Showing posts with label Production Cloning. Show all posts
Showing posts with label Production Cloning. Show all posts

Friday 15 February 2013

Data Subset in TDM

In my previous post, I discussed the Challenges in Production Cloning approach.  In this post, we will focus on its solution, the Data Subset process / Data Sub-setting.

Data subset is the process of slicing a part of the Production Database and loading it into the Test Database.  For ex. instead of cloning a 50 TB production database, create a subset that is only 50 GB worth data and put it back into the Test Database.  Lets assume in a retail application, you have a Customers table having 10 million customers and Orders table having 100 million orders and 100 million other transaction tables, our subset process will try to shrink the sizes to good reasonable limits as depicted in the picture below.















Advantages of data sub-setting

Wednesday 13 February 2013

Challenges in Production Cloning approach

In my previous articles, I have already discussed the topics "How to create Test Data" and "Top 3 Challenges in using Production data in Test Environments".  In this post we will focus on the challenges that we face in Production Cloning approach and how to overcome those challenges.

1.  Infrastructure


Even though it is highly recommended to have the Test Environment in the same lines as Production, it is not always feasible to test under those real-time conditions.  It is highly recommended to do Performance / load / stress tests exactly mimicking the Production database, but the expensive infrastructure requirements might be an overkill for Functional Testing.  But cloning might force you to have production like infrastructure which will translate into higher costs for the customer.

2.  High Storage Costs


Another major challenge associated with Production Cloning is that all the production data needs to be stored in testing region.  Assuming the production data is 50 TBs (Terabytes), the Test Database also needs to hold 50 TBs of data.  So storage has to be provided for storing all of the data.  And with the databases being backed up regularly, that would mean higher storage costs for the customer.