✍️ @Jessica's Blog

[LJess495]

Hi and welcome to Content Lab! Here is a self paced guide to ensure you get feedback as you publish your technical blog.

Resources:

• Previous workshop recording
• Previous blog posts

Timeline:

• 📋 Dec 1st have an outline and open up issue
• 📰 Dec 8th have rough draft in
  • Mentor reviews by 12/15
• [ ] Dec 15th-20th turn in final draft

📋 Blog Outline: Write your outline in the issue directly

Requirements

Questions to consider:

• Who’s reading this? Where are they in your dev journey? What do they need to know before they can dive into this story?
• If people could leave with just one action, what would it be?
• Were there surprises or alternative problem solving you want to give a heads up to?

Sample Topics for your blog post

• Creating tests for Stripe/Cicero/Twilio
• Using Vuetify and V-cards
• Debugging a PR test failure affecting entire codebase and creating an issue for it
• System Design/Architecture design for caching capability
• Implementing Text to Speech
• Configuring secrets for APIs in codespaces
• Building Actions for [security|community|CI| etc]

Example Outlines

What makes good documentation on open source?

• Could this be a list? (3 pieces of documentation thats easy to check for and add to the project to add immediate value?
• What inspired you from the Tech documentation workshop?
• What would you help encourage other first time contributors to do?
• Is a learning curve for everyone? And whats the balance between good documentation and too much documentation? Choice architecture
• What is each space used for? Wiki vs Discussion vs Pages
• How do we search and find? Reference: https://blackgirlbytes.dev/conquering-the-fear-of-contributing-to-open-source Reference issue/PR for photos Conclusion: Documentation is always changing, will always be needed`

To Do: when you complete the requirements, add "outline ready" label on your issue

• [ ] Identify your topic from one of the PRs approved
• [ ] Outlining bullet points of blog roadmap
• [ ] Is your blog a List, Survey, or demo?
• [ ] Which Visuals or Diagram or Code snippets will you add
• [ ] References to resources

📰 Blog Rough draft: Format into a google doc

Questions to answer across draft

• Why is this helpful for a reader?
• What problem does this help them solve?
• What kind of experience should the reader have or that you will provide so they’re up to speed
• What larger problem is this solving?
• Were there other ways of solving this problem - what made you choose the one that you did?
• What were the positive tradeoffs? (Did it save time? Save hours? Was more secure?)
• What is the best way to present the content (i.e. code snippets, graphics) ?
• What additional resources can they provide the reader if they want more information?
• Is there a call to action?

To do: when you complete the requirements, add "draft ready" label on your issue

• [ ] intro paragraph
• [ ] context of Amplify
• [ ] paragraph on problem
• [ ] paragrph compare your solution
• [ ] paragraph impact your solution
• [ ] Less than 600 words
• [ ] Drop link to your google doc (with permissions for edits) in review issue

[LJess495]

Outline of Blog Topic: Data Models Title: Before You Build a Database: Why Understanding Data Models is Key

Sections:

1. Data Model Overview
   1. What are data models
   2. Why are data models important
2. Understanding Data Model
   1. Types of data models (Conceptual, Logical, Physical)
   2. Core components of data models (entities, attributions, relationships)
3. Data Model in Action
   1. Documenting Data Models
      1. General Techniques
      2. Applying to Amplify
         1. Breakdown of the data models from the Amplify Project
   2. Incorporating a data model into a database
      1. Use my current working issue as an example on how its done - Data Model: AdvocacyGroupTypes
      2. Testing & Iterations
         1. How I test
         2. Why iterations are important
      3. Useful Optimization strategies - indexing, partitioning, etc.
4. Things to keep in Mind
   1. Common Challenges (data redundancy, scalability)
   2. Best practices (flexibility, version control)
5. Conclusion
   1. Why it is important to have a solid understanding of data models
   2. Data models is the backbone to ensure data in your project is stored and managed effectively