In 2019 the volume of data that we as a single user produce amounts greatly to a massive data set that can compromises event the biggest of infrastructures, specially now that we have so much data to share like global positioning, preferences, email, google search, ad preferences, etc. Performance Engineering provides an understanding on how that infrastructure deals with a massive data and how it should scales to provide you 99.999% of availability. Low level performance engineering gives all industries the possibility of handling the data flow with minimum downtime and giving us the best possible throughput. Most of high end systems runs on cloud computing platforms but intrinsically they are running under different web servers hosts. This could create different branching possibilities as to how to tune them to extract the most of our resources and how we could save dollars by leveraging the right infrastructure at the right time, as well as enabling developers on what are the best data structures that should be used to extract the most performance. Failing as an option gives us the understanding on what SREs could do in case systems events happen and this should not be overlooked, where actually this should be exercised as much as possible