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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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Toc

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

Go Prometheus exporter – exporting data from your Go application

One of the best ways to track long-term changes to your application is to use time-series data to monitor and alert us about important changes. Prometheus
(https://prometheus.io/) is a great way to perform this task. Prometheus is an open source time-series monitoring tool that utilizes a pull model via HTTP in order to drive monitoring and alerting. It is written in Go and has first-class client libraries for Go programs. The following steps show a very simple implementation of the Go Prometheus HTTP library:

  1. First, we instantiate our package and import our necessary libraries:
package main
import (
"net/http"
"github.com/prometheus/client_golang/prometheus/promhttp"

)
  1. Then, in our main function, we instantiate a new server and have it serve a NewServeMux that returns a Prometheus...
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