CI/CD

CI/CD (Continuous Integration and Continuous Delivery/Deployment) is a software development methodology that automates the integration, testing, and deployment of code changes. It enables teams to deliver software updates more frequently and reliably by streamlining the pipeline from development to production. This approach reduces manual errors, improves code quality, and accelerates release cycles.

Also known as: Continuous Integration, Continuous Delivery, Continuous Deployment, CI, CD

🧊Why learn CI/CD?

Developers should learn and use CI/CD to automate repetitive tasks like building, testing, and deploying code, which is essential for modern agile and DevOps practices. It is particularly valuable in projects requiring frequent updates, such as web applications, microservices, or mobile apps, as it ensures faster feedback loops and reduces deployment risks. Adopting CI/CD helps teams maintain high-quality codebases and respond quickly to market demands.

See how it ranks →

Compare CI/CD

CI/CD vs Manual Deployment→CI/CD vs Waterfall Methodology→CI/CD vs Traditional Release Cycles→

Learning Resources

CI/CD Explained

CI/CD Tutorial for Beginners

Introduction to CI/CD on Coursera

Jenkins Handbook

Related Tools

Devops Jenkins Gitlab Ci Github Actions Docker

Alternatives to CI/CD

Manual Deployment Waterfall Methodology Traditional Release Cycles

Other CI/CD Tools

360 Degree Feedback

360 Degree Feedback is a performance evaluation methodology where an employee receives confidential, anonymous feedback from people who work around them, including peers, subordinates, supervisors, and sometimes external stakeholders like clients. It provides a comprehensive view of an individual's skills, behaviors, and performance from multiple perspectives, helping identify strengths and areas for development. This process is often used in organizational development, leadership training, and performance management to foster self-awareness and professional growth.

A/B testing is a statistical method used to compare two versions of a product, feature, or content to determine which performs better based on user behavior and metrics. It involves randomly splitting users into groups (A and B) and exposing them to different variants, then analyzing the results to make data-driven decisions. This technique is widely used in web development, marketing, and product optimization to improve user experience and achieve business goals.

A/B testing is a controlled experiment methodology used to compare two versions (A and B) of a variable, such as a webpage, app feature, or marketing campaign, to determine which performs better based on statistical analysis. It involves randomly splitting users into groups, exposing each to a different variant, and measuring outcomes like conversion rates or engagement. This approach helps make data-driven decisions to optimize user experience and business metrics.

ABC Analysis is an inventory categorization technique that classifies items into three categories (A, B, and C) based on their value or importance, typically using the Pareto principle where a small percentage of items account for a large portion of the total value. It helps organizations prioritize resources and management efforts by focusing on high-value items (A), moderate-value items (B), and low-value items (C). This method is widely used in supply chain management, inventory control, and business analysis to optimize efficiency and reduce costs.

Academic Learning

Academic Learning refers to the structured, theory-based approach to education and skill development, typically associated with formal institutions like universities and colleges. It emphasizes foundational knowledge, research, critical thinking, and theoretical understanding, often through courses, lectures, and academic assessments. This methodology is used to build a deep, systematic understanding of subjects, preparing individuals for advanced study or specialized professional roles.

Academic Programming

Academic Programming refers to the practice of writing code in an educational or research context, emphasizing clarity, correctness, and pedagogical value over production efficiency. It involves using programming to teach concepts, conduct experiments, or develop proofs, often in fields like computer science, mathematics, or engineering. This approach prioritizes learning outcomes, reproducibility, and theoretical understanding, typically with simpler tools and languages suited for instruction.