Engineering Lifecycle
A Disciplined Six-Stage Engineering Lifecycle
Every Triple iTech engagement moves through the same six governed stages, from requirements gathering through long-term maintenance. Each stage closes with documented inputs, architectural deliverables, and a clear decision point, so operational boundaries are defined before code is written and production systems remain observable after launch.
Six Stages, One Accountable Path
Discovery defines the systems in scope and their constraints. Architecture Blueprint fixes service boundaries, data contracts, and deployment topology. Agile Sprints deliver those boundaries in tested increments. QA Hardening validates regression, security, and performance behaviour. Cloud Cutover moves production traffic under a rehearsed runbook with rollback criteria. Continuous Site Reliability then governs alerting, capacity, and incident response for the life of the system.
01 · Discovery
Stakeholder interviews, system inventories, and dependency mapping establish the operational boundaries. Inputs include current integrations, compliance obligations, and throughput targets. The deliverable is a scoped requirements baseline that names what is out of scope as clearly as what is in it.
02 · Architecture Blueprint
Service decomposition, API contracts, data ownership, and infrastructure topology are documented before implementation begins. Reviewers assess failure domains, authentication flows, and scaling assumptions. The deliverable is an approved architecture record that governs every later change.
03 · Agile Sprints
Work proceeds in fixed-length sprints with defined acceptance criteria, reviewed backlogs, and continuous integration on every merge. Microservices and Python or React components are built against the blueprint contracts. The deliverable is a working, versioned increment at the close of each sprint.
04 · QA Hardening
Automated regression suites, integration tests, load profiles, and security scans run against the release candidate. Defects are triaged against severity thresholds, and fixes are re-verified before promotion. The deliverable is a signed test report with known limitations documented.
05 · Cloud Cutover
Production traffic is moved through a rehearsed runbook with staged DNS, database migration checkpoints, and explicit rollback triggers. Kubernetes rollouts are gated by readiness probes and observed error budgets. The deliverable is a verified production state with a post-cutover review.
06 · Continuous Site Reliability
Service level objectives, alert policies, capacity forecasts, and incident post-mortems govern the system after launch. Monitoring covers latency, saturation, and error rates across each service. The deliverable is a sustained reliability record reviewed on a fixed cadence.
Governance Standards
Protecting Production Through Process
Sprint cadences set a predictable rhythm for scope, review, and release. Each sprint closes against written acceptance criteria rather than estimated progress, which keeps unfinished work from reaching the release branch. Scope changes are logged against the architecture record so that every deviation from the blueprint is visible to the engineering leads responsible for it.
Automated test suites are the primary control for regression. Unit, contract, integration, and end-to-end tests run on every merge, and a release is blocked when coverage of critical paths or security checks falls below the agreed threshold. Cutover runbooks document each step, owner, and rollback trigger in advance, so that a production change is an executed plan rather than an improvised response.