When compared to more conventional DevOps or deployment tools, Power BI deployment pipelines offer a native method of managing report and dataset promotion, but they also have some significant drawbacks.
Principal Drawbacks: Limited Automation and Flexibility
Compared to CI/CD tools like Jenkins or Azure DevOps, pipelines have fewer built-in automation features.
External scripting (PowerShell, REST API) is frequently needed for complex deployment logic.
Absence of Real Version Control
Pipelines do not natively support versioning and branching of reports and datasets.
Integration of source control (such as Git) needs to be handled independently.
Fundamental Workflows for Approval
There are no built-in approval or validation processes; Power Automate or other governance tools must be integrated.
In certain situations, limited granularity
Although selective deployments are feasible, granular control isn't as well supported by the UI and API as it is by more conventional DevOps tools.
Absence of a Rollback Button
Rollbacks cannot be undone with a single click; they must be manually re-deployed or restored from backups.
Manual Dependency Management
The user is responsible for managing order and bindings; pipelines do not automatically resolve complex dependencies across datasets and reports.
Mostly Concentrated on Power BI Artifacts
Unable to handle other application or infrastructure deployments; not made for multi-technology stacks.
Inadequate Audit Trails and Monitoring
There are activity logs, but they aren't as detailed or adaptable as those found in specialized DevOps platforms.
