Deploying SSIS Projects to Different Environments

In this post I’m explaining how you can deploy a developed SSIS project to several different environments. It might have happened to you that there are several environments that you need to deploy the SSIS projects to. Assume that you have DEV, QA, UAT and PROD environments. Some organisations might have even more environments. Also, there are many cases that you might have several PRODs that the SSIS packages should be deployed to all of them. So the scenario is that whenever you create a new SSIS project in DEV area or you may modify the existing projects, you need to deploy each SSIS project to QA for testing purposes. So, if you have 3 new SSIS projects or you’ve just modified 3 existing projects, you’ll need to deploy each project separately. It is the same story for QA guys after finishing the test cases and after the SSIS projects pass all the test cases. They’ll need to deploy all projects to UAT. Again it is the same story with UAT and PROD. It is getting harder when you need to deploy all the projects in several different PROD environments.

Using the solution below, you can easily deploy all SSIS projects from an environment to another environment or even several different environments.

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Drop tables from selected schemas database wide

In my previous post called “How to drop tables database wide using T-SQL” I’ve explained that how we could delete all tables database wide in SQL Server. But, what if there are some other schemas other than “dbo” and some tables that are created in those schemas? If we just delete “[dbo].” from the code we will obviously face to the following error message: “Cannot find the object “TABLE_NAME” because it does not exist or you do not have permissions.” for those tables that are not under “dbo” schema. So, we need to retrieve all schemas and their related tables. This approach is really helpful when we are implementing an ETL process that is designed to delete the tables from particular schemas and recreate the tables and populate new data. This is a common way for staging to delete and recreate tables instead of updating existing tables as update is really costly.

So, let’s write some codes.

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