AIAfterHours

Introduction: The Dawn of a New Era 🌅 Hey there, visionaries! Let's talk about something that's setting the tech world on fire—Artificial Intelligence (AI). But not just any AI; I'm talking about Generative AI and its summarisation capabilities. This transformative tech isn't just for generating cute poems or chatbots; it's a game-changer for Infrastructure Automation and DevSecOps teams. What is Generative AI? 🧠 In a nutshell, Generative AI algorithms create new data that's similar to the data they were trained on. Imagine a machine writing code, generating configs, or even predicting potential bottlenecks in your system before they happen. This isn't just automation; it's like having an extra engineer on your team who never sleeps. Subtypes of Generative AI 🌳 Text-based Models: Think GPT-4, which can write anything from poetry to code. Image-based Models: Generates or modifies images. Think DeepFakes or image-enhancement models. Data Simulators: ...

 In today’s rapidly changing business landscape, platform engineering has emerged as a critical element for modern organizations. It enables businesses to create and maintain a set of proprietary internal tools that streamline the software development process, especially when working with cloud applications. An effective internal developer platform (IDP) can automate tedious tasks, reduce cognitive loads for developers, and speed up application development while scaling with a company’s operational needs. In this article, we will explore what platform engineering is, the role of an IDP in software development, how to build a platform engineering team, and the best practices and challenges involved in creating a cutting-edge IDP. Platform engineering is not just the next phase of DevOps; it is the supporting backbone that makes DevOps effective. The process creates and maintains a set of internal proprietary tools that speed up software development. With platform engineering, organ...

 Picture this: You’re a chef, running a high-end restaurant. You’ve got a lot on your plate (pun intended). You need to create innovative, delicious dishes that satisfy your customers, while keeping costs in check and maintaining a consistent level of quality. Oh, and you’ve got a tight deadline: dinner service starts in an hour. How do you do it? You need a well-oiled machine: a kitchen that’s optimized for speed, quality, and efficiency. You need a platform that supports your needs, with tools and processes that enable your team to work together effectively. And you need to make sure your kitchen is secure and reliable, with fail-safes in place to prevent disasters. This is where Platform Engineering, DevSecOps, Site Reliability Engineering, and Automation come in. These concepts can supplement each other to increase time to value, enhance productivity, reduce risk, increase customer satisfaction, and increase profitability. Let’s break it down. Platform Engineering Platform ...

 Automation has been a game changer across industries, improving productivity & efficiency. However, the world of automation is on the brink of another major evolution with the integration of Artificial Intelligence (AI). The fusion of AI with automation has the potential to redefine the way we develop & deliver services, products & solutions AI in Automation: A Revolutionary Approach Traditionally, automation has been rule-based & required significant manual input. But with AI, we can introduce the concept of learning & adapting in automation. AI can analyse vast amounts of data, identify patterns & make decisions based on these patterns – a far cry from the static rule-based approach of traditional automation Intelligent Automation: A Marriage of AI & Automation This integration of AI with automation is often referred to as Intelligent Automation (IA). IA allows for more complex & sophisticated processes to be automated, decreasing human interv...

Artificial Intelligence (AI) is becoming increasingly popular, and the next wave of competitive advantage is expected to come from emerging technologies such as blockchain, the cloud, and AI. This has led to a rapid shift towards digital technologies, which has gone from years to months or even days. Consequently, there has been a significant increase in the number of intelligent automation and AI implementations. To integrate AI into an organization’s DNA, DevOps principles for AI are essential. DevOps principles enable AI at scale by operationalizing machine learning models from design to production. DevOps for AI ensures that the right AI delivery processes are in place, bringing flexibility and a “fail fast” approach needed during times of constant change and technological transformation. Essentially, DevOps for AI facilitates continuous delivery, deployment, and monitoring of models. DevOps for AI offers several benefits, including speeding up time-to-market by reducing non-valu...