End-to-end software delivery
Software Development Life Cycle An end-to-end view of how software moves from an identified opportunity through planning, design, implementation, release, operation, learning, maintenance, and retirement.
01 Discovery and Product Planning 02 Requirements Engineering 03 Software Architecture and System Design 04 Sprint Planning and Backlog Refinement 05 Software Development 06 Quality Assurance and Verification 07 Release Management 08 Operations and SRE 09 Product Analytics and Learning 10 Maintenance and Continuous Improvement 11 Retirement and Decommissioning 01
Lifecycle stage
Discovery and Product Planning Establish the customer problem, business context, expected outcomes, constraints, and investment rationale before committing to a solution.
Documentation artifacts BRD Roadmap Business case Opportunity assessment Product vision Working artifacts Problem statement Outcome hypotheses Prioritized opportunities Initial success metrics Typical owners Product management Business analysis Product leadership Stakeholders involved Customers and users Executive leadership Sales and marketing Finance Engineering leadership 02
Lifecycle stage
Requirements Engineering Discover, analyze, validate, document, and manage functional and non-functional requirements so delivery teams share a testable understanding of the intended system.
Working artifacts User stories and use cases Validated requirements baseline Assumptions and constraints Acceptance examples Typical owners Product management Business analysis Requirements engineering Stakeholders involved Customers and users Software engineering QA Security and compliance Operations 03
Lifecycle stage
Software Architecture and System Design Define the system structure, boundaries, interfaces, data flows, quality attributes, deployment topology, and major technical decisions.
Working artifacts Architecture baseline Interface contracts Data model Threat model Capacity assumptions Proofs of concept Typical owners Software architects Senior software engineers Solutions architects Data architects Stakeholders involved Product management Software development teams Security Infrastructure and platform engineering Data engineering Operations and SRE 04
Lifecycle stage
Sprint Planning and Backlog Refinement Break approved product and architecture intent into small, ordered, estimable, testable units of delivery with clear dependencies and acceptance conditions.
Working artifacts Product Backlog Estimates and dependency map Delivery plan Risk and spike items Typical owners Product owner Engineering team Engineering manager or delivery lead Stakeholders involved Product management QA Design Architecture Business stakeholders 05
Lifecycle stage
Software Development Implement, review, integrate, and document software while maintaining code quality, security, testability, and alignment with the approved design.
Working artifacts Source code Automated tests Build artifacts Database migrations Code-review decisions Typical owners Software developers Software engineers Stakeholders involved Product management QA Security Platform engineering Architecture 06
Working artifacts Automated and manual test results Defect backlog Coverage and quality evidence Release recommendation Typical owners QA engineers Software development teams Test automation engineers Stakeholders involved Product management Security Operations and SRE Business acceptance testers Customers or pilot users 07
Lifecycle stage
Release Management Prepare, approve, coordinate, deploy, and verify a software release while controlling operational, security, and business risk.
Working artifacts Versioned release package Deployment pipeline execution Migration scripts Go-live checklist Production verification evidence Typical owners Release management Software engineering Platform engineering Stakeholders involved Product management QA Security Operations and SRE Customer support Business owners 08
Lifecycle stage
Operations and SRE Operate the service safely in production by observing behavior, responding to incidents, managing capacity, and protecting reliability objectives.
Working artifacts Metrics, logs, and traces Alerts and dashboards Incident timeline Capacity and reliability forecasts Operational automation Typical owners SRE Operations Platform and infrastructure engineering Service-owning engineering team Stakeholders involved Product management Security operations Customer support Engineering leadership Customers 09
Lifecycle stage
Product Analytics and Learning Measure adoption, behavior, outcomes, reliability, and commercial performance so teams can validate assumptions and prioritize the next product decisions.
Documentation artifacts Measurement plan Experiment brief Analytics specification Product performance review Working artifacts Product dashboards Funnel and cohort analyses Experiment results Customer feedback themes KPI and business-metric trends Typical owners Product analytics Product management Data teams Stakeholders involved Software engineering Design and research Sales and marketing Customer success Executive leadership 10
Lifecycle stage
Maintenance and Continuous Improvement Sustain and improve the system through defect correction, dependency upgrades, security remediation, performance work, refactoring, and technical-debt management.
Documentation artifacts ADR Postmortem Maintenance backlog Technical-debt register Upgrade and migration plan Deprecation notice Working artifacts Patches and corrective releases Refactored components Updated dependencies Performance improvements Reliability improvements Typical owners Service-owning engineering team Maintenance engineering Platform and infrastructure engineering Stakeholders involved Product management Security Operations and SRE Customer support Architecture 11
Lifecycle stage
Retirement and Decommissioning Safely withdraw a product, service, interface, or platform while migrating users and data, satisfying retention obligations, and removing operational dependencies.
Documentation artifacts Retirement decision record Decommissioning plan Customer migration plan Data retention and deletion plan End-of-life notice Working artifacts Migrated users and workloads Archived or deleted data Removed infrastructure and credentials Closed operational dependencies Final compliance evidence Typical owners Product management Service-owning engineering team Operations and SRE Stakeholders involved Customers Customer support and success Security and compliance Legal and privacy Finance Dependent engineering teams The lifecycle is iterative, not strictly linear. Teams revisit requirements, design, implementation, testing, and operational decisions as evidence changes. The stages describe distinct responsibilities and artifacts, not a mandatory waterfall process.