How to Prevent Firebase Runaway Costs
Taming Firebase Costs: A Practical Guide
Firebase is an incredibly powerful platform that lets developers build robust applications quickly. However, users are rightly worried about the eye-watering costs, which are usually unexpected, and the fear of hitting that kind of bill puts off a lot of people for whom Firebase is a brilliant tool.
In this post, we’ll explore the main Firebase services that tend to incur the highest costs, discuss the events that can cause sudden billing spikes, and share strategies for avoiding these Firebase bills, helping you keep your spending under control.
Firebase Services That Can Drive Up Costs
To better understand how Firebase costs can accumulate, let’s look at some common use cases and their associated pricing.
Before diving into cost prevention strategies, it’s important to understand which Firebase services are most likely to contribute to high bills. Certain Firebase services are particularly prone to Firebase runaway costs when usage isn’t carefully managed. Here are some of the key culprits:
1. Cloud Firestore
Firestore Pricing Details: Firestore charges are based on:
- Document Reads, Writes, and Deletes: Each operation (read/write/delete) is billed separately.
- Storage Costs: Based on the amount of data stored in Firestore.
- Network Egress: Costs associated with data transfer out of Firestore.
- Queries: Each query operation counts as a read for every document returned. Complex queries can result in multiple document reads, increasing costs significantly.
For example, reading 50,000 documents, writing 10,000, and deleting 5,000 documents in a month can cost around $5-$10 depending on data size. Optimising queries with techniques like pagination, composite indexes, limiting reads, and structuring data to minimize unnecessary lookups can significantly reduce these costs.
2. Realtime Database
Much like Cloud Firestore, the Realtime Database charges based on data transfer and simultaneous connections. Firebase cost management is essential here to avoid unexpected expenses. As your application scales, maintaining multiple concurrent connections or processing large volumes of data can significantly contribute to Firebase runaway costs.
Realtime Database Pricing Details: The pricing for Realtime Database is based on:
- Data Downloaded: You are billed for the amount of data downloaded from the database. Uploads are free, but all outbound data incurs costs.
- Simultaneous Connections: Charges apply based on the number of concurrent connections to the database.
- Storage Costs: You’re billed for the amount of data stored in your database.
For example, if your application handles 1,000 simultaneous connections with an average of 500MB of data downloaded daily, your monthly costs could quickly add up, especially if the app scales unexpectedly.
Use Case Example:
Chat Application: A chat app with 500 active users simultaneously sending messages can incur high costs due to the number of connections and data transferred. If each message is about 1KB and each user sends 50 messages daily, this could result in over 25MB of data transfer daily, costing around $5–$10/month depending on data usage patterns. As your application scales, maintaining multiple concurrent connections or processing large volumes of data can significantly contribute to Firebase runaway costs.
An example of how you could optimise this is to structure your data so you only get the current chat for a user (rather than downloading all messages), and also only get the most recent messages.
3. Cloud Storage
Storing and serving large files or high volumes of media can quickly add up. Costs are influenced by the amount of data stored, the frequency of downloads, and network egress
Cloud Storage Pricing Details: Firebase Cloud Storage pricing is based on:
- Storage Costs: Charged per GB of data stored per month. Rates vary depending on the storage class (Standard, Nearline, Coldline, Archive).
- Network Egress: Billed based on the amount of data transferred out of Firebase to external locations. Transfers within Google Cloud are generally cheaper.
- Operations Costs: Costs apply for class A (uploading, listing files) and class B operations (downloading, reading metadata).
For example, storing 1TB of data in Standard Storage in North America could cost around $20/month. However, frequent access to large files could result in additional egress charges, potentially doubling monthly costs.
Use Case Example:
- Photo Sharing App: An app storing user-uploaded photos might accumulate 1TB of data from 100,000 images. With Firebase’s pricing, this could cost around $20/month for storage alone. If each photo is viewed frequently (causing high download costs), monthly expenses could double or triple quickly. Implementing caching and serving images through a CDN can significantly reduce these costs.
4. Cloud Functions
Cloud Functions are billed based on the number of invocations, execution time, and outbound data. Firebase cost management plays a critical role in controlling execution times and limiting unnecessary invocations. A simple misconfiguration or an unexpected surge in requests can dramatically increase function executions, leading to hefty Firebase costs.
Cloud Functions Pricing Details: Firebase Cloud Functions pricing includes:
- Invocations: Each time a function is triggered, it counts as an invocation.
- Compute Time: Billed based on the memory allocated to the function and the time it takes to execute.
- Outbound Data Transfer: Charged based on the volume of data sent from the function to external services.
For example, if your app processes 100,000 invocations per month with each function running for an average of 200ms, the costs can range from $10-$30/month. However, inefficient coding practices, like recursive calls or lack of proper exit conditions, can inflate these costs significantly.
Use Case Example:
- E-commerce Backend: Imagine an online store with 1,000 daily transactions. If each transaction triggers multiple Cloud Functions for inventory updates, payment processing, and notifications, with an average execution time of 500ms, this could lead to 30,000 invocations monthly. This usage can accumulate costs around $20–$30, but inefficient coding practices (like unnecessary nested calls) could exponentially increase these costs.
Firebase Frights: Real-World Examples of Unexpectedly High Bills
Understanding the theory is helpful, and there are some pretty scary examples of these runaway bills and how they can strike
The $70,000 Surprise
A user on Hacker News reported receiving a shocking $70,000 bill in a single day—a massive jump from their usual $50 bill (source).
The $120,000 Monthly Bill
A FlutterFlow community member shared their shock after being quoted a $120,000 monthly Firebase bill. This user, new to Firebase, hadn’t optimized their app for cost efficiency. (source).
The £13,000 Bill for Personal Projects
A Reddit user recounted receiving an unexpected £13,000 bill for two personal projects. As a new developer, they likely made mistakes in their code or security settings. T (source).
Crowdfunding App Optimisation Case Study
A developer demonstrated how a crowdfunding app faced potential costs of $30,000/month due to inefficient Firestore queries. The app fetched all donations for each campaign, causing millions of reads. The solution? Storing the total amount as a separate field and updating it with each new donation via a Cloud Function, reducing reads and slashing costs dramatically (source).
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 aren’t just a threat to your application’s performance—they can also result in a sudden flood of requests. This unexpected traffic can cause Cloud Functions to be invoked repeatedly, trigger excessive reads and writes in your databases, and increase storage requests, all of which contribute to steep Firebase costs.
Unoptimised Database Queries
Poorly structured queries in Cloud Firestore or the Realtime Database can result in reading more data than necessary. When every query triggers hundreds or thousands of document reads, your Firebase costs can balloon unexpectedly.
Accidental Infinite Loops or Recursive Calls
A bug in your Cloud Functions code, such as an accidental infinite loop or recursive function calls, can lead to continuous invocations. Without proper safeguards, this error can generate an unanticipated surge in usage that quickly turns into a costly problem, driving up Firebase costs.
Unexpected User Behaviour
Sometimes, legitimate user activity—such as an unforeseen viral trend or spike in usage—can lead to a surge in requests, data reads, or file downloads. Without appropriate limits or caching, these events may result in significant additional charges, contributing to Firebase runaway costs.
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 the Google Cloud Console to establish spending alerts and set budget limits. These tools notify you when your usage nears a predefined threshold. However, these alerts aren’t enough on their own - when an alert is triggered, you’ll need to manually take action - if you’re being DDoSed in the middle of the night - it might be too late to avoid a massive bill.
Consider using advanced cost protection tools like FlameShield. FlameShield offers real-time monitoring and automated responses to potential cost surges, helping to prevent runaway Firebase costs before they escalate.
Optimise Your Database Structure and Queries
Analyse and refine your database schema to reduce unnecessary data transfers. Use indexing where appropriate and consider pagination or caching to lower the number of reads, helping to limit Firebase costs. Never ‘scan’ an entire collection - be more specific in the documents you need to retrieve.
Implement Rate Limiting and Throttling
Protect your Cloud Functions and other services by applying rate limiting. This not only helps defend against DDoS attacks but also guards against unexpected spikes in traffic from legitimate sources, supporting Firebase cost optimisation.
This isn’t the easiest step to take right now, but one option is to use this tool to help:
Firebase Functions Rate Limiter
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,
Final Thoughts: Stay Ahead of Firebase Costs
So, how can you keep Firebase costs under control? By understanding which Firebase services are most likely to incur high costs and recognising the triggers behind billing spikes, you can proactively manage your Firebase expenses. Combine thoughtful planning, continuous monitoring, and protective tools like FlameShield to keep your applications efficient and cost-effective.
After all, wouldn’t you rather spend time building amazing apps instead of stressing over unexpected bills? Stay proactive, and Firebase will be a powerful ally in your development journey.
References
- Understand Realtime Database Billing - Firebase
- Firebase bill is usually $50, but I was surprised to see a $70k bill - Hacker News
- Unexpected Firebase Costs - FlutterFlow Community
- Unexpected Firebase bill of £13k - Reddit
- How to NOT get a $30K Firebase Bill - YouTube
- Avoid Surprise Bills - Firebase Documentation
- What Can Cause Firebase Costs to Skyrocket? - Reddit
- Never Get an Unexpected Bill from Firebase! - Fire Beast