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Optimize cross-platform mobile apps with Datadog RUM and Kotlin Multiplatform support
2025-05-20 · via Datadog | The Monitor blog

Mobile developers are increasingly adopting Kotlin Multiplatform to share business logic across iOS and Android. While Kotlin Multiplatform reduces duplication of code-writing efforts, it also introduces blind spots. Developers often lack real-time visibility into how shared code performs across platforms, making it harder to troubleshoot issues and monitor user experience.

The Datadog Kotlin Multiplatform SDK provides a unified integration that brings observability directly into your shared code. With one setup, your mobile teams gain access to a full suite of monitoring capabilities that include Datadog Real User Monitoring (RUM), Crash Reporting and Error Tracking, Session Replay, and logs. You can control these capabilities from the shared layer to provide consistency and prevent redundancy.

In this post, we’ll explain how the Datadog Kotlin Multiplatform SDK provides visibility into cross-platform mobile apps by helping you:

Debug performance issues across platforms

Performance bottlenecks in mobile apps can stem from many layers, from shared logic to platform-specific UI code. In Kotlin Multiplatform projects, identifying where those slowdowns occur requires clear, consistent visibility across both iOS and Android.

Datadog RUM provides visibility into screen load times, user actions, backend request durations, and Mobile Vitals such as frozen frames and memory usage across both platforms. With the Kotlin Multiplatform SDK, you can instrument your code one time in the commonMain source set and track performance consistently without duplicating work.

If your app uses Ktor for network requests, Datadog automatically collects performance data for those calls across both iOS and Android. Datadog also handles the propagation of tracing headers to achieve frontend-to-backend distributed tracing that provides complete information about application requests. Datadog RUM captures screen load metrics and helps you correlate issues with shared business logic and platform-specific components by providing stack traces and session context. These capabilities help you identify the root cause of issues, reduce debugging time, and maintain consistent performance.

Distributed tracing in Datadog RUM.
Distributed tracing.
Distributed tracing in Datadog RUM.

Investigate crashes and stability issues

Crashes and stability issues can happen anywhere in a mobile stack, whether in shared code or native implementations. Without centralized crash tracking, developers often rely on fragmented tools or manual reproduction steps to pinpoint the issue.

With the Datadog Kotlin Multiplatform SDK, you can collect crash reports that include app hangs and watchdog terminations on iOS and Application Not Responding (ANR) errors on Android, all from the single codebase. You can then correlate these findings with real user sessions in Datadog RUM. You receive critical context for every crash: what the user was doing, which screen the user was on, and which logs or events preceded the issue.

Datadog links the crash and error data with session-level insights, so you can view the stack trace, device state, and user actions together in one place. If an exception or error occurs in shared logic, or if a crash happens due to memory pressure in iOS, you can analyze it without needing to reproduce the issue manually. Logs that are collected from the shared module add even more detail to accelerate root cause analysis.

An Android ANR error shown in Datadog RUM.
ANR error.
An Android ANR error shown in Datadog RUM.

Establish a single source of truth for cross-platform monitoring

Even with shared business logic, iOS and Android mobile teams often remain siloed when it comes to monitoring and debugging. Different tools, logs, and workflows can slow down collaboration and obscure the full picture.

Datadog enables teams to use a single integration point in the commonMain module to unify how they track app performance, stability, and user behavior across platforms. This shared observability setup helps developers stay aligned and respond to issues faster.

When building shared experiences such as onboarding of a new product for a company or checkout for purchases in an ecommerce application, teams can use Datadog to monitor how a given feature performs on each platform. With dashboards and alerts built from the same dataset, teams can quickly spot inconsistencies, track feature usage with Product Analytics, and review real user flows by using Session Replay. Everyone works from the same data, reducing delays and simplifying collaboration.

An event timeline of a user session in Session Replay.
An event timeline of detected user frustration.
An event timeline of a user session in Session Replay.

Start monitoring Kotlin Multiplatform applications today

Kotlin Multiplatform helps mobile teams simplify development by sharing business logic across iOS and Android platforms, but monitoring can remain fragmented without the right tools. The Datadog Kotlin Multiplatform SDK bridges that gap by giving your teams real-time visibility into performance, stability, and user behavior, all from a single shared integration. As a result, your teams can reduce blind spots, debug issues faster, and deliver more consistent user experiences without duplicating setup or splitting workflows between platforms. To get started, see the Kotlin Multiplatform SDK documentation.

If you don’t already have a Datadog account, you can sign up for a 14-day free trial.