Implementation mistakes that penalties productivity and affect hosting bills
An example on how the slowness could sit there undetected for years. This is the story how we’ve managed to nail the cause down.
How do frameworks measure the size they occupy in memory?
That day I figured out process thinks to consume 2 times more RAM than it physically has.
Who is more interested in hosting optimization – you (who pays the bill), or vendor (that gets a percent from a hosting price)? The story is about how a simple query tune could make a difference.
No matter how powerful your hardware is in case most of that power dissolves in poor implementation. Can you guess the heaviest CPU consumer in enterprise-scaled software?
This story is about coding attitude and paying attention to implementation detail.
Is it too ambitious to say we could save at least 2/3 of time by optimizing code for arguments that are supplied 95% of times?
How many times you’ve witnessed application taking all the free memory? This story puts light on the roots of the problem.
Would a few weeks old data be a strong foundation for making a decision today? Is it fair to say you’ll always need more power to crunch the data with a constant growth of information collected?