Course Overview
This course covers the methodology for full-stack workload profiling in the cloud, including the use of performance characterization and flame graphs to resolve real-world problems. The course uses the example of FlowGo, an open-source microservice-based blockchain application, to demonstrate how to identify and resolve performance issues. Students will learn how to use tools such as TCP Life and PMU to trace TCP communications and analyze performance data. The course also covers the concept of CPI (cycles per instruction) and how it can be used to measure performance. By the end of the course, students will be able to apply the full-stack workload profiling methodology to resolve performance issues in their own applications.
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Chapter Overview
This course covers the methodology for full-stack workload profiling in the cloud, including the use of performance characterization and flame graphs to resolve real-world problems. The course uses the example of FlowGo, an open-source microservice-based blockchain application, to demonstrate how to identify and resolve performance issues. Students will learn how to use tools such as TCP Life and PMU to trace TCP communications and analyze performance data. The course also covers the concept of CPI (cycles per instruction) and how it can be used to measure performance. By the end of the course, students will be able to apply the full-stack workload profiling methodology to resolve performance issues in their own applications.