Concurrency is, essentially, the practice of doing multiple things at the same time, but not, specifically, in parallel. It can help us to improve the perceived performance of our applications, and it can also improve the speed at which our applications run.
The best way to think of how concurrency works is to imagine one person working on multiple tasks and quickly switching between these tasks. Imagine this one person working concurrently on a program, and, at the same time, dealing with support requests. This person would focus primarily on the writing of their program, and quickly context switch to fixing a bug or dealing with a support issue should there be one. Once they complete the support task, they could switch context again, back to writing their program really quickly.
However, in computing, there are typically two performance bottlenecks that we have to watch out for and guard against when writing our programs. It's important to know the differences between the two bottlenecks, as if you try to apply concurrency to a CPU-based bottleneck, then you would find that the program actually starts to see a decrease in performance as opposed to an increase. And if you tried to apply parallelism to a task that really requires a concurrent solution, then you could again see the same performance hits.
