s becoming increasingly difficult to understand what’s going on within software development organizations.

New Relic’s GVP & GM Buddy Brewer and SVP Greg Perotto join the podcast to discuss observability best practices, how to avoid data silos, the value of telemetry across the entire software life cycle and the five key insights of New Relic’s Observability Forecast.

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For everyone having done multithreading and async programming, it’s fairly obvious that the amount of complexity required to (correctly) implement threading and async increases the cognitive requirements to understand the codebase to sometimes unfathomable amounts. Typically, this results in difficult to track down bugs, and over time what we often refer to as « spaghetti code » or « the big ball of mud ». To put this into context, I’d like to put forth a statement in regards to this.

Everyone who (falsely) believes they understand threading and async, don’t understand threading and async!

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Today, in this article we will discuss basic concepts of Azure Function. An Azure Function is a perfect example of Serverless architecture or computes service. Using Azure Function, we can run the event-based code without managing any infrastructure. Since the Azure function is a trigger-based service, so it always executes a script of a block of code in response to a variety of events. 

An Azure Function can also be used to achieve the decoupling, high throughput or response, reusability of code, etc. So, we will discuss the Azure Functions in all aspects in four parts. Today, in the first part of this article series, we will discuss the below topics:

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DataWeave is a programming language designed for transforming data. It is the primary language of MuleSoft for data transformation and an expression language for components and connectors configuration.

Mulesoft released Dataweave 2.4.0 for Mule Version 4.4. The 2.4.0 version of DataWeave introduced many new features. In this post, we will see one of the newly introduced DataWeave modules.

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Welcome to the third blog post in our “Kubeflow Fundamentals” series specifically designed for folks brand new to the Kubelfow project. The aim of the series is to walk you through a detailed introduction of Kubeflow, a deep-dive into the various components, and how they all come together to deliver a complete MLOps platform.

If you missed the previous installments in the “Kubeflow Fundamentals” series, you can find them here:

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If you’re not using fluent assertions in your tests yet and just rely on basic JUnit assertions, you might be missing out on a simple but very effective tool to write high-quality test code. The article starts with a short recap about the virtues of fluent assertions and how they address the shortcomings of basic assertions.

But while very much in favor of fluent assertion I think that current implementations don’t realize their full power: Problems are demonstrated in AssertJ, the main fluent assertion library for Java. Finally, I present a new solution to overcome these issues.

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