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Is your organization ready to move containerized workloads into production or yet struggling with these challenges? Adopting complex stateful workloads with many dependencies, deploying containerization tooling without well-framed DevOps practices, and becoming gripped into vendor lock-in faster may be a few of such challenges. Having the right DevOps team in place and finding out how Kubernetes integrates with your company’s technological infrastructure to undergo effective legacy application modernization should be the way out. As an organization, you should consider if you have the requisite roles and skillsets before adopting new technologies. You must decide on runtime and orchestration engines in technical terms while selecting containerization workloads with utmost care and attention.

With more than 70% of organizations running containerized applications in production, Kubernetes has emerged to be one of the most sought-after methods to organize containers. Here are a few of the Kubernetes best practices that ensure its adoption truly advancing container deployment.

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What is Deno?

Deno a pristine method to compose worker-side JavaScript. It solves many of the problems that Node does. It was created by the same person as Node. It uses the V8 JavaScript engine under the hood but the rest of the runtime is implemented in Rust and Typescript.

What Reason Does Deno Utilize Rust?

Deno may be a safe TypeScript run-time on Chrome V8. It had been initially written in Go and now has been revamped in Rust to remain far away from potential garbage collector issues. Deno is like Node js yet is centered around security. The rationale that Deno made was JavaScript. Significantly more horrendous than having a competitor who understands your thing back to front, Deno was made expressly to fix what Dahl saw due to the crucial weaknesses of NodeJs — including security issues, use of a centralized repository system (npm), and heavy tooling.

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Gartner predicts that by 2023, over 50% of medium to large enterprises will have adopted a Low-code/No-code application as part of their platform development.
The proliferation of Low-code/No-code tooling can be partially attributed to the COVID-19 pandemic, which has put pressure on businesses around the world to rapidly implement digital solutions. However, adoption of these tools — while indeed accelerated by the pandemic — would have occurred either way.
Even before the pandemic, the largest, richest companies had already formed an oligopsony around the best tech talent and most advanced development tools. Low-Code/No-code, therefore, is an attractive solution for small and mid-sized organizations to level the playing field, and it does so by giving these smaller players the power to do more with their existing resources.
While these benefits are often realized in the short term, the long-term effect of these tools is often shockingly different. The promise of faster and cheaper delivery is the catch — or lure — inside this organizational mousetrap, whereas backlogs, vendor contracts, technical debts, and constant updates are the hammer.
So, what exactly is the No-Code trap, and how can we avoid it?

What is a No-Code Tool?

First, let’s make sure we clear up any confusion regarding naming. So far I have referred Low-Code and No-Code as if they were one term. It’s certainly easy to confuse them — even large analyst firms seem to have a hard time differentiating between the two — and in the broader context of this article, both can lead to the same set of development pitfalls.
Under the magnifying glass, however, there are lots of small details and capabilities that differentiate Low-code and No-code solutions. Most of them aren’t apparent at the UI level, leading to much of the confusion between where the two come from.
In this section, I will spend a little bit of time exploring the important differences between those two, but only to show that when it comes to the central premise of this article they are virtually equivalent.

Low-Code vs. No-Code Tools

The goal behind Low-Code is to minimize the amount of coding necessary for complex tasks through a visual interface (such as Drag ‘N’ Drop) that integrates existing blocks of code into a workflow.
Skilled professionals have the potential to work smarter and faster with Low-Code tools because repetitive coding or duplicating work is streamlined. Through this, they can spend less time on the 80% of work that builds the foundation and focuses more on optimizing the 20% that makes it different. It, therefore, takes on the role of an entry-level employee doing the grunt work for more senior developers/engineers.
No-Code has a very similar look and feel to Low-Code, but is different in one very important dimension. Where Low-Code is meant to optimize the productivity of developers or engineers that already know how to code (even if just a little), No-Code is built for business and product managers that may not know any actual programming languages. It is meant to equip non-technical workers with the tools they need to create applications without formal development training.
No-Code applications need to be self-contained and everything the No-Code vendor thinks the user may need is already built into the tool.
As a result, No-Code applications create a lot of restrictions for the long-term in exchange for quick results in the short-term. This is a great example of a ‘deliberate-prudent’ scenario in the context of the Technical Debt Quadrant, but more on this later.

Advantages of No-Code Solutions

The appeal of both Low-Code and No-Code is pretty obvious. By removing code organizations can remove those that write it — developers — because they are expensive, in short supply, and fundamentally don’t produce things quickly.
The benefits of these two forms of applications in their best forms can be pretty substantial:
  • Resources: Human Capital is becoming increasingly scarce — and therefore expensive. This can stop a lot of ambitious projects dead in their tracks. Low-Code and No-Code tools minimize the amount of specialized technical skills needed to get an application of the ground, which means things can get done more quickly and at a lower cost.
  • Low Risk/High ROISecurity processes, data integrations, and cross-platform support are all built into Low-Code and No-Code tools, meaning less risk and more time to focus on your business goals.
  • Moving to Production: Similarly, for both types of tools a single click is all it takes to send or deploy a model or application you built to production.
Looking at these advantages, it is no wonder that both Low-Code and No-Code have been taking industries by storm recently. While being distinctly different in terms of users, they serve the same goal — that is to say, faster, safer and cheaper deployment. Given these similarities, both terms will be grouped together under the ‘No-Code’ term for the rest of this article unless otherwise specified.

List of No-Code Data Tools

So far, we have covered the applications of No-Code in a very general way, but for the rest of this article, I would like to focus on data modeling. No-Code tools are prevalent in software development, but have also, in particular, started to take hold in this space, and some applications even claim to be an alternative to SQL and other querying languages (crazy, right?!). My reasons for focusing on this are two-fold: 
Firstly, there is a lot of existing analysis around this problem for software development and very little for data modeling. Secondly, this is also the area in which I have the most expertise.
Now let’s take a look at some of the vendors that provide No-Code solutions in this space. These in no way constitute a complete list and are, for the most part, not exclusively built for data modeling. 

1. No-Code Data Modeling in Power BI

Power BI was created by Microsoft and aims to provide interactive visualizations and business intelligence capabilities to all types of business users. Their simple interface is meant to allow end-users to create their own reports and dashboards through a number of features, including data mapping, transformation, and visualization through dashboards. Power BI does support some R coding capabilities for visualization, but when it comes to data modeling, it is a true No-Code tool.

2. Alteryx as a Low-Code Alternative

Alteryx is meant to make advanced analytics accessible to any data worker. To achieve this, it offers several data analytics solutions. Alteryx specializes in self-service analytics with an intuitive UI. Their offerings can be used as Extract, Transform, Load (ETL) Tools within their own framework. Alteryx allows data workers to organize their data pipelines through their custom features and SQL code blocks. As such, they are easily identified as a Low-Code solution.

3. Is Tableau a No-Code Data Modeling Solution?

Tableau is a visual analytics platform and a direct competitor to Power BI. They were recently acquired by Salesforce which is now hoping to ‘transform the way we use data to solve problems—empowering people and organizations to make the most of their data.’ It is also a pretty obvious No-Code platform that is supposed to appeal to all types of end-users. As of now, it offers fewer tools for data modeling than Power BI, but that is likely to change in the future.

4. Looker is a No-Code Alternative to SQL

Looker is a business intelligence software and big data analytics platform that promises to help you explore, analyze, and share real-time business analytics easily. Very much in line with Tableau and Power BI, it aims to make non-technical end-users proficient in a variety of data tasks such as transformation, modeling, and visualization.

You might be wondering why I am including so many BI/Visualization platforms when talking about potential alternatives to SQL. After all, these tools are only set up to address an organization’s reporting needs, which constitute only one of the use cases for data queries and SQL. This is certainly a valid point, so allow me to clarify my reasoning a bit more.

While it is true that reporting is only one of many potential uses for SQL, it is nevertheless an extremely important one. There is a good reason why there are so many No-Code BI tools in the market—to address heightening demand from enterprises around the world — and therefore, it is worth taking a closer look at their almost inevitable shortcomings.

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As a consistent user and developer on the OpenShift platform over the years, I’ve tried helping users by sharing my application development content as we’ve journeyed from cartridges all the way to container base development.

With container based development we’ve also transitioned from using templates to define how to deploy our tooling and applications, to operators. There are many examples of how to work with the templated versions of our applications around decision management and process automation found on Red Hat Demo Central and JBoss Demo Central.

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No-code and low-code technologies have been making inroads for years but have never quite delivered on their promise as reliable alternatives to traditional software development for complex, business-critical applications. Then COVID-19 forced a new, expedited timeline for moving analog in-person processes to semi- or fully-automated online ones. At the same time, IT and engineering roadmaps have been thrown out the window as technical teams scramble to adjust to new distributed working conditions while juggling multiple "hair on fire" problems. As a result, operations and business teams have been left with urgent needs for new business applications and scant developer resources, creating the perfect storm for no- or low-code solutions to emerge as the savior of productivity. But decision-makers should be wary of treating these platforms as a panacea to avoid costly failures and lost time.

What Are No-Code and Low-Code Technologies?

To understand how no- and low-code solutions fill the gap between business demand for development and supply of technical resources, it is helpful to understand what those terms mean exactly. No-code platforms allow people with no technical knowledge to stand up complex, cloud-based business applications using simple, drag-and-drop tooling. Relatedly, low-code platforms are also based on the concept of abstraction through pre-built software building blocks oriented towards accelerating time to development by reducing the amount of “original” code that needs to be written in any given application. Perhaps because of their shared DNA, there is a trend towards convergence; as no-code platforms become more powerful and versatile with add-ons and application marketplaces, and low-code platforms build features to require less coding. Given this trend, we can collectively refer to these platforms as Low-code Development Platforms.

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As a cloud-native developer you’ve installed an OpenShift Container Platform development environment on your local machine, but what’s next?

What can you do with the fully stocked container registry provided to you?

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Time for another update on installing the Red Hat Process Automation Manager with my easy install project.

Installing the latest process automation tooling for your development projects in just minutes on your very own machine has never been easier.

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Companies today are becoming more and more application-driven, which in turn is making every company today a software company – whether they know it yet or not. With this, companies are having to issue more application releases than ever before, and their software delivery cycles are increasingly complex. Therefore, in order to cope with the number of applications they are supporting, large enterprises now need hundreds and sometimes thousands of test environments. But as the number of environments continues to rise, successfully managing them all is becoming more and more challenging by the day.

A recent survey conducted by Enterprise Management Associates (EMA), titled the EMA 2018 Test Environment Management Survey, found that only 4% of large enterprises have fully integrated test environment management (TEM) processes in the DNA of their application development, despite the overarching benefits that TEM tools can bring to businesses across a range of industries. Given the speed and efficiency improvements that TEM tools provide, the question should be asked, why aren’t more businesses integrating them effectively or even at all?

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