Comparing Firebase's hidden costs and ROI with Kotzilla for Android development teams
In my previous article, I covered how Firebase Performance Monitoring offers high-level insights into app performance but often misses the fine details developers need, especially for complex Android, Kotlin Multiplatform (KMP) and Compose Multiplatform (CMP) apps.
Many Android developers I’ve spoken with initially adopted Firebase because “it was free.” They tried to work around its limitations by adding custom traces and building manual dashboards to get more visibility.
But, is Firebase Performance Monitoring truly free ?
Once you factor in custom instrumentation, cloud storage, ETL pipelines, and developer time, the Total Cost of Ownership (TCO) can be high.
Beyond cost, there’s also Return on Investment (ROI) to consider: how much do these investments actually improve user experience, reduce downtime, or protect app revenue?
This article breaks down Firebase’s hidden costs and compares them to Kotzilla, a built-in performance monitoring platform that delivers full visibility and measurable ROI for Kotlin apps using the Koin DI framework.
Firebase’s pricing page shows Performance Monitoring capabilities available for free in both the Spark (Free) and Blaze (Paid) plans.
While this is a valid statement, the free tier provides basic trends and metrics on your app, as well as the ability to add custom traces. In practice, for production-grade monitoring and analysis, teams often complement these capabilities with other Firebase services, third-party tools, or custom developments. The table below highlights the differences between the free Spark plan and other related services and tools on the paid Blaze plan:
| Aspect | Spark Plan (Free) | Part of Blaze Plan (Paid) |
|---|---|---|
| Session sampling coverage | Minimal (~1–5% of sessions), even in debug builds | Full coverage requires manual implementation using BigQuery/Storage usage |
| Custom trace quota | Limited (exact daily quota not public) | Unlimited, but extra costs generated to export and analyze the data |
| BigQuery export | ❌ Not available | ✅ $0.02/GB stored + $5/TB queried |
| Storage retention | 30 days in Firebase console | Long-term via BigQuery or Cloud Storage (storage costs apply) |
| Firebase Storage (logs & diagnostics) | 1 GB free / 10 GB outbound | $0.10/GB stored + $0.15/GB served |
| Cloud Firestore / Realtime DB | 1 GB free | Pay-as-you-go, scales with volume |
| Production-grade support | ❌ No SLA | ✅ SLA-backed support (~$100/mo+) |
The hidden cost isn’t just money, it’s developer effort: instrumenting traces, correlating data, debugging regressions, and maintaining pipelines. Over time, this effort greatly exceed nominal service and infrastructure costs, slowing down problem resolution.
Let’s break down the key areas where Firebase creates overhead and how Kotzilla’s built-in approach handles them automatically.
Firebase has two major limitations that make it hard to diagnose real performance issues in Android and Kotlin Multiplatform apps:
Limited sampling
By default, only 1–5% of sessions are captured. That’s enough for general trends but unreliable when you need to catch performance blockers. Even during development, you never know which sessions will be recorded. Aggregated metrics further hide per-session details, making it harder to reproduce and debug regressions.
Limited visibility into runtime behavior
Out of the box, Firebase doesn’t provide insights into component resolution lifecycles, dependency injection (DI) graph resolution, execution across main/background threads, or component initialization that freeze user screens. Gaining partial visibility requires custom traces, manual breadcrumbs, and additional infrastructure, which leads to:
👉 Kotzilla solves these challenges out of the box:
In Firebase, getting deep insights into Android app performance often requires managing multiple tools and workflows:
👉 Kotzilla provides a purpose-built dashboard for Kotlin apps, automatically correlating performance issues, crashes all in a single view. Key advantages include:
This unified approach reduces engineering overhead and also improves MTTR and user experience, giving you the confidence that you are addressing the most impactful issues first.
Another major hidden cost in Firebase is the lack of a unified view for all issues. Performance Monitoring and Crashlytics are separate SDKs with distinct consoles, making it difficult to see how performance issues in a session may later cause crashes or ANRs.
👉 Kotzilla captures both performance and crash data in the same SDK and dashboard, fully correlated at the session and component level. You and your team can instantly see:
This unified visibility reduces investigation time and allows you to proactively fix issues before they impact users or trigger Android Vitals thresholds.
While Crashlytics now includes initial support for AI recommendations via Gemini, these currently cover only crashes. Performance issues still require manual investigation and fixes: instrumenting traces, identifying critical paths, and correlating data across sessions.
👉 Kotzilla takes Android, KMP and CMP performance monitoring a step further. By capturing the right runtime context for both crashes and performance issues, the platform generates contextual AI prompts tailored to each specific problem. You can use these prompts directly with your favorite AI coding assistants (Copilot, Gemini, Claude, or others) helping you resolve issues faster.
How it works with Kotzilla:
Across all these areas, the true cost of Firebase isn’t just infrastructure and additional services it’s developer effort:
👉 With Kotzilla, you can focus on preventing and fixing issues:
The Kotzilla Platform has a predictable and scalable pricing:
As discussed in the previous sections, the true cost of Firebase isn’t just financial. It’s also developer effort spent instrumenting traces, debugging regressions, and maintaining dashboards.
Total cost of ownership (TCO) is only part of the story. Real ROI comes from protecting users, revenue, and app reputation by preventing downtime and resolving issues faster.
Here are some examples of the impact of performance issues on mobile apps:
In typical Firebase setups, performance issues and crashes are only detected after they impact users, which slows down resolution and increases business risk.
By the time issues are fixed, users may have already abandoned your app, and revenue may be lost.
Kotzilla helps teams detect most issues early and resolve production ones faster:
All of this is possible thanks to contextual runtime data and the ability to integrate with your preferred AI coding assistant for actionable, issue-specific recommendations.
Real-world ROI:
| Metric | Improvement | How it’s achieved |
|---|---|---|
| Monitoring Costs | 50% lower | Essential runtime data automatically captured |
| Cost of Fixes | 10× reduced | Issues caught during development |
| MTTR in Production | 5× faster | Contextual AI-assisted resolution |
In this article Beyond MTTR: The ROI of Early Issue Detection in Kotlin Apps I share more details into how the Kotzilla Platform delivers better ROI than most traditional tools:
Firebase Performance Monitoring may look free, but once you add custom traces, cloud storage, ETL pipelines, and developer time, the true cost quickly rises. Many issues go undetected until they impact users.
Beyond the money, the bigger price is developer effort spent instrumenting and maintaining instead of fixing and improving.
The Kotzilla Platform is built for Kotlin teams using Koin. It delivers automatic Koin-level insights, unified crash and performance data, and AI-powered recommendations. With per-session, per-thread, and per-component context, you can spot problems earlier, resolve production issues faster, and keep your focus on building features.
The result: lower monitoring costs, faster fixes, fewer ANRs and crashes, and more time to build apps your users love.
About the Author This article was written by Miguel Valdes-Faura from the Kotzilla team. Kotzilla provides AI-powered performance monitoring for Koin-based Android applications, trusted by leading companies like Canal+, TotalEnergies, Worldline, Volkswagen, and Литрес to speed up issue resolution and reduce downtime. Follow us for more insights on Android development best practices and performance optimization strategies.