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ADF Pipeline Best Practices for Production
A pipeline that works in debug is not yet a production pipeline. This guide collects the practices that close the gap in Azure Data Factory: small pipelines within documented limits, reruns that cannot corrupt data, credentials out of the factory, deployment by release pipeline, cost control and monitoring.
Azure Databricks with ADF: Orchestration Patterns
Azure Data Factory can run Databricks notebooks, Python files, Jar files and jobs as pipeline steps. This guide covers the linked service and its cluster options, passing parameters in and reading results back, how the cluster choice changes run time and cost, and the orchestration patterns that hold up in production.
ADF vs SSIS: Migrating Legacy ETL to the Cloud
Moving SQL Server to Azure leaves a question behind: what happens to the SSIS packages? This guide compares SSIS with Azure Data Factory, explains the two migration routes, running packages unchanged on the Azure-SSIS integration runtime or rebuilding them as pipelines, and gives a way to decide package by package.
ADF Global Parameters and Variables Explained
Azure Data Factory has three ways to hold a value: pipeline parameters, variables and global parameters. This guide compares their scope and whether they can change, shows Set Variable and Append Variable in JSON, explains why a variable cannot reference itself and why variables misbehave in parallel loops.
Data Partitioning Strategies in ADF Copy Activity
A large table copied through one query is limited by one connection. This guide explains the partition options of the Azure Data Factory Copy activity, how dynamic range bounds really work, how to choose a partition column, with skew measured on 2.9 million real rows, and how partitioning applies to files.
ADF Performance Tuning: DIUs and Parallelism
Raising DIUs is the reflex when a Copy activity is slow, and it is often the wrong move. This guide explains what Data Integration Units and parallel copies control, their documented defaults and limits, how billing responds, when staged copy helps, and how to read the monitoring view to find the real bottleneck.