How to Prevent Firebase Runaway Costs

Taming Firebase Costs: A Practical Guide

Firebase is a powerful platform for building apps quickly, but the fear of unexpected, high costs can be a major deterrent. By understanding which services drive up expenses, recognizing the triggers behind billing spikes, and combining thoughtful planning with continuous monitoring, you can effectively manage your Firebase costs. This guide explores how to stay proactive, keep your applications efficient, and make Firebase a powerful ally in your development journey instead of a source of stress over unexpected bills.

TL;DR: How to Prevent Runaway Costs

Set Budget Alerts: Use the Google Cloud Console to set spending limits and get notified, but remember they require manual action.
Optimise Queries: Refine your database structure and queries to avoid fetching unnecessary data. Never scan entire collections.
Implement Rate Limiting: Protect your Cloud Functions from excessive invocations caused by attacks or bugs.
Enforce Strict Security Rules: Lock down your database and storage to prevent unauthorized access.
Enable App Check: Ensure requests to your backend are from your genuine app, blocking fraudulent traffic.
Limit Upload Size: Compress files before uploading and use a CDN for frequently accessed content.
Review Function Triggers: Carefully test your Cloud Functions to prevent infinite loops, especially those triggered by database writes.
Use Automated Tools: Consider tools like FlameShield for real-time monitoring and automated protection against cost surges.

Firebase Services That Can Drive Up Costs

Certain Firebase services are prone to runaway costs if not managed carefully. Here are the key culprits:

1. Cloud Firestore

Billed on: Document Reads/Writes/Deletes, Storage, and Network Egress.
Watch out for: Inefficient queries reading excessive documents, which can escalate costs quickly.
Example: A social media app fetching entire comment threads instead of paginating results can trigger excessive read operations and high bills.

2. Realtime Database

Billed on: Data Downloaded, Simultaneous Connections, and Storage.
Watch out for: High numbers of concurrent users and large, frequent data transfers.
Example: A chat app’s costs can rise with many simultaneous connections; this can be optimized by structuring data to fetch only the most recent messages.

3. Cloud Storage

Billed on: Storage (per GB), Network Egress, and Operations (uploads/downloads).
Watch out for: Storing large media files that are downloaded frequently.
Example: A photo-sharing app can see costs triple from frequent downloads; implementing caching and serving images through a CDN can significantly reduce this.

4. Cloud Functions

Billed on: Number of Invocations, Compute Time, and Outbound Data.
Watch out for: Inefficient code, accidental infinite loops, or recursive calls that trigger continuous executions.
Example: An e-commerce function that triggers other functions in a nested way can exponentially increase invocations and costs per transaction.

Firebase Frights: Real-World Examples

The Damage	The Story	Source
$70,000 in one day	A developer’s usual $50 bill skyrocketed after a bug likely caused an infinite loop.	Hacker News
$120,000 monthly quote	A new Firebase user on FlutterFlow was quoted an enormous monthly bill due to an unoptimised app.	FlutterFlow Community
£13,000 for personal projects	A new developer was hit with a £13,000 bill for two small personal projects, likely due to misconfigured security rules or code.	Reddit
$30,000/month potential cost	A crowdfunding app was fetching all donations for every campaign, leading to millions of reads. A simple optimisation slashed the potential costs.	YouTube

What Triggers Billing Spikes

Understanding the specific events that lead to billing spikes can help you anticipate and mitigate them. Some common triggers include:

DDoS Attacks and Malicious Traffic

Distributed Denial-of-Service (DDoS) attacks can flood your app with requests, causing a sudden spike in function invocations, database reads/writes, and storage operations, all of which drive up costs.

Unoptimised Database Queries

Poorly structured queries that read more data than necessary can cause costs to balloon unexpectedly, especially when they trigger thousands of document reads per operation.

Accidental Infinite Loops or Recursive Calls

A bug in your Cloud Functions, like an infinite loop or recursive call, can lead to continuous invocations, generating a massive surge in usage and a costly bill.

Unexpected User Behaviour

A sudden viral trend or spike in legitimate user activity can lead to a surge in requests, data reads, or file downloads, resulting in significant charges if not properly managed.

How to Avoid Firebase Runaway Costs

Preventing Firebase runaway costs is hard, but here are some strategies for Firebase to help:

Budget caps that work

Use cost alerts in Google Cloud Console, and if you want automated protection, try an open-source Firebase Kill Switch. The difference with FlameShield is that it’s set-and-forget: it’s easier to configure, doesn’t require you to manage your own monitoring logic, and it runs continuous health checks to make sure your kill switch is still working — not just set up once and forgotten. This matters because a misconfigured kill switch is the same as having none at all.

Optimise Your Database Structure and Queries

Design queries to return only what you need—use indexes and pagination to avoid broad collection scans. Set up security rules that enforce these limits so malicious actors can’t scan entire collections.

Implement Rate Limiting and Throttling

You can use the Firebase Functions Rate Limiter for open-source protection. FlameShield offers smart, configurable rate limiting — you choose the point at which it activates, so you can reduce latency under normal load while still automatically blocking traffic surges before they cause large bills. It supports per-user, per-IP, or global limits, so you can protect costs without slowing down your entire app.

Enforce Strict Security Rules

Ensure that your Firebase security rules are comprehensive and up-to-date. A good first step is preventing any access to data (even data that is ok to be public) from firestore and storage, this gives you the ability to limit user requests on a user as well as provides friction for anyone trying to deliberately rack up costs.

Limit the size of uploads

Put in triggers and client side code that automatically compress and shrink your files before they’re uploaded. Similarly, make sure that you’re only storing the necessary data - and caching things client side if needed. If you’re using firebase storage to retrieve files really frequently - think about instead storing them in a CDN instead - this can cut your costs and increase the performance for users by placing images in caching locations closer to where they actually are.

Test and review your function triggers

This is the big one, and this is the real risky place that functions come from!

If you write to firestore, trigger a function, and then write back to the same firestore instance - your function will get called again. These kind of circular dependency can immediately spike your usage and give you a massive headache. Look for the other triggers in place - pubsub in particular will retry,