Beyond MTTR: The ROI of early issue detection in Kotlin apps

TL;DR

App downtime and performance issues cost businesses thousands to millions per hour in lost revenue and developer time. Traditional debugging tools often only help after issues disrupt production, leading to expensive fixes and delays.

The Kotzilla Platform helps Kotlin developers prevent these losses by:

• Identifying issues early in the development process, reducing the number of problems that reach production.
• Reducing MTTR (Mean Time to Resolution) in both development and production by identifying the root cause of issues without relying on manual tracing.
• Providing visibility into the execution of components and dependencies across different app threads, enabling the detection of performance and structural issues that can cause downtime and degrade user satisfaction.

Overview

You’ve seen it happen before, your app is running smoothly until suddenly, it’s not.

Users start reporting issues. Performance slows down. Your team drops everything to investigate. Hours or even days are spent looking into logs, adding traces, and trying to pinpoint the problem.

By the time you finally fix it, the damage is done:

• Revenue is lost.
• Users are frustrated.
• Your team’s time has been wasted.

In this article, I’ll break down the hidden costs of downtime, why traditional debugging tools often fall short, and how early detection can save your team time, money, and frustration. I’ll also introduce you to Kotzilla, a platform designed to help you catch and fix issues before they ever reach production.

The true cost of downtime

Downtime isn’t just about your app being unavailable. It has a domino effect:

• Lost revenue: If users can’t access your app, they can’t make purchases or view ads. Both are critical sources of revenue in the mobile economy.
• Frustrated customers: if your app crashes or runs slowly, users will leave bad reviews or worse, stop using it altogether.
• Wasted developer time: instead of working on new features, your team is stuck fixing problems.

And the numbers prove just how costly this can be:

• IT downtime costs an average of $5,600 per minute (source: Atlassian and Gartner)
• Major outages can cost between $74,000 and $1 million per hour (source: Infrascale)
• 75% of mobile companies say slow releases cost them at least $100,000 per year, for some, it’s as much as $10 million (source: Kobiton)

The problem with fixing issues in production

The second something breaks in production, the clock starts ticking.

Every hour spent troubleshooting is an hour taken away from building new features. That’s why Mean Time to Resolution (MTTR) is such an important metric:

• Top-performing teams fix issues in under an hour.
• For the majority of the teams can take days or even weeks (source: Splunk and DORA)

Most debugging tools are reactive and they only help you after an issue has already disrupted production.

According to The National Institute of Standards and Technology (NIST), fixing an error during the design phase can cost up to 100 times less than fixing it after deployment (source: NIST)

To truly optimize performance and prevent downtime, it’s important to:

• Reduce MTTR in production by quickly pinpointing the root cause without relying on manual logging.
• Identify issues early in the development process to reduce the number of problems that reach production.
• Gain full visibility into component execution and dependencies across different app threads. This helps detect structural problems early, preventing scalability issues down the road.

Why traditional tools leave you guessing

Imagine that you release an update, and suddenly, your app starts to get slow. Some users experience freezes, others complain about slow loading times. You check your monitoring dashboard.

An ANR alert pops up. Great! But what caused it?

There’s a delay, but no clear link to the actual component responsible. You click on more details to see additional info in dedicated troubleshooting views. A lot of information is shown, but no clear data about the issue or its impact on the main thread execution.

In fact, the troubleshooting view showed a lot of activity related to coroutines execution, which didn't add much value related to this issue.

So, you start guessing. Which component or dependency could be blocking the main thread? You introduce manual tracing in some components. More time spent adding custom spans, rebuilding, testing. Eventually, you find the problem: a ViewModel initialization blocking the main thread.

Now, imagine a background task slowing down silently, not enough to trigger an ANR but still affecting performance. Traditional tools don’t even register it if this is related to a slow component or dependency resolution. You only discover the problem when users complain.

The same happens with dependency resolution issues. If a slow dependency is dragging down startup time, most tools won’t tell you why, just that something is wrong. You’re left manually mapping dependencies, adding even more logging, just to figure out what should have been obvious.

This is the core problem:

• Traditional tools typically reacts after a blocking issue surface
• They detect symptoms, but the root cause often stays hidden unless it's related to a slow database query call, latencies in the network or in API services calls.
• You need to connect the dots with logs, traces, and manual debugging.

Detect more issues early and understand their root causes

The Kotzilla Platform is designed to help you see how your app behaves in real-time, linking issues to the specific components, dependencies, and threads they run on. Whether you’re debugging during development or dealing with a production crisis, the platform makes sure you understand both the symptom and the root cause behind the issue so you can fix it quickly.

Here are the main components of the Kotzilla Platform:

Koin IDE Plugin: visualize your app structure and catch configuration issues

As your app grows and its dependency graph becomes more complex, small configuration errors can start to appear, unnoticed at first but potentially causing big issues down the line. The Koin IDE Plugin is here to catch those issues:

• Visualize your app’s structure: the plugin offers a tree view of your Koin configuration, helping you understand how components and dependencies are wired together within your app and to allowing you to navigate between this view and the code.
• Detect configuration issues : The plugin detects potential misconfigurations like missing or circular dependencies while you’re still coding, so you can fix them before they lead to runtime errors.

Kotzilla SDK: capture data and detect issues early, even in production

By connecting directly to your Koin container, the SDK captures real-time data on how your components and dependencies execute. Whether you’re testing a new feature in your debug builds or debugging a live app in production, Kotzilla ensures you can detect critical issues and structural inefficiencies before they escalate:

• Real-time data capture: The SDK tracks the execution flow across different threads, helping you pinpoint performance bottlenecks whether it's slow UI rendering, app freezes, or long startup times.
• Spot both critical and structural issues: Kotzilla not only identifies issues that affect user experience, like slow rendering or ANRs, but also uncovers deeper structural problems such as inefficiencies in dependency resolution or poor thread management that can prevent your app from scaling in the future.

Kotzilla Console: root cause analysis when you need It most

The Kotzilla Console is where you can further investigate not just what went wrong, but why it happened in the first place:

• Assess issue impact and prioritisation: The Console provides insights into which user sessions are impacted, including app versions, devices, and the severity of the issue, allowing you to quickly assess the scope and prioritize resolution.
• Trace execution flow: From the ViewModel to background execution, Kotzilla shows how components and dependencies interact, so you can easily track down where things started to break.

Back to our ANR example

Let’s go back to our previous scenario. You remember: you release an update, and suddenly, your app starts to slow down.

You check the Kotzilla Console or your Android Studio through the Koin IDE Plugin, and see a "Main Thread Performance Issue" detected.

The issue already contains the exact component responsible for the slowdown:

• com.google.samples.apps.nowinandroid.MainActivityViewModel
• Resolution is Blocking Main Thread

No more guessing. No need to manually add traces or sift through logs. The information you need is already there.

You click on the issue to investigate further:

• How many user sessions are impacted?
• Which app versions are affected?
• How long did the component resolution take?

To analyze the root cause, you open one of the impacted user sessions and drill down into the sequence of events that led to the issue. The execution flow visualization reveals that he actual source of the issue isn’t the ViewModel itself, it’s one of its dependencies, the UserRepository dependency.

You can now take immediate action by offloading heavy data processing such as large dataset operations like filtering or mapping from the main thread to a background thread.

Kotzilla’s economic impact on Kotlin apps debugging

As discussed in previous sections, the true cost of issues in your Kotlin app isn't just about how much time you spend fixing them. It's about the broader impact on your bottom line, from lost revenue to wasted developer hours, and the long-term scalability of your app.

The Kotzilla platform has been specifically designed for Kotlin developers using Koin, providing full visibility into how components and dependencies interact within your app. Whether you’re debugging in development or troubleshooting live production issues, Kotzilla ensures you have the real-time data and insights needed to diagnose and resolve problems quickly, avoiding the costs of downtime, performance degradation, and inefficient debugging processes.

Let’s break down the key areas where the platform provides measurable cost savings:

1. Cost of downtime avoidance in production

• Average cost of downtime per hour: you can lose substantial revenue for every minute or hour your app is down.
• Estimated downtime hours prevented annually: Kotzilla’s early detection reduces the downtime caused by critical issues.

Annual savings = cost of downtime per hour × downtime hours prevented

2. Savings from proactive issue resolution

• Average cost to fix an issue in development: Kotzilla helps resolve issues during development, potentially saving up to 100 times the cost of fixing the same issue in production.
• Average cost to fix an issue in production: The cost of fixing issues during production is substantially higher due to lost revenue, downtime, and more intensive developer time.

Production cost = average cost to fix in production × number of issues
Development cost = average cost to fix in production / 100 × number of issues

Annual savings = production cost − development cost

3. Savings from fixing remaining issues in production

While Kotzilla helps prevent many issues during development, some problems will still happen in production, especially those that only occur on specific hardware models, OS versions, or device configurations. Kotzilla’s platform enables quicker detection and resolution of these issues, leading to important cost savings by reducing both Mean Time to Resolution (MTTR) and developer time spent debugging.

• Number of issues remaining in production
• Average cost to fix an issue in production
• Average developer hourly rate
• MTTR
• Costs of logging

Total Cost = (number of issues remaining × average cost to fix in production) + (number of issues remaining × MTTR × average developer hourly rate) + total logging costs.

Savings = total cost (without Kotzilla Platform) - total cost (with Kotzilla Platform)

Conclusion

The true cost of app issues isn’t just the time spent fixing them, but the impact on revenue, customer satisfaction, and team productivity. Traditional debugging tools often leave you reacting to problems in production after the fact. With the Kotzilla Platform, you can identify and resolve a lot of critical and structural issues early before they escalate.

By providing deep visibility into your app’s components and dependencies, the platform helps you avoid the high costs of fixing issues in production, reduce downtime, and save on both developer time and expensive debugging efforts.