In this article, I will discuss the role of platform engineering in the software development lifecycle, its motivations, and tasks, and describe several approaches and examples for building your own platform.
First, it is essential to provide a disclaimer: if your company consists of a single team, if it is a small company, or if it is a startup, then platform engineering may not be suitable for you. Platform engineering requires dedicated resources and personnel focused exclusively on these tasks due to the scope involved.
Every six months, the volume of Deep Fake content doubles. With each iteration, these fakes become more sophisticated and convincing, posing significant challenges in detection and prevention. To address this escalating issue, we have embarked on a comprehensive project aimed at developing a robust solution for Deep Fake detection and mitigation.
Project Overview Our project encompasses several key tasks:
Analyzing Current Detection Methods: We start by evaluating the existing Deep Fake detection techniques to understand their strengths and weaknesses.
We are excited to present our innovative solution tailored for Sika Company.
The Challenge Large international companies, like Sika, generate enormous volumes of data, including data sheets, reports, emails, and more. This data often comes in various languages and formats, making it incredibly challenging to manage and utilize effectively.
Our Solution Our solution leverages the latest advancements in artificial intelligence to transform how we interact with complex data sets. Traditional methods often involve labor-intensive manual work, which is both time-consuming and costly.
In the previous installment of this series, I discussed the rationale behind using interfaces and how they can be defined across various programming languages. Now, we shift our focus to functional programming. This topic may appear more intricate, primarily because its roots are deeply tied to mathematical concepts. Such mathematical nuances give rise to certain prerequisites. Before diving deep, let’s establish a foundational understanding by defining some key terms.
Note: Regrettably, the Go language is somewhat limiting in certain respects.
In the previous article, we looked at how interfaces look in an imperative approach. In this one, we will explore how we can hide something behind an interface when we have declarative code.
Helm (YAML) Although we can write a program to create entities in k8s, using available APIs and libraries in different languages, the most common way is to write configuration files in YAML language. These files describe the requests to the k8s API, executed with the kubectl program.
This article continues the previous one, where I delved into the significance of interfaces, highlighting their benefits and issues. In the present article, we’ll examine interfaces through practical examples to understand how they’re organized from a language design perspective and explore their advantages and disadvantages. Additionally, I’ll explain how interfaces can be implemented in those programming languages that lack them (as a keyword).
Go Indeed, in the Go programming language, support for interfaces is inherent from the get-go, as its creators intended to design a language that allows developers to rediscover the joy of programming.
