Leveraging ADF scalability: Performance tuning of an ADF pipeline

Due to its serverless architecture, ADF is inherently scalable, dynamically adjusting its resource allocation to meet workload demands without the need for users to manage physical servers. This flexible architecture offers users various techniques to enhance the performance of their data pipelines.

One approach for improving performance involves harnessing the power of parallelism, such as incorporating a ForEach activity into your pipelines. The ForEach activity allows for the parallel processing of data by iterating over a collection of items, executing a specified set of activities for each item in parallel. This can significantly reduce overall execution time, especially when dealing with large datasets or when multiple independent tasks can be processed concurrently.

For example, suppose you have a pipeline that needs to process data from multiple files stored in Azure Blob Storage. By using a ForEach...