English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 12m | 170 MB
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.
Table of Contents
Introduction
1 Go performance optimization
2 What you should know
3 Setting up
Performance Overview
4 Why optimize
5 Setting goals
6 Understanding Big O notation
7 Computer architecture overview
CPU Optimization
8 Measuring speed
9 Using the profiler
10 Common mistakes
11 Tips and tricks
12 Challenge Improve a data structure
13 Solution Improve a data structure
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
Concurrency
20 Amdahl’s law and its implications
21 Fan out
22 Consumer producer
23 Challenge GitHub influence
24 Solution GitHub influence
Service Optimization
25 Measuring service performance
26 Choosing serialization format
27 Choosing transport medium
28 Caching
29 Challenge Stock prices
30 Solution Stock prices
Development Process
31 Why do you need a process
32 Recording benchmarks
33 Monitoring and alerting
Conclusion
34 Next steps
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