There is a problem validating your database

There are a few extremely rare circumstances where it is viable to release straight from development into production.Except for those unicorns, the rest of us are required to go through some sort of process prior to releasing our code into production.In a perfect world, testing wouldn’t even be necessary.In a slightly imperfect world, testing would be easy to do and the environment would exactly match your production environment, both in terms of processing power and in the quantity and quality of the data. Instead, getting a testing environment setup involves a series of trade-offs that allow you to adequately simulate the production environment while working on smaller machines, frequently with less data that is also different from production.Next, depending on the functionality being developed and tested, you don’t want production information within the test environment (imagine testing email processing with your production email list).Finally, the size of your production system may preclude having a full copy of the production system in your testing environment.A deployment consists of the steps required to support this process by getting new code into the environments necessary to support the release.

The necessary checks and tests can turn up surprises: The handover process can expose deficiencies.

The Release process aims to create a speedy method for getting code out of the development and into production while, at the same time, also attempting to protect the production environment to ensure uptime and data integrity.

To reconcile these conflicting aims, Database Lifecycle Management recommends that you must stick to the Release process tightly, as its defined, and bring as much automation to bear as you possibly can on that process.

With good teamwork, planning and forethought, though, the process can be made almost painless This article describes how a piece of database code can be moved to production, painlessly and quickly, through the necessary testing environments and then via staging to releasing the database code into the production environment.

The more of the process of release that you can automate, the smoother the process becomes.

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The basic server setup for a QA environment is required to emulate the functionality of production, but it doesn’t have to emulate its performance.

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