Continuous Value Flow means every change – big or small – moves through an automated pipeline from merge to production in a consistent, observable, low-risk fashion. Embedding this outcome ensures teams deliver user value faster, recover from failures more quickly, and maintain a high bar on quality.
“All code changes are built, tested, packaged, deployed, and verified in production with zero-touch pipelines and safety controls, achieving a lead time for changes under 24 hours and a change failure rate below 5%.”
| Category | Description |
|---|---|
| People & Culture | Teams rely on manual releases with little confidence in automation. Changes are infrequent and high-risk. |
| Process & Governance | No defined release cadence or change process. Quality gates and rollback steps are missing. |
| Technology & Tools | Builds and deployments are triggered manually. CI/CD tooling may be ad hoc or missing. |
| Measurement & Metrics | No visibility into lead time, failure rate, or deployment frequency. Recovery is reactive. |
| Category | Description |
|---|---|
| People & Culture | CI is adopted for some services. Developers start integrating code more frequently. |
| Process & Governance | Release processes are repeatable but still manual. Environments are semi-standardised. |
| Technology & Tools | CI pipelines run on commit or merge. Deployment automation is limited or triggered manually. |
| Measurement & Metrics | Basic visibility into pipeline success/failure. Some awareness of time to deploy. |
| Category | Description |
|---|---|
| People & Culture | Teams use CI/CD pipelines confidently. Delivery is seen as a team responsibility. |
| Process & Governance | Releases follow a clear, automated path to production. Rollback procedures are known. |
| Technology & Tools | End-to-end CI/CD pipelines exist. Tests, builds, and deployments run automatically. |
| Measurement & Metrics | Lead time and change failure rate are monitored. Data is used for retros and planning. |
| Category | Description |
|---|---|
| People & Culture | Teams use metrics to drive improvement. Post-deployment telemetry informs future changes. |
| Process & Governance | Deployment cadence, rollback rates, and recovery time are tracked and governed. |
| Technology & Tools | Canary releases, automated rollbacks, and progressive deployment are applied. |
| Measurement & Metrics | All four DORA metrics (LTfC, CFR, DF, MTTR) are tracked. Trends are reviewed regularly. |
| Category | Description |
|---|---|
| People & Culture | Teams actively experiment with delivery approaches. Observability informs product decisions. |
| Process & Governance | Feedback loops across delivery stages are fast, closed, and used to adapt strategy. |
| Technology & Tools | Pipelines self-heal and optimise through anomaly detection, adaptive alerts, and auto-remediation. |
| Measurement & Metrics | Metrics drive platform and process evolution. Continuous improvement is embedded. |