Go Performance Optimization

Course details

Code that runs faster and consumes less memory can save your organization a lot of money, and responsive applications keep your users happy. For the past 25 years, Miki Tebeka has helped companies develop faster software with fewer resources. In this course, he shares the tools and techniques that he uses when optimizing code and services. Learn when and why to optimize and go over goal setting. Go over how to measure code performance and memory consumption. Explore solutions that involve concurrency and service optimization. Plus, discover why recording benchmarks is important and how to monitor and alter performance effectively.

Concepts

0. Introduction

01 - Go performance optimization
02 - What you should know
03 - Setting up

1. Performance Overview

04 - Why optimize
05 - Setting goals
06 - Understanding Big O notation
07 - Computer architecture overview

2. CPU Optimization

08 - Measuring speed
09 - Using the profiler
10 - Common mistakes
11 - Tips and tricks
12 - Challenge - Improve a data structure
13 - Solution - Improve a data structure

3. Memory Optimization

14 - Measuring memory
15 - Profiling memory
16 - Common mistakes
17 - Tips and tricks
18 - Challenge - Improve memory consumption
19 - Solution - Improve memory consumption

4. Concurrency

20 - Amdahl's law and its implications
21 - Fan out
22 - Consumer producer
23 - Challenge - GitHub influence
24 - Solution - GitHub influence

5. Service Optimization

25 - Measuring service performance
26 - Choosing serialization format
27 - Choosing transport medium
28 - Caching
29 - Challenge - Stock prices
30 - Solution - Stock prices

6. Development Process

31 - Why do you need a process
32 - Recording benchmarks
33 - Monitoring and alerting

Conclusion

34 - Next steps