The 8 Ops

  What is Linux and How Can It Help in DevOps? If you’ve ever wondered, what is Linux and why it’s essential in the world of DevOps , you’ve come to the right place. Linux is more than just an operating system; it’s a powerful tool that plays a central role in DevOps automation and infrastructure management. Understanding Linux’s capabilities and how it fits into DevOps workflows is key to improving software development processes. In simple terms, Linux is an open-source operating system (OS) that allows developers and IT professionals to interact with and manage the underlying hardware of a computer. Unlike other operating systems, Linux is customisable, secure, and free—making it a favorite in the DevOps community. Linux for Devops Why is Linux So Popular in DevOps? Linux is at the core of many DevOps practices because of its stability, flexibility, and integration with essential DevOps tools. Here’s how Linux for DevOps works and why it’s indispensable: Automation : Linux po...

DevOps Cycle: A Simple Guide In the world of software development, the DevOps cycle is one of the most crucial processes for ensuring that applications are built, tested, deployed, and maintained efficiently. It combines Development (Dev) and Operations (Ops) into a unified process that bridges the gap between developers who create the software and operations teams who maintain and run it. DevOps Cycle: A simple guide In this blog, we'll break down the DevOps cycle step by step, using simple examples, so anyone—whether you’re a developer or just curious about how technology works—can understand its significance. What is the DevOps Cycle? The DevOps cycle refers to the continuous process of software development, deployment, and maintenance, with the goal of achieving faster delivery, improved collaboration, and higher-quality software. It consists of multiple stages, each designed to improve and automate a different aspect of the software lifecycle. Here's an overview of the key...

What is DevOps? DevOps is a culture, set of practices, and tools that combine software development (Dev) and IT operations (Ops). It aims to shorten the development lifecycle and provide continuous delivery with high software quality. In simple terms, DevOps bridges the gap between Developers (who write code) and Operations (who deploy and manage that code in production). DevOps: The Basics Imagine you’re at a car assembly line, where designers plan and engineers build. DevOps is like a streamlined process that allows designers and engineers to work together closely, ensuring that every car model rolls off the line faster, with fewer errors, and with higher quality. Why Do We Need DevOps? Before DevOps, developers and operations teams often worked in silos i.e. isolation or separation. Developers would create code, throw it over the wall, and operations would handle deployment and management. This traditional model led to: Slow releases: Development took time, testing took time, and d...

Exciting Changes Ahead: Welcome to The 8 Ops! Dear Readers, I have some exciting news to share! After careful consideration and reflection, I’ve decided to transition my blog from " Data Science Learnings " to " The 8 Ops ". This change marks a new chapter in our journey together, focusing on the dynamic fields of Cloud Computing and DevOps—the future of technology. Why the Change? As we continue to witness rapid advancements in technology, it’s clear that cloud computing and DevOps are not just trends but essential components of modern IT practices. With powerful tools like AWS, Azure, Kubernetes, Docker, Jenkins, Git, Ansible and many more , the possibilities are endless. I believe that these technologies will shape the future of how we build, deploy, and manage applications. By shifting the focus of this blog, I aim to provide you with insights and knowledge in these areas—from foundational concepts to practical applications. Whether you’re a beginner or looking ...

Introduction Descriptive statistics is one of the ways to describe the data. In data science, descriptive statistics are used to provide an overview of a huge data collection. It's used to see if the data is normally distributed or not. It is presented in the form of a chart, graphs, table, frequency distribution, and so on. It provides information on summary statistics that includes Mean, Standard Error, Median, Mode, Standard Deviation, Variance, Kurtosis, Skewness, Range, Minimum, Maximum, Sum, and Count. Two major information is provided by Descriptive Statistics regarding the data: The measure of Central Tendency The measure of Dispersion Descriptive Statistics Descriptive statistics answer the following questions: What is the value that best describes the data set? How much does a data set speads from its average value? What is the smallest and largest number in a data set? What are the outliers and how it affects the dataset? Measure of Central Tendency It describes a w...

What is Hypothesis Testing? Statistics is all about data. That huge amount of data will only be useful if we are going to analyze it or take out conclusions from it. To find out such important interpretations or conclusions we use hypothesis testing. Statistics Statistical Hypothesis testing is to test the assumption (hypothesis) made and draw a conclusion about the population. This is done by testing the sample representing the whole population and based on the results obtained; the hypothesis is either rejected or accepted. Pre-requisites: DSL | E1 Statistics Steps in Hypothesis Testing The three major steps are: Making an initial assumption. We will take the initial assumption as the null hypothesis, H0. Example: We want to know whether the defendant is guilty or innocent. Thus, we take H0 as Defendant not guilty. Collecting the data. This data will not only be the data but the shreds of evidence as well. Example: Fingerprints, DNA, etc. Gathering evidence to reject/accept the hypot...