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Lessons
9 modules
41
Video duration
32 videos
7h 9m
Download
8 files
232.2 KB
Quizzes
0
Build a Google Analytics in Go

Build a Google Analytics in Go

Product information

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Description

Build a basic Google Analytics-like application using Go, TypeScript, PostgreSQL, Docker, and ClickHouse.

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Additional details

This course assumes you've taken my Build SaaS apps in Go course or are familiar with Go's standard library for building web applications.

We cover the following aspects:

  1. The client-side tracker.
  2. The Go backend API.
  3. Geo-localization from an IP address.
  4. Storing the data into PostgreSQL.
  5. Using Docker to improve your developer's life.
  6. Generating traffic and testing the performance of our system.
  7. Optimizing the DB, table, and queries.
  8. Using ClickHouse to handle 100x the volume of our database.
  9. Building a CLI dashboard.
  10. Deploying our approach to a VM.

Lessons in this course

All lessons are available after your purchase.

Introduction
  • 1. Course intro 3 mins
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  • 2. What you need 0 mins read time
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The JS tracker
  • 1. What we need 9 mins
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  • 2. Setup project 11 mins
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  • 3. Tracker class 16 mins
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  • 4. Track page views 13 mins
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  • 5. Handle missing data 16 mins
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  • 6. Code 41.7 KB
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Go server API
  • 1. API design 3 mins
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  • 2. Track handler 10 mins
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  • 3. Decode data 15 mins
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  • 4. Data structure 20 mins
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  • 5. Use Docker to test 28 mins
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  • 6. Code 57.5 KB
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Get geo info
  • 1. Architecture design 3 mins
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  • 2. Run the project 16 mins
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  • 3. Call from API 12 mins
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  • 4. Code 17.8 KB
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Generate traffic
  • 1. Fill database 4 mins
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  • 2. Generate 15M rows 14 mins
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  • 3. Import the data 15 mins
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  • 4. Code 2.2 KB
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Improve performance
  • 1. The problem 14 mins
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  • 2. Let's normalize 16 mins
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  • 3. This sucks! 10 mins
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  • 4. ClickHouse? 10 mins
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  • 5. Is it faster than PG? 12 mins
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  • 6. Code 486 bytes
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Refactor API for ClickHouse
  • 1. Swap PG for ClickHouse 14 mins
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  • 2. Queue and batch inserts 27 mins
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  • 3. Adding referrer domain 3 mins
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  • 4. Code 66.2 KB
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CLI dashboard
  • 1. Proof of concept 18 mins
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  • 2. Refactor and display metrics 19 mins
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  • 3. Dashboard v1 27 mins
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  • 4. Code 26.0 KB
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Deployment
  • 1. Add configuration 11 mins
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  • 2. API authentication 9 mins
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  • 3. Servers config / setup 23 mins
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  • 4. Dashboard config 8 mins
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  • 5. Code 20.3 KB
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