lengthy ,” adds Heneke . “ I was joking we all could have had babies in that time .”
The first job ? List all the company ’ s individual systems and rank them according to requirements including CPU speed , memory , disc volume , disc I / O , and operating system type , before mapping them to the AWS environment .
All in all , the total number of systems to consider reached around 500 .
“ It sounds like something you can do over a cup of tea , but let me reiterate – it takes months to get right ,” says Heneke , who sounds almost haunted by this stage of the process . “ There ' s always something that creeps out of the woodwork . It ’ s a moving target because continuously new systems are created and other systems are decommissioned .”
Migration headaches The migration itself was also far from straightforward .
While a number of Pick n Pay ’ s Microsoft systems could effectively be lifted and shifted across to the cloud , the retailer ' s SAP systems running on IBM AIX caused headaches . Legacy systems on AIX ’ s big endian couldn ’ t be backed up and restored to the little endian in the cloud , meaning the only option was to undertake an exportimport exercise .
“ When you have to do that for a 20-oddterabyte database , it becomes quite a difficult challenge ,” laments Heneke – though he also reveals that the hardest part was managing the integration , bearing in mind the hundreds of partners and suppliers within Pick n Pay ’ s working ecosystem .
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