3) Canary Deployment:

    Gradually rolling out a new version of the application to a small subset of users or servers before deploying it to the entire infrastructure.

Example: Releasing a new mobile app version to 5% of users initially to monitor for any unexpected issues before a full release.

4) Rolling Deployment:

  Gradually replacing instances of the old version with the new one, minimizing downtime and risk.

Example: Updating a cluster of servers one at a time, ensuring that the application remains available throughout the deployment process. 

5) Feature Toggles (Feature Flags): 

   Controlling the release of new features by toggling them on or off without redeploying the application.

Example: Introducing a new UI component but activating it only for internal users initially to gather feedback before exposing it to all users. These strategies help in achieving a balance between deploying new features quickly and maintaining the stability and reliability of the application. The choice depends on the specific requirements, risks, and constraints of the project.

6) A/B Testing:

   A method of comparing two versions (A and B) of a webpage, application, or feature to determine which performs better.

Example: Consider an e-commerce website testing two variations of a checkout button. Version A is the existing button design, while Version B is a new design. By randomly assigning users to either A or B, the company can analyze user interactions and conversion rates to decide which version is more effective in increasing purchases.

7) Shadow Deployment:

 Introducing a new version of an application or service alongside the existing production version, allowing it to run concurrently without affecting live users.

Example: Suppose a company wants to deploy a new messaging feature in a chat application. With shadow deployment, the new messaging system is deployed in parallel with the existing one, but the messages from the new system are only logged for analysis rather than being visible to users. This allows the team to monitor performance, identify issues, and ensure a smooth transition before making it live for all users.