This open source code project delivers a simple metadata driven processing framework for Azure Data Factory (ADF). The framework is made possible by coupling ADF with an Azure SQL Database that houses execution stage and pipeline information that is later called using an Azure Functions App. The parent/child metadata structure firstly allows stages of dependencies to be executed in sequence. Then secondly, all pipelines within a stage to be executed in parallel offering scaled out control flows where no inter-dependencies exist.
The framework is designed to integrate with any existing Data Factory solution by making the lowest level executor a stand alone Worker pipeline that is wrapped in a higher level of controlled (sequential) dependencies. This level of abstraction means operationally nothing about the monitoring of orchestration processes is hidden in multiple levels of dynamic activity calls. Instead, everything from the processing pipeline doing the work (the Worker) can be inspected using out-of-the-box ADF features.
This framework can also be used in any Azure Tenant and allow the creation of complex control flows across multiple Data Factory resources by connecting Service Principal details through metadata to targeted Subscriptions > Resource Groups > Data Factory's and Pipelines, this offers very granular administration over data processing components in a given environment.
- Granular metadata control.
- Metadata integrity checking.
- Global properties.
- Dependency handling.
- Execution restart-ability.
- Parallel execution.
- Full execution and error logs.
- Operational dashboards.
- Low cost orchestration.
- Disconnection between framework and Worker pipelines.
- Cross Data Factory control flows.
- Pipeline parameter support.
- Simple troubleshooting.
- Easy deployment.
- Email alerting.
Who | Details |
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Paul Andrew | @mrpaulandrew paul@mrpaulandrew.com https://mrpaulandrew.tech |
If you've found a bug or have a new feature request please log the details using the repository issues.
Go to... Issues
Go to... External Requests
Go to... Internal Backlog
Go to... Glossary
Blogs | mrpaulandrew.com/ADF.procfwk | |
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GitHub | github.com/mrpaulandrew/ADF.procfwk | |
#ADFprocfwk | ||
Vlogs | youtube.com/mrpaulandrew |
Version | Overview | Related Blog(s) & Release Notes |
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1.7.1 | Alerting Check Bug Fix added, plus:
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ADF.procfwk v1.7.1 - Alerting Bug Fix And Pipeline Parameter Size Limit Removed |
1.7 | Pipleline EMail Alerting added, plus:
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ADF.procfwk v1.7 - Pipeline Email Alerting |
1.6 | Error Details for Failed Activities Captured, plus:
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ADF.procfwk v1.6 - Error Details for Failed Activities Captured |
1.5 | Power BI Dashboard for Framework Executions, plus:
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ADF.procfwk v1.5 - Power BI Dashboard for Framework Executions |
1.4 | Enhancements for Long Running Pipelines, plus:
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ADF.procfwk v1.4 - Enhancements for Long Running Pipelines |
1.3 | Metadata Integrity Checks, plus:
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ADF.procfwk v1.3 - Metadata Integrity Checks |
1.2 | Execution Restartability, plus:
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ADF.procfwk v1.2 - Execution Restartability |
1.1 | Service Principal Handling via Metadata, plus:
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ADF.procfwk v1.1 - Service Principal Handling via Metadata |
1.0 | Simple framework designed and base compontents built.
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Blog Series: Creating a Simple Staged Metadata Driven Processing Framework for Azure Data Factory Pipelines |