Performance Guide

Avonni Dynamic Components are fast by default. This guide helps you keep them that way as your components grow in complexity.

Three Rules That Matter Most

1. Fetch data once, pass it down

• Parent components should query Salesforce

• Child components receive data through resources

• Avoid multiple components querying the same data independently

2. Only load what you need

• Use specific filters in your queries (e.g., RecordType, Status, Date Range, etc.).

• Show/hide sections with conditional visibility instead of loading everything upfront

• Consider if data needs to load immediately or can wait for a user action

3. Keep structures simple

• Flat component structures perform better than deeply nested ones

• Use specialized components (Data Table, Tree) for complex data instead of nesting multiple Dynamic Components

• If you're nesting more than 2-3 levels deep, there's usually a more straightforward way

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Common Performance Mistakes

❌ Each nested component runs its own "On Load" query This creates a cascade of queries that slows everything down.

✅ Parent fetches data, passes subsets to children via resources One query, multiple components use the results.

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❌ Loading all 50 columns in a Data Table by default Most users only need 5-7 key fields initially.

✅ Show essential columns, reveal details on-demand Use Open Flow Panel or Open Dynamic Component Panel for full record details.

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❌ Component A updates Component B, which updates Component A Creates infinite loops or excessive re-rendering.

✅ Design one-way data flows Parent → Child communication through resources, Child → Parent through events.

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When to Optimize

You probably have a performance issue if:

• Components take more than 2-3 seconds to load

• Users see multiple loading spinners in sequence

• Browser Network tab shows 10+ Salesforce queries for one page load

Use Browser Developer Tools (Network tab) to see what's actually happening. If you're seeing dozens of requests or slow queries, that's your starting point.

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Need Help?

Many Trailblazers in our Community Group have tackled these exact challenges. They share:

• Network tab screenshots with diagnostic help

• Before/after architecture improvements

• Query patterns for large datasets

• What actually worked in production environments

Join the Community | Direct questions: [email protected]