A good example of this is how to set up and manage Structured Query Language, or SQL. SQL may be the IEEE’s 2023 most popular language, but it has a fussy syntax that relatively few dedicate themselves to mastering. Many developers are not familiar with how to write effective and efficient SQL queries, so they may end up with poorly new zealand whatsapp number data performing requests that take longer to return results. Alternatively, developers often turn to Object-Relational Mappers (ORMs) to handle their SQL requests for them. situation simpler for developers, they can suffer from the same poor performance and bad query design that writing your own SQL code can, coupled with the need to update and manage the ORM itself. This combination is often seen alongside a penchant for using long-running transactions that stifle performance.
For DBAs, spotting these issues and correcting them was part of the full-time job. However, for SREs that are not familiar with database performance, these slow transactions can be accepted as “just how things are” rather than a symptom of something being wrong. Alternatively, developers can try throwing more resources at the problem by buying larger machines or cloud instances to run in.
Alongside query design, DBAs were also responsible for setting up data indexes on their databases. Indexing data is a Harry Potter-ish dark art to many, who either over-index or under-index, leading to poor performance. In the past, DBAs used to look for redundant indexes that were no longer used or popular queries that had not been indexed, and then correct the database for better performance.