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intro to artifical intelligence

Unit 1
Unit 1: basic programming
Introduction to PythonBasic Programming ConceptsData Structures and Algorithms
Unit 3 • Chapter 3

Deployment

Video Summary

Deployment is the process of releasing software or applications to a production environment where end-users can access and utilize them. It involves several key stages, starting with building the application, performing testing (unit, integration, system, and user acceptance testing), and packaging the application into a deployable format. The chosen deployment method depends on factors like application architecture (microservices, monolithic), infrastructure (cloud, on-premise), and scalability requirements. Common methods include blue/green deployments (minimizing downtime by switching between live and staging environments), canary deployments (gradually releasing to a subset of users), and rolling deployments (incremental updates). Successful deployment requires careful planning, version control, automated processes (CI/CD), and robust monitoring to ensure application stability and performance. Post-deployment monitoring is crucial for identifying and addressing issues swiftly. Effective deployment strategies are vital for ensuring a positive user experience and minimizing disruption to services.

Knowledge Check

Which deployment strategy involves releasing new code to a small subset of users before a full rollout?

What is a key benefit of using automated deployment processes?

What type of testing is performed to ensure the application functions correctly in the production environment?