Is Firebase Performance Monitoring Really Free? Comparing True Costs and ROI with Kotzilla

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 Performance Monitoring – under the hood costs

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:

Total Cost of Ownership (TCO): Why Firebase isn’t really free

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.

1. Full visibility and contextual correlation

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:

• Engineering overhead to instrument and maintain traces
• Extra infrastructure costs (Firestore, ETL pipelines)
• Risk of blind spots if critical traces are missing

👉 Kotzilla solves these challenges out of the box:

• In development, 100% of user sessions are captured; in production, you can choose the sampling rate.
• As an Android developer, you get per-session, per-thread, and per-component insights, fully correlated with app state, so you see exactly how a slow dependency, component, or thread impacts user experience, without manual tracing.

2. Advanced dashboards and real-time alerts

In Firebase, getting deep insights into Android app performance often requires managing multiple tools and workflows:

• Multiple tools required: Performance Monitoring, Crashlytics, and Analytics must be combined to get a full picture.
• Custom pipelines needed: Data often needs exporting to BigQuery or processing via custom ETL pipelines.
• Limited alerting: While Firebase provides alerts for aggregate metrics (i.e, app start time), it does not natively support alerts tied to specific components. This makes proactive, component-level monitoring more difficult without custom solutions.
• Manual correlation: Engineers spend significant time stitching data together to understand what’s happening in each user session.

👉 Kotzilla provides a purpose-built dashboard for Kotlin apps, automatically correlating performance issues, crashes all in a single view. Key advantages include:

• Prioritized issue tracking: Dashboards automatically sort problems by criticality, helping you and your team focus on issues that impact users and business outcomes first.
• Per-session visibility: Track slow components, thread blocking, and crashes within the same user session to understand root causes.
• Built-in alerts & notifications: Receive real-time, component-aware alerts via email with no extra setup. Teams immediately know which component is causing the issue.
• Actionable insights out of the box: No custom ETL pipelines, manual dashboards or custom traces required

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.

3. Unified view of crashes and performance Issues in Android, KMP and CMP apps

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.

• You must manually correlate sessions across dashboards
• Cognitive overhead increases, slowing root cause analysis
• Early signs of issues that trigger crashes or ANRs may go unnoticed until users are affected

👉 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:

• Which slow ViewModel or dependency resolution is slowing down your app
• How thread blocking or worker delays contributed to ANRs
• Complete chains of events across threads, components, and sessions

This unified visibility reduces investigation time and allows you to proactively fix issues before they impact users or trigger Android Vitals thresholds.

4. AI-Powered insights and fix recommendations

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:

1. Automatic Issue Detection: Captures crashes, slow startups, and performance bottlenecks with full context.
2. Contextual AI Prompts for Fixes: Generates actionable, issue-specific recommendations for AI coding assistants.
3. Continuous Monitoring & Validation: Tracks runtime after fixes, alerts teams to regressions, and ensures ongoing stability.

5. Engineering time: the biggest hidden cost for Android developments teams

Across all these areas, the true cost of Firebase isn’t just infrastructure and additional services it’s developer effort:

• Instrumenting hundreds of custom traces
• Debugging performance regressions without full session context
• Maintaining dashboards or ETL pipelines
• Investigating root causes of ANRs and crashes after users are affected

👉 With Kotzilla, you can focus on preventing and fixing issues:

• Component-level traces are automatically captured
• Per-session visibility across threads and dependency graphs is built-in
• Dashboards, alerts, and workflows are ready to use
• Developers spend time fixing issues

The Kotzilla Platform has a predictable and scalable pricing:

• Solo Dev (Free): 1M events, 1 user, unlimited applications monitored
• Dev Team (59€/user/month): 1M events/month per user, up to 12 users, unlimited applications monitored, with team collaboration and dedicated support. Additional data batches of 1M events can be added as needed

Real ROI: Preventing ANRs, crashes, and reducing downtime

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:

• Android Vitals sets thresholds for ANRs (0.47% of sessions) and crashes (1.09%). Breaching these thresholds can reduce app visibility on Google Play, trigger store listing warnings, and damage user retention, app reputation, and business revenue.
• 75% of mobile companies report that slow releases cost them at least $100,000 per year; for some, it’s as much as $10 million (source: Kobiton).

Firebase Performance Monitoring workflows are reactive

In typical Firebase setups, performance issues and crashes are only detected after they impact users, which slows down resolution and increases business risk.

1. ANRs or crashes happen in production
2. Google Play Vitals flags negative trends
3. Developers investigate manually through Crashlytics and Performance Monitoring

By the time issues are fixed, users may have already abandoned your app, and revenue may be lost.

The Kotzilla Platform: Proactive issue detection & resolution

Kotzilla helps teams detect most issues early and resolve production ones faster:

• Identify early signs of issues: Spot performance bottlenecks, slow component initialization and crashes before they affect users
• Catch more issues before production: Detect a large number of potential issues and regressions during development
• Resolve complex production issues faster: Quickly address problems that only appear under certain devices, configurations, or edge-case scenarios

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:

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:

• Detection and resolution costs drop significantly compared to manual Firebase workflows
• Teams avoid lost revenue due to unplanned downtime
• App reliability and user satisfaction improve, reinforcing Play Store visibility

Conclusion

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.