When would you choose Progressive delivery over EKS?

In modern software development, the choice between Progressive Delivery and Kubernetes, such as EKS (Elastic Kubernetes Service), can depend on several factors including deployment strategy, team expertise, and project requirements. Progressive Delivery allows you to gradually roll out new features, providing the ability to test in production and minimize risk while EKS offers a robust container orchestration solution. Here are some scenarios where you might choose Progressive Delivery over EKS:

  • Risk Mitigation: When you want to deploy features in a controlled manner and monitor their impact.
  • Feature Toggles: If your application benefits from enabling/disabling features on-the-fly without a complete redeploy.
  • Stakeholder Feedback: For receiving feedback from a subset of users before a full rollout.
  • Resource Constraints: If your team lacks the expertise to manage Kubernetes effectively.
  • Simple Applications: For smaller applications that do not require the overhead of a full orchestration platform.

Example of Progressive Delivery Implementation

<?php // Example snippet for Progressive Delivery implementation $featureFlag = true; // Enable new feature for a subset of users if ($featureFlag) { // Code for the new feature } else { // Code for the old feature } ?>

Progressive Delivery EKS Kubernetes Deployment Strategy Feature Toggles

Related Questions

How do I avoid rehashing overhead with std::set in multithreaded code?

How do I find elements with custom comparators with std::set for embedded targets?

How do I erase elements while iterating with std::set for embedded targets?

How do I provide stable iteration order with std::unordered_map for large datasets?

How do I reserve capacity ahead of time with std::unordered_map for large datasets?

How do I erase elements while iterating with std::unordered_map in multithreaded code?

How do I provide stable iteration order with std::map for embedded targets?

How do I provide stable iteration order with std::map in multithreaded code?

How do I avoid rehashing overhead with std::map in performance-sensitive code?

How do I merge two containers efficiently with std::map for embedded targets?