Search Results for "devops"
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Showing 7 open source projects for "devops"
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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DevOps Basics
Practical and document place for DevOps toolchain
You are new to DevOps or want to learn some DevOps tools, or you are already a DevOps engineer, and you are looking for DevOps documents and a place to practice DevOps tools? This repository will assist you in enhancing your DevOps skills and serve as a bookmark for documents related to DevOps. -
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DevOps Roadmap 2026
DevOps Roadmap for 2026. with learning resources
DevOps Roadmap is a structured 2026 learning guide for people preparing for DevOps engineering roles. It presents the field as a sequence of practical competencies rather than a list of fashionable products. The path begins with Git, a programming language, Linux, scripting, networking, security, and server administration. It then advances through containers, Kubernetes, infrastructure as code, CI/CD, monitoring, observability, cloud platforms, and software engineering practices. ... -
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aws-devops-zero-to-hero
AWS zero to hero repo for devops engineers to learn AWS in 30 Days
aws-devops-zero-to-hero is a 30-day AWS learning roadmap aimed squarely at DevOps engineers who want both conceptual understanding and hands-on projects. The README is structured as a day-by-day syllabus, starting with “Day 1: Introduction to AWS” and moving through IAM, EC2, VPC networking, security, DNS (Route 53), storage (S3), and many other core services. -
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The Book of Secret Knowledge
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks
...The project is not a traditional application, but a navigable technical library meant to save time when looking for useful tools or operational knowledge. Its content spans areas such as Linux, networking, DevOps, security, databases, web infrastructure, shell usage, and productivity. The collection is useful for both quick lookup and broader exploration of technical topics. Its main value is centralizing many scattered resources into a single, community-maintained reference. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Mastering Zsh
Advanced topics to take advantage of zsh
...It explains topics such as completions, prompt customization, helper functions, and shell behavior in a structured way. The project is especially useful for developers, DevOps users, and terminal-heavy workflows. Its purpose is not to replace beginner tutorials, but to deepen everyday zsh knowledge with practical improvements. -
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How They DevOps
A curated collection of publicly available resources
How They DevOps is a collection of public writeups, posts, and references that show how well-known companies actually implement DevOps practices in the real world. Instead of describing DevOps in the abstract, it points to concrete CI/CD setups, infrastructure choices, incident processes, and tooling stacks used by tech organizations. This gives learners and teams a reality check: DevOps at scale is opinionated, messy, and adapted to business constraints. ... -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing.
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