SDLC – Comparison Scenarios – Part 4

A Product Manager focuses on the 'what' and 'why' of a product, defining its vision, strategy, and features to meet customer needs. A Project Manager focuses on the 'how' and 'when', coordinating resources, timelines, and budgets to execute the plan. Example: The Product Manager decides the app needs a chat feature to improve retention. The Project Manager creates the schedule and assigns tasks to ensure the chat feature is built on time and within budget.

A Product Owner represents the business and customers, maximizing product value by managing and prioritizing the product backlog. A Scrum Master is a facilitator who guides the team in Scrum practices, removes obstacles, and ensures smooth delivery. Example: The Product Owner decides which features are most valuable to build next. The Scrum Master helps the team run efficient meetings and resolves an issue where developers are blocked by missing server credentials.

An Epic is a large body of work that cannot be completed in a single development cycle and must be broken down into smaller tasks. A User Story is a small, specific requirement written from an end-user's perspective that can be completed in a few days. Example: 'Build a customer billing portal' is an Epic. 'As a customer, I want to download my invoice as a PDF' is a User Story nested within that Epic.

A Sprint is a specific type of iteration used strictly in the Scrum framework, always lasting a fixed duration (usually 1 to 4 weeks). An Iteration is a general, framework-agnostic term for any repeatable development cycle in Agile. Example: A team practicing Scrum refers to their 2-week cycle as a Sprint. A team practicing generic Agile or Extreme Programming (XP) simply refers to their development cycles as Iterations.

The Product Backlog is an evolving, prioritized list of all features, requirements, and fixes needed for the entire product. The Sprint Backlog is a subset of those items chosen by the team to be completed during the current Sprint. Example: The Product Backlog contains 150 items for the year. During planning, the team pulls 5 high-priority items from that list to form the Sprint Backlog for the next two weeks.

Continuous Integration (CI) is the practice of frequently merging code changes into a central repository, where automated builds and tests are run. Continuous Delivery (CD) is the next step, automatically packaging and preparing that tested code for release to a production environment. Example: In CI, a developer pushes code, triggering automatic unit tests. In CD, once the tests pass, the system automatically builds a deployment-ready package and pushes it to a staging server.

Continuous Delivery prepares code for release automatically, but requires a manual human decision to push it live to customers. Continuous Deployment automates the entire pipeline, instantly pushing every passed code change directly to the live production environment. Example: In Continuous Delivery, the release candidate is ready, and a manager clicks a button to go live. In Continuous Deployment, the code goes live to customers the moment it passes the automated test pipeline, without human intervention.

Deployment is a technical action where software is installed and run in an environment (like production). Release is a business decision to make those deployed features visible and available to users. Example: Developers deploy a new checkout design to the production servers on Tuesday, but keep it hidden behind a feature flag. On Thursday, the marketing team releases the feature by turning the flag on, making it visible to customers.

A Proof of Concept (POC) is a small exercise designed to test the technical feasibility of a single idea. A Prototype is a working model of the product built to test its design, usability, and flow with real users. Example: Building a quick script to see if an AI API can actually read a specific PDF layout is a POC. Building a clickable interface showing how a user will navigate, upload, and view those PDFs is a Prototype.

Corrective maintenance fixes active bugs or failures in the system. Adaptive maintenance updates the system to work in a changing environment (like a new OS). Perfective maintenance adds new features or improves performance based on user requests. Preventive maintenance solves latent issues to stop future failures before they happen. Example: Fixing a crash is Corrective. Updating the app for iOS 20 is Adaptive. Speeding up page load times is Perfective. Cleaning up messy code to prevent future bugs is Preventive.