摘要：Brendan Gregg, Netflix An everyday problem in our industry is understanding how software is consuming resources, particularly CPUs. What exactly is consuming how much, and how did this change since the last software version? These questions can be answered using software profilers, tools that help direct developers to optimize their code and operators to tune their environment. The output of profilers can be verbose, however, making it laborious to study and comprehend. The flame graph provides a new visualization for profiler output and can make for much faster comprehension, reducing the time for root cause analysis. In environments where software changes rapidly, such as the Netflix cloud microservice architecture, it is especially important to understand profiles quickly. Faster comprehension can also make the study of foreign software more successful, where one's skills, appetite, and time are strictly limited.
