A FREE pragmatic DevOps learning to kickstart your DevOps career and knowledge in the Cloud Native era following the Agile MVP style! ⭐ (2026 plans for DevOps, Cloud, Platform, SRE, SWE)

This is my DevOps learning plan for the year 2024

DevOps Roadmap

A Devops pipeline is set of automated processes and tools that the development (Dev) and operations (Ops) teams implement to build, test, and deploy software faster and easier. In this course you will complete DevOps pipeline generally consists of a set of tools which are normally broken down into the following categories: Plan Code Integrate Test Release Deploy Operate This learning path will cover: Git is an open-source and distributed version control system. Github is git repository hosting service used for code sharing, bug tracking, feature request and much more. PyCharm is an integrated development environment (IDE) for python programing language. Flask is a python web framework. HTML is the standard markup language for Web pages. CSS is a style sheet language use to style a HTML document. SQLAlchemy is an open-source SQL toolkit and object-relational mapper which gives full power and flexibility of SQL. Selenium is used to automate web browser interaction. Pytest is unit testing framework that allows users to write test codes. Ngrok allows to expose a web server running on your local machine to the internet. Github Action enables you to include Continues Integration (CI) and continuous deployment (CD) capabilities and many other features directly in your repository. Docker is an open source containerization platform enables developers to package applications into containers. Docker Hub is a cloud-based repository for finding and sharing container images with your team. Kubernetes is an open-source container orchestration for automating deployment, scaling, and management of containerized applications. This course is one stop shop where you will learn web development, continuous integration, continuous deployment, containerization, writing neat and quality code, devops concepts and much more with python programing language. What you’ll learn Learn to build Continuous Integration Continuous Deployment pipeline Build CI CD tool to update docker image after any update Learn to create dockerfile Learn the fundamental concepts of Docker Learn the fundamental concepts of Kubernetes Learn to create Kubernetes YAML files Learn to deploy high availability, fault tolerance, scalable application Learn all the basic and advanced git commands Learn different types of branches like master, developer, feature, release and hotfix branch Learn fundamental concepts of Version Control System Learn to use Github actions for CI CD pipeline Learn to build python flask web application Learn to use SQL Alchemy Lean to create HTML pages using HTML, CSS and bootstrap Are there any course requirements or prerequisites? Git installed Docker installed Kubernetes installed Any IDE Github account Docker hub account Who this course is for: Anyone who wants to Enhance their skills in DevOps domain Developers and IT Pros Instructor User photo Pranjal Srivastava Docker | Kubernetes | AWS | Azure | ML | Linux | Python I am an Instructor, Devops engineer, machine learning enthusiast, cloud expert and passionate developer. I have authored 60+ courses with over 50,000+ students worldwide across 175+ countries on wide array of technologies like containerization, machine learning, Linux, programming languages and cloud computing platforms like Microsoft Azure, Amazon Web Service and IBM Cloud.

No description available

DevOps Learning Plan 2024

Python is point of fact the Next Big Thing to investigate. There is no need to be worried about its worth, profession possibilities, or accessible positions. Python's commitment to the advancement of your calling is huge, as its notoriety among designers and different areas is step by step waning. Python is "the one" for an assortment of reasons. It's a straightforward pre-arranged language that is not difficult to get. Subsequently, the general improvement time for the task code is diminished. It accompanies an assortment of structures and APIs that assistance with information examination, perception, and control. Employment opportunities in Python While India has a critical interest for Python engineers, the stock is very restricted. We'll utilize a HR master articulation to validate this. For both Java and Python, the expert was relied upon to employ ten developers. For Java, they got over 100 fantastic resumes, however just eight for Python. In this way, while they needed to go through an extensive method to get rid of resilient people, they had no real option except to acknowledge those eight individuals with Python. What does this say about the circumstance to you? Regardless of Python's straightforward language structure, we desperately need more individuals in India to update their abilities. This is the reason learning Python is a particularly colossal opportunity for Indians. With regards to work openings, there may not be numerous for Python in India. Notwithstanding, we have countless assignments accessible per Python developer. In the relatively recent past, one of India's unicorn programming organizations was stood up to with an issue. It had gotten a $200 million (Rs. 1200 crore) arrangement to develop an application store for a significant US bank. Be that as it may, the organization required talented Python developers. Since Python was the best language for the undertaking, it wound up paying a gathering of independent Python developers in the United States multiple times the charging sum. For sure and Naukri, for instance, have 20,000 to 50,000 Python work postings, showing that Python vocation openings in India are copious. It is an insightful choice to seek after a profession in Python. The diagrams underneath show the absolute number of occupation advertisements for the most well known programming dialects. Python Job Descriptions Anyway, what sorts of work would you be able to get in the event that you know Python? Python's degree is broad in information science and investigation, first off. Customers regularly demand that secret examples be separated from their informational indexes. In AI and man-made reasoning, it is additionally suggested. Python is a top choice among information researchers. Furthermore, we figured out how Python is used in web advancement, work area applications, information examination, and organization programming in our article on Python applications. Python Job Profiles With Python on your resume, you might wind up with one of the accompanying situations in a presumed organization: 1. Programmer Investigate client necessities Compose and test code Compose functional documentation Counsel customers and work intimately with other staff Foster existing projects 2. Senior Software Engineer Foster excellent programming engineering Mechanize assignments by means of prearranging and different apparatuses Survey and troubleshoot code Perform approval and confirmation testing Carry out form control and configuration designs 3. DevOps Engineer Send refreshes and fixes Break down and resolve specialized issues Plan systems for support and investigating Foster contents to mechanize representation Convey Level 2 specialized help 4. Information Scientist Recognize information sources and mechanize the assortment Preprocess information and dissect it to find patterns Plan prescient models and ML calculations Perform information representation Propose answers for business challenges 5. Senior Data Scientist Manage junior information experts Construct logical devices to create knowledge, find designs, and foresee conduct Execute ML and measurements based calculations Propose thoughts for utilizing had information Impart discoveries to colleagues While many significant firms are as yet utilizing Java, Python is a more seasoned yet at the same time well known innovation. Python's future is splendid, on account of: 1.Artificial Intelligence (AI): Machine knowledge is alluded to as man-made consciousness. This is as a conspicuous difference to the regular astuteness that people and different creatures have. It is one of the most up to date advances that is clearing the globe. With regards to AI, Python is one of the main dialects that rings a bell; truth be told, it is probably the most ideally equipped language for the work. We have different structures, libraries, and devices devoted to permitting AI to swap human work for this objective. It supports this, however it additionally further develops productivity and precision. Discourse acknowledgment frameworks, self-driving vehicles, and other AI-based advancements are models. The accompanying devices and libraries transport for these parts of AI: AI – PyML, PyBrain, scikit-learn, MDP Toolkit, GraphLab Create, MIPy General AI – pyDatalog, AIMA, EasyAI, SimpleAI Neural Networks – PyAnn, pyrenn, ffnet, neurolab Normal Language and Text Processing – Quepy, NLTK, genism 2. Enormous Data Enormous Data is the term for informational collections so voluminous and complex that conventional information handling application programming is insufficient in managing them. Python has assisted Big Data with developing, its libraries permit us to break down and work with a lot of information across groups: Pandas scikit-learn NumPy SciPy GraphLab Create IPython Bokeh Agate PySpark Dask 3. Systems administration Python additionally allows us to design switches and switches, and perform other organization mechanization undertakings cost-viably. For this, we have the accompanying Python libraries: Ansible Netmiko NAPALM(Network Automation and Programmability Abstraction Layer with Multivendor Support) Pyeapi JunosPyEZ PySNM Paramiko SSH Python Course

DevOps Learning Plan

This Repository Consists Of My Journey Guide To Become A DevOps Engine. My DevOps Learning Plan,

This repository is my documenting repository for learning various areas that make up DevOps. I plan to spend an hour or two per day including weekends to get a foundational knowledge of DevOps.

This repository is my documenting repository for learning DevOps. I started this journey on the 16th October 2022 and I plan to run to December 16th for a complete 90-day romp on spending an hour a day including weekends to get a foundational knowledge across a lot of different areas that make up DevOps

This repository is a step-by-step daily plan to get a BETTER understanding of everything DevOps from Linux fundamentals to Kubernetes, all the way to Reliability & SRE. I am doing this just to refresh up on certain topics, going at my own pace following my own learning path.

Plan for learning DevOps .............

Complete DevOps Learning Plan — 30 Lessons covering K8s, CI/CD, IaC, Monitoring, Security, AWS, SRE & CKA Prep

Web page for Learning plan for Devops

No description available

Learning plan from ReactiveOps for their aprenticeship roles

No description available

No description available

No description available

Hands-on DevOps automation plan covering Shell scripting, Python, and real-time automation practices with curated resources and daily tasks.

In this repo I plan to document my DevOps learning Journey.

All my learning cloud, devops projects. Planning to work on Docker and Kubernetes

This repository contains the lab for agile planning from Devops and Software Engineering learning path on Coursera.

Here’s a structured 10-day Azure DevOps learning plan to prepare you for the AZ-400: Designing and Implementing Microsoft DevOps Solutions certification

My Linux learning plan focused on Cloud Engineering and DevOps concepts — practical commands, mental models, and hands-on practice.

This a DevOps learning mail where everything about DevOps will be found in a sequential manner, useful for freshers, experienced and even non-IT guys planning to switch to IT via DevOps.

image.png PNG 31.34KB I'll create a complete DevOps learning website with HTML, CSS, and JavaScript. This will include DevOps explanations, a 2-month learning plan, and a LinkedIn job results section.

A simple bash script to back up a directory into a timestamped .tar.gz archive. (Day 3 of DevOps Learning Plan)

100-day Python learning plan tailored for a DevOps Engineer, from beginner to advanced, with practical examples and industry-standard practices: