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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

Implementing OpenCensus for your application

Let's use a practical example for OpenCensus tracing in an application. To get started, we need to make sure that we have Docker installed on our machine. You should be able to use the installation documents at https://docs.docker.com/ in order to be certain that Docker is installed and runs correctly on your machine. Once this is completed, we can get going with creating, implementing, and viewing a sample application. Once we have Docker installed, we can pull important images for our instrumentation. In our example, we will use Redis (a key–value store) to store key–value events in our application and Zipkin (a distributed tracing system) to view these traces.

Let's pull our dependencies for this project:

  1. Redis, which is a key–value store that we are going to use in our sample application:
docker...
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