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Hands-On High Performance with Go

You're reading from   Hands-On High Performance with Go Boost and optimize the performance of your Golang applications at scale with resilience

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789805789
Length 406 pages
Edition 1st Edition
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Author (1):
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Bob Strecansky Bob Strecansky
Author Profile Icon Bob Strecansky
Bob Strecansky
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Learning about Performance in Go
2. Introduction to Performance in Go FREE CHAPTER 3. Data Structures and Algorithms 4. Understanding Concurrency 5. STL Algorithm Equivalents in Go 6. Matrix and Vector Computation in Go 7. Section 2: Applying Performance Concepts in Go
8. Composing Readable Go Code 9. Template Programming in Go 10. Memory Management in Go 11. GPU Parallelization in Go 12. Compile Time Evaluations in Go 13. Section 3: Deploying, Monitoring, and Iterating on Go Programs with Performance in Mind
14. Building and Deploying Go Code 15. Profiling Go Code 16. Tracing Go Code 17. Clusters and Job Queues 18. Comparing Code Quality Across Versions 19. Other Books You May Enjoy

Understanding trace collection

Being able to collect traces is integral to implementing tracing in your distributed system. If we don't aggregate these traces somewhere, we won't be able to make sense of them at scale. There are three methods with which we can collect trace data:

  • Manually invoking the tracing of the data by calling trace.Start and trace.Stop
  • Using the test flag -trace=[OUTPUTFILE]
  • Instrumenting the runtime/trace package

In order to understand how to implement tracing around your code, let's take a look at a simple example program:

  1. We first instantiate our package and import the necessary packages:
package main

import (
"os"
"runtime/trace"
)
  1. We then invoke our main function. We write the trace output to a file, trace.out, which we will use later:
func main() {

f, err := os.Create("trace.out")
if err...
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