Introduction
The pipeline that automates delivery for every other application in your landscape stops short the moment SAP changes need to move.
DevOps has become the standard for enterprise software delivery. Most organizations have already invested heavily, reorganizing teams and implementing tools like Azure DevOps (ADO) to manage their pipelines. The pipeline model works because every artifact is versioned, tested, and promoted through automated stages. SAP transports break this model.
Transports have unique properties. They carry code, data, or configurations, and they are not compiled. They have implicit dependencies dictating import sequencing. For these reasons and more, there is no easy way to manage transports using ADO pipelines natively.
But it is possible to bring transport management operations into ADO pipelines through integration. To do this, it is imperative that the integrity of the transport management process is maintained. This means adhering strictly to transport sequencing and dependency rules and ensuring compliance with all change policies and segregation of duties. By building these checks directly into ADO, SAP changes can finally achieve the same level of automation as the rest of the enterprise pipeline.
The pipeline that automates delivery for every other application in your landscape stops short the moment SAP changes need to move.
The Hidden Cost of a Two-Track Delivery Model
When SAP runs on a separate delivery track, every team that depends on it absorbs the delay.
Many organizations have already taken the first step by tracking SAP work items in Azure DevOps. Business analysts write user stories, developers update tasks through sprints, and testers prepare validation plans alongside non-SAP teams. On the surface, this creates alignment. SAP work appears in the same boards, the same sprint reviews, and the same velocity reports as everything else.
The break happens when changes need to move. For cloud-native applications, a completed work item means the code has been committed, the pipeline has built and tested it, and the artifact is ready for deployment. For SAP, a completed work item means the functional or technical work is done, but the transport still needs to be released, sequenced, checked for conflicts, and imported into the target environment. These steps happen outside Azure DevOps, often managed through SAP-native tools, spreadsheets, or informal coordination between basis administrators and development leads.
This creates a two-track delivery model. Non-SAP components flow through automated pipelines and arrive in QA within hours of sprint completion. SAP components follow a separate manual path and arrive days or sometimes weeks later. The result is predictable: integration testing cannot begin on schedule because the SAP components are missing. The impact extends beyond the SAP team. Every application that integrates with SAP, whether middleware, analytics, or front-end services, inherits the delay.
When SAP runs on a separate delivery track, every team that depends on it absorbs the delay.
What an Integrated SAP DevOps Model Looks Like in Azure DevOps
SAP delivery accelerates when transport operations become pipeline activities rather than offline tasks.
Closing the gap begins with linking transports directly to ADO work items. This can be achieved using CoreALM’s SAP Transport Management for Azure DevOps. With this integration in place, developers can create SAP transports directly from ADO, attaching them to their user stories or tasks. This linkage means that the status of every work item reflects the true state of the SAP change, including whether the transport has been released, whether it has passed validation checks, and whether it has been successfully imported into the target environment.
When it’s time to deploy the changes, dependency checks automatically validate the transports being imported to ensure there are no missing objects. Once validation is complete, the changes are automatically deployed in the right sequence. This automation saves considerable manual effort, but it’s only the beginning of what is possible. Additional opportunities to automate include:
- Code quality and vulnerability checks
- Change impact analysis and risk assessment reporting
- Automated validation of related regression test scenarios
The more that is automated, the more context is available for change and release managers who can shift from judgment-based decisions to data-driven confirmations. The approver’s role becomes confirming that the risks have been appropriately mitigated based on the evidence, rather than relying on their experience to flag potential issues. This maintains governance and process compliance while ensuring that evidence is captured consistently for every change, leaving behind a complete audit trail visible from within a single system.
SAP delivery accelerates when transport operations become pipeline activities rather than offline tasks.
Conclusion: SAP Belongs in the Pipeline, Not Beside It
The organizations that move fastest are the ones that stopped treating SAP as an exception to their DevOps model.
The two-track delivery model has persisted because SAP transports are genuinely different from code deployments, and most DevOps platforms were never designed to handle them. But by automating the integrity checks required for SAP transports within the same workflow, leaders can close this gap and accelerate the release schedule. As SAP landscapes become more modular and more deeply integrated with cloud services and enterprise platforms, releases can finally be coordinated across the enterprise, bringing SAP changes into the enterprise release pipeline. All of this efficiency is wrapped in a governance model that is strong, consistent, and fully auditable.
For leaders ready to bring SAP into the DevOps pipeline, three actions matter now:
- Attach every SAP transport to your ADO work items. In the same way that developers link pull requests to user stories, link SAP transports to your work items so the work item status reflects the actual readiness of the change in SAP and so transports can participate in pipeline automations.
- Automate transport validation inside the pipeline. Sequencing checks, dependency analysis, and conflict detection should run as automated pipeline stages rather than manual pre-cutover activities. This shifts governance from reactive to preventive and eliminates the most common source of deployment failures.
- Coordinate SAP and non-SAP releases as a single enterprise outcome. SAP changes should advance through the same governed pipeline as every other application. When all components arrive in QA together and deploy to production together, integration testing starts on time and cutovers execute as planned.
Bringing SAP transports into the pipeline solves the execution challenge. But a pipeline that moves transports without understanding the business processes behind them is automating logistics, not delivery. In next week’s edition, we explore how integrating SAP Cloud ALM with Azure DevOps adds the process intelligence that transforms a transport pipeline into a true CI/CD pipeline for SAP.
