Performance monitoring in Firebase - Step-by-Step Execution

Process Flow - Performance monitoring

Start App

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Initialize Firebase Performance

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Collect Metrics Automatically

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Add Custom Traces & Attributes

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Send Data to Firebase Console

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Analyze Performance Data

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Optimize App Based on Insights

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Repeat Monitoring Cycle

This flow shows how Firebase Performance Monitoring starts with app launch, collects data automatically and custom traces, sends it to the console, and helps optimize the app.

Execution Sample

Firebase

import { getPerformance, trace } from 'firebase/performance';
const perf = getPerformance();
const myTrace = trace(perf, 'custom_trace');
myTrace.start();
// code to measure
myTrace.stop();

This code initializes Firebase Performance, starts a custom trace, runs code to measure, then stops the trace.

Process Table

Step	Action	Evaluation	Result
1	Import Firebase Performance module	Module imported	Firebase Performance ready
2	Initialize performance monitoring	getPerformance() called	Performance instance created
3	Create custom trace named 'custom_trace'	trace(perf, 'custom_trace')	Trace object created
4	Start custom trace	myTrace.start()	Trace timer started
5	Execute code to measure	Code runs	Performance data recorded
6	Stop custom trace	myTrace.stop()	Trace timer stopped and data sent
7	Data sent to Firebase Console	Automatic upload	Performance data available for analysis
8	Analyze data in console	Developer views metrics	Insights for optimization
9	Optimize app based on insights	Code changes	Improved app performance
10	Repeat monitoring cycle	Continuous monitoring	Ongoing performance improvements

💡 Monitoring cycle repeats continuously as app runs and data is collected

Status Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	After Step 6	Final
perf	undefined	Performance instance	Performance instance	Performance instance	Performance instance	Performance instance
myTrace	undefined	undefined	Trace object	Trace running	Trace stopped	Trace stopped

Key Moments - 3 Insights

Why do we need to call myTrace.start() and myTrace.stop()?

Because the trace measures the time between start() and stop() calls. Without them, no timing data is recorded. See execution_table rows 4 and 6.

Does Firebase Performance Monitoring collect data automatically?

Yes, it collects some metrics automatically after initialization (step 2). Custom traces are optional for detailed measurement (step 3).

When is the performance data available in the Firebase Console?

After stopping the trace, data is sent automatically (step 7) and then appears in the console for analysis (step 8).

Visual Quiz - 3 Questions

Look at the execution table, what is the state of 'myTrace' after step 4?

A Trace object created but not started

B Trace timer started and running

C Trace timer stopped

D Trace object undefined

💡 Hint

Check the 'Result' column at step 4 in the execution_table

At which step does the performance data get sent to Firebase Console?

A Step 5

B Step 6

C Step 7

D Step 8

💡 Hint

Look for 'Data sent to Firebase Console' in the execution_table

If we skip calling myTrace.stop(), what happens to the trace data?

A No timing data is recorded or sent

B Data is sent automatically anyway

C Trace never starts

D Trace stops after a timeout

💡 Hint

Refer to key_moments about start() and stop() calls and execution_table steps 4 and 6

Concept Snapshot

Firebase Performance Monitoring:
- Initialize with getPerformance()
- Automatically collects basic metrics
- Use trace() to create custom traces
- Call start() and stop() to measure code blocks
- Data uploads automatically to Firebase Console
- Analyze data to improve app speed
- Repeat monitoring continuously

Full Transcript

Firebase Performance Monitoring starts when the app launches and initializes the performance instance. It collects some metrics automatically. Developers can create custom traces to measure specific code parts by calling start() and stop() on the trace object. After stopping, data is sent to the Firebase Console where developers analyze it to find performance issues and optimize the app. This monitoring cycle repeats continuously to keep improving app speed and user experience.