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What belongs inside a software factory?
Set the boundary from inputs to operational feedback. The factory should govern how source code and dependencies enter the workflow, how builds run, how tests and security assessments are performed, where artifacts are stored, and how approved artifacts reach delivery systems. It should also capture enough metadata to help a later reviewer determine what was built and under which controls.
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Some capabilities sit outside the pipeline but are essential to its operation: identity and access management, source control, dependency repositories, and artifact storage and distribution. Downstream deployment systems can use retained provenance evidence and policy to decide whether an artifact is acceptable. The CNCF TAG Security’s Secure Software Factory guidance treats these controls as connected parts of the supply-chain workflow rather than isolated tools.
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That boundary matters: installing a CI/CD product does not, by itself, establish trusted inputs, secure pipeline permissions, traceable outputs, or an operating model for maintaining the service.
How should you map the delivery lifecycle?
Use lifecycle phases as a planning aid, then adapt them to the application and organization. One useful reference sequence is Design, Instantiate, Verify, and Operate & Monitor. It can be mapped to automated build, continuous integration (CI) verification, and continuous delivery (CD), but phase names, gates, and responsibilities need not be identical across teams.
| Reference phase | Factory concern | Typical workflow connection |
|---|---|---|
| Design | Define the intended system, its requirements, and the controls relevant to its risks. | Shapes the checks and delivery constraints that later automation must enforce. |
| Instantiate | Stage source, dependencies, and configuration in a controlled build process. | Automated build and artifact creation. |
| Verify | Test and assess the resulting software and its inputs. | CI checks, including tests and security analysis. |
| Operate & Monitor | Distribute or release accepted artifacts and use operational feedback to inform future changes. | CD, release, and ongoing operational feedback. |
NIST’s NCCoE DevSecOps notional reference model describes continuous build as automated staging of source, dependencies, and configuration, with artifacts and evidence passed to later automation. Its CI stage includes tests and assessments; examples of security analysis include static analysis, software composition analysis, secret scanning, infrastructure-as-code scanning, and container scanning. Its CD stage packages tested artifacts for release and distribution, with continued assessment.
NIST explicitly cautions: “This model is not intended to be a one-size-fits-all solution, but rather a guide for software development efforts.” The DoD’s Enterprise DevSecOps Reference Design: CNCF Kubernetes is a government-specific example, not a universal implementation template. Your application type, language, deployment target, regulatory obligations, threat model, and team skills should determine the actual workflow.
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Treat security and provenance as properties of the workflow. A secure factory needs controls over the pipeline itself as well as checks on the software it produces. The goal is to reduce risk and retain evidence—not to claim that any control set proves an artifact is safe.
- Control pipeline configuration. Keep workflow definitions as code in a controlled repository so changes can be reviewed and traced.
- Limit execution scope. Give tasks only the access they need, make each task narrowly scoped and well defined, and trigger it from explicit lifecycle events.
- Record what happened. Capture relevant inputs and execution metadata so teams can understand which source, dependencies, configuration, and workflow produced an artifact.
- Manage dependency intake deliberately. Where it improves control and traceability, keep dependency ingestion distinct from source ingestion.
- Reduce build variability where practical. Keep build steps minimal and make them hermetic where feasible. Seek reproducible builds when the toolchain supports them.
- Retain verification evidence. Preserve attestations, signatures, and metadata that downstream systems or reviewers can use to validate an artifact against policy.
- Apply assessments at the right stages. Integrate relevant tests and security analysis into CI, and continue assessment through packaging and distribution where appropriate.
These measures improve control and make later validation more useful, but they do not eliminate all supply-chain risk or establish that every dependency, build environment, or output is harmless.
How should you choose the factory architecture?
There is no universally correct toolchain in the cited guidance. NIST distinguishes its vendor-neutral reference model from vendor-specific implementations; the DoD design says tool choices depend on factors such as language, application type, lifecycle tasks, and deployment platform. Use those constraints, plus the platform’s users and operators, to compare architectural options.
| Decision | Option A | Option B | Questions to resolve |
|---|---|---|---|
| Starting point | Vendor-neutral reference model | Concrete implementation | Does the implementation fit your requirements and available skills, and can you explain where it differs from the model? |
| Operations | Managed service | Self-operated components | Which choice provides the necessary controls and reliability within your team’s operating capacity? |
| Workflow ownership | Central shared workflows | Team-specific extensions | Which controls should remain consistent, and where do application-specific needs justify extensions? |
| Deployment design | Greater cloud portability | Deployment-specific optimization | How much portability is needed, and what operational or integration trade-offs does it introduce? |
For each candidate design, assess compatibility with your language and application architecture, integration with existing source and deployment systems, security and audit controls, portability needs, developer usability, reliability, operator burden, and the cost of maintaining the capability. These are decision criteria, not a published benchmark or a claim that one category is always superior.
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If the factory is delivered as an internal platform, operate it as a product rather than treating it as a one-time infrastructure rollout. The platform may reduce duplicated work and cognitive load, enable reuse, and benefit from specialist operation. Those potential benefits depend on solving real user problems and sustaining the service; a central platform without adoption, clear value, feedback, or ongoing investment can become an underused dependency.
- Find a specific user problem. Learn where teams lose time or struggle to complete a recurring delivery task.
- Build a small useful capability. Provide a workable first solution rather than trying to standardize every team’s workflow at once.
- Gather feedback from actual users. Use their experience to identify friction, missing capabilities, and adoption barriers.
- Improve before broadening scope. Refine the service and its support model, then scale capabilities where user evidence justifies it.
The CNCF TAG App Delivery Platform Engineering Maturity Model describes movement from ad hoc or temporary capabilities toward dedicated ownership, self-service interfaces, product investment, and feedback-informed operation. It is intended to support guidance and introspection, not to impose a rigid maturity formula. Adapt the progression to your organization’s needs and capacity.
A March 24, 2026 report page for the CNCF and SlashData State of Cloud Native Development Q1 2026 says 88% of backend developers work in standardized DevOps and platform environments. That is a report finding about the surveyed context; it does not establish that standardization alone causes better performance or that every organization should adopt the same platform design.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do you measure whether the factory is working?
Set a baseline before introducing a platform change, state what outcome you expect, and reassess after teams have had a chance to use it. Combine measures of user experience and service delivery with measures of software delivery and reliability; a single speed metric can miss friction or instability elsewhere.
- User and service measures: satisfaction, adoption, active users and retention, time from a request to fulfillment, and time to a first code change.
- Delivery measures: deployment frequency, lead time for changes, time to restore service, and change failure rate. These are commonly used DORA delivery measures.
- Trade-offs: assess stability and throughput alongside changes to platform workflows so that standardization or faster fulfillment does not conceal reliability or delivery problems.
The CNCF TAG App Delivery CNCF Platforms White Paper suggests platform measures such as active users and retention, satisfaction, fulfillment latency, time to a first code change, and product delivery metrics. DORA’s Accelerate State of DevOps Report 2024 emphasizes user focus and iterative improvement and notes the importance of considering stability alongside throughput. Use metrics to test a specific hypothesis and guide adjustments, not as proof that a platform change caused an outcome without considering context.
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What should the first implementation include?
A sensible first scope is one representative application path, chosen because it exposes the controls and user needs you actually have—not because it is the most convenient demo. Map its source and dependency inputs, build environment, checks, artifact destination, delivery handoff, and required evidence. Then make the path repeatable, observe how teams use it, and expand only when the results and operating capacity support doing so.
- Document the lifecycle and the responsibilities of the teams that build, operate, and consume the factory.
- Define which inputs and outputs must be controlled or recorded for the application’s risks and audit needs.
- Choose a workflow that integrates with the existing source and deployment systems where that is appropriate.
- Confirm who owns the shared capabilities, user support, maintenance, and feedback loop.
- Establish user and delivery baselines before changing the workflow, then review the outcomes against an explicit hypothesis.
Tool recommendations and version details can become time-sensitive. The CNCF Secure Software Factory guidance directs implementers to consult current official tool documentation; do not treat a reference design or example toolchain as confirmation that a particular version is current or suitable for your environment.
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