This page is part of the ForgeSDLC knowledge base — an AI-assisted, human-directed methodology for taking product work from concept to production. For the core operating model and vocabulary, see Forge SDLC overview and What is ForgeSDLC?.

DevOps

What it is

DevOps is a culture, set of practices, and toolchain that unifies software development (Dev) and IT operations (Ops) to shorten the systems development lifecycle while delivering features, fixes, and updates frequently and reliably. It emphasizes automation, continuous integration and delivery (CI/CD), infrastructure as code (IaC), monitoring, and fast feedback loops between development and production.

DevOps is not a single framework with prescribed roles and events (like Scrum). It is a philosophy and capability that complements any delivery methodology — Scrum teams, Kanban teams, and phased projects all benefit from DevOps practices.

Process diagram (handbook)

DevOps infinity loop

The infinity loop: Plan → Code → Build → Test → Release → Deploy → Operate → Monitor → Plan. Continuous feedback from operations informs development.

Authoritative sources (external)

Resource	Executive summary (why it's linked here)
Wikipedia — DevOps	Stable overview of DevOps history, practices, and culture — entry point before vendor-specific guidance.
Wikipedia — CI/CD	Continuous integration and delivery — the technical backbone of DevOps pipelines.
The DORA team (Google Cloud)	Research-backed DevOps metrics and capabilities; the four key metrics (deployment frequency, lead time, change failure rate, MTTR).
The DevOps Handbook	Practitioner reference by Gene Kim et al. — principles, technical practices, and case studies (purchase/library).

Core practices (summary)

Practice	Purpose
Continuous Integration (CI)	Merge and test code frequently; keep trunk/main green.
Continuous Delivery (CD)	Automate the path from integration to production-ready artifacts.
Continuous Deployment	Automatically deploy every change that passes the pipeline (subset of teams).
Infrastructure as Code (IaC)	Manage infrastructure through version-controlled definitions (Terraform, Ansible, etc.).
Monitoring & observability	Instrument systems for health, performance, and business metrics; alert on anomalies.
Incident management	Detect, respond, resolve, and learn from production incidents systematically.
Automated testing	Unit, integration, contract, performance, security tests in the pipeline.
Configuration management	Version-controlled, reproducible environments; no snowflake servers.
Feature flags	Decouple deployment from release; control rollout granularity.

DORA four key metrics

Metric	What it measures
Deployment frequency	How often code is deployed to production.
Lead time for changes	Time from commit to production.
Change failure rate	Percentage of deployments causing failures.
Mean time to restore (MTTR)	Time to recover from a production failure.

Mapping to this blueprint's SDLC

DevOps idea	Blueprint touchpoint
CI/CD pipeline	Phase D–E: build, verify, release — `SDLC.md` §7, project `docs/development/CI-CD.md`.
IaC	Phase D–F: build, deploy, operate — version-controlled alongside application code.
Monitoring	Phase F: operate & learn — production signals feed next cycle.
Incident response	Phase F: operate — runbooks, escalation, post-incident reviews.
Automation	Cross-phase: reduce manual toil in build, test, deploy, and operate.

Ceremonies: DevOps adds operational ceremonies (incident reviews, deployment reviews, SLO reviews) to development-focused ones. See ceremonies/devops.md.

Roles: DevOps introduces or emphasizes SRE, platform engineer, release engineer — see roles-archetypes.md.

Agentic SDLC: DevOps + agents + tracking

Topic	Guidance
CI/CD	Agents can generate pipeline configurations, Dockerfiles, and IaC templates. Human review ensures security and correctness of deployment automation.
Monitoring	Agents can analyze logs and metrics, suggest alerts, and draft runbooks. Human sets SLOs and escalation policies.
Incident response	Agents can correlate alerts and suggest root causes. Human owns incident command and customer communication.
Feature flags	Agents can suggest flag configurations for gradual rollout. Human decides rollout strategy and risk tolerance.
DORA metrics	Agents can compute and visualize DORA metrics from pipeline data. Human interprets trends and drives improvements.

DevOps vs other methodologies

Comparison	Relationship
DevOps → Lean	DevOps applies Lean thinking to the full delivery pipeline: eliminate waste, optimize flow, build quality in. Value-stream mapping is a shared practice.
DevOps → Kanban	Kanban visualizes the flow that DevOps automates. DevOps pipelines are often modeled as Kanban stages.
DevOps → Scrum	Scrum defines what to build and when to review. DevOps defines how to build, deploy, and operate reliably. Complementary, not competing.
DevOps → Phased	DevOps practices (CI, automated testing) can be applied within phased gates to accelerate feedback without abandoning governance.

Prescriptive deep dive (teams)

Package devops/README.md — foundation fit, roles (SRE, platform engineer, release engineer), ceremonies (deployment review, incident review, SLO review, blameless post-mortem), pipeline flow maps.

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