The Software Development Lifecycle (SDLC) Explained

The software development lifecycle (SDLC) is the sequence of phases a piece of software goes through, from the first idea to retirement: planning, requirements, design, build, testing, deployment and maintenance. Every team follows some version of it, whether they write it down or not.

The useful question is not "do we have an SDLC?" but "where does work fall through the cracks between phases?"

The seven SDLC phases

1. Planning – decide what to build and why, roughly how big it is, and who is involved.
2. Requirements – turn the idea into specific, testable needs. User stories and acceptance criteria live here.
3. Design – architecture, data model, interface. Diagrams are worth more than paragraphs at this stage.
4. Build – write the code, review it, merge it.
5. Testing – verify it does what the requirements said, and that nothing else broke.
6. Deployment – move it through your environments to production. See deployment environments for how dev, QA, staging and production fit together.
7. Maintenance – fix bugs, apply hotfixes, make small improvements, and eventually plan the next version.

SDLC models compared

The phases stay the same; the models differ in how you move through them.

• Waterfall runs each phase once, in order. Predictable on paper, painful when requirements change late.
• Iterative and incremental models repeat the cycle in smaller loops, each one delivering a usable slice.
• Agile (Scrum, Kanban and their hybrids) shrinks the loop to a sprint or a single ticket. Every phase happens continuously.
• V-model pairs each build phase with a matching test phase, which suits regulated environments that need evidence.

Most modern teams run agile day to day with a few waterfall-style gates where they matter, such as client scope approval before build and sign-off before release.

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Where the lifecycle usually breaks

The phases themselves are rarely the problem. The handovers are:

• Requirements written in one tool, designs drawn in another, code in a third. Nobody can see which diagram led to which ticket.
• Testing recorded in a spreadsheet, so there is no history of what failed and why.
• Releases planned in someone's head, so a missed step only surfaces in production.

Every handover that relies on someone copying information across is a place where the lifecycle leaks.

How Flow helps

Jira and Azure DevOps both cover large parts of the SDLC well. Jira is strong for issue tracking and has a vast marketplace for filling gaps, while Azure DevOps bundles boards, repos, pipelines and test plans for teams in the Microsoft ecosystem. Flow takes a different angle: keep every phase in one delivery platform, with the client in the loop. In Livex Flow you get:

• Diagram boards that turn into tickets, so a design sketch becomes stories and sub-tasks without retyping, plus a database designer that exports SQL.
• A testing hub with test runs, pass/fail per ticket and failure history, so the testing phase leaves evidence.
• A release planner per environment with checklist steps that persist until the release is complete.
• Integrations with Azure DevOps and GitHub for repo and commit linking, so build activity shows up on the ticket.

For the testing phase in more depth, read software testing basics.