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Go Performance Optimization

سرفصل های دوره

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.


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

  • 02 - 1. Performance Overview
  • 01 - Why optimize
  • 02 - Setting goals
  • 03 - Understanding Big O notation
  • 04 - Computer architecture overview

  • 03 - 2. CPU Optimization
  • 01 - Measuring speed
  • 02 - Using the profiler
  • 03 - Common mistakes
  • 04 - Tips and tricks
  • 05 - Challenge Improve a data structure
  • 06 - Solution Improve a data structure

  • 04 - 3. Memory Optimization
  • 01 - Measuring memory
  • 02 - Profiling memory
  • 03 - Common mistakes
  • 04 - Tips and tricks
  • 05 - Challenge Improve memory consumption
  • 06 - Solution Improve memory consumption

  • 05 - 4. Concurrency
  • 01 - Amdahls law and its implications
  • 02 - Fan out
  • 03 - Consumer producer
  • 04 - Challenge GitHub influence
  • 05 - Solution GitHub influence

  • 06 - 5. Service Optimization
  • 01 - Measuring service performance
  • 02 - Choosing serialization format
  • 03 - Choosing transport medium
  • 04 - Caching
  • 05 - Challenge Stock prices
  • 06 - Solution Stock prices

  • 07 - 6. Development Process
  • 01 - Why do you need a process
  • 02 - Recording benchmarks
  • 03 - Monitoring and alerting

  • 08 - Conclusion
  • 01 - Next steps
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